39,019 results
Search Results
2. Computer Computing and Simulation—In View of the Leaves’ Categories, Shapes and Mass
- Author
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Li, Jiahong, Li, Heng, Fu, Qiang, Rannenberg, Kai, Editor-in-chief, Sakarovitch, Jacques, Series editor, Goedicke, Michael, Series editor, Tatnall, Arthur, Series editor, Neuhold, Erich J., Series editor, Pras, Aiko, Series editor, Tröltzsch, Fredi, Series editor, Pries-Heje, Jan, Series editor, Whitehouse, Diane, Series editor, Reis, Ricardo, Series editor, Furnell, Steven, Series editor, Furbach, Ulrich, Series editor, Gulliksen, Jan, Series editor, Rauterberg, Matthias, Series editor, Li, Daoliang, editor, and Chen, Yingyi, editor
- Published
- 2015
- Full Text
- View/download PDF
3. Short Paper: Mechanized Proofs of Verifiability and Privacy in a Paper-Based E-Voting Scheme
- Author
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Marie-Laure Zollinger, Peter Y. A. Ryan, and Peter B. Rønne
- Subjects
Scheme (programming language) ,050101 languages & linguistics ,Theoretical computer science ,Cryptographic primitive ,Computer science ,media_common.quotation_subject ,05 social sciences ,Short paper ,02 engineering and technology ,Gas meter prover ,Mathematical proof ,Voting ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,0501 psychology and cognitive sciences ,computer ,Formal verification ,Protocol (object-oriented programming) ,computer.programming_language ,media_common - Abstract
Electryo is a paper-based voting protocol that implements the Selene mechanism for individual verifiability. This short paper aims to provide the first formal model of Electryo, with security proofs for vote-privacy and individual verifiability. In general, voting protocols are complex constructs, involving advanced cryptographic primitives and strong security guarantees, posing a serious challenge when wanting to analyse and prove security with formal verification tools. Here we choose to use the \({{\,\mathrm{\textsc {Tamarin}}\,}}\) prover since it is one of the more advanced tools and is able to handle many of the primitives we encounter in the design and analysis of voting protocols.
- Published
- 2020
4. The Norwegian State Railway System GTL (1976)
- Author
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Steine, Tor Olav, Rannenberg, Kai, Editor-in-chief, Sakarovitch, Jacques, Series editor, Goedicke, Michael, Series editor, Tatnall, Arthur, Series editor, Neuhold, Erich J., Series editor, Pras, Aiko, Series editor, Tröltzsch, Fredi, Series editor, Pries-Heje, Jan, Series editor, Whitehouse, Diane, Series editor, Reis, Ricardo, Series editor, Murayama, Yuko, Series editor, Dillon, Tharam, Series editor, Gulliksen, Jan, Series editor, Rauterberg, Matthias, Series editor, Gram, Christian, editor, Rasmussen, Per, editor, and Østergaard, Søren Duus, editor
- Published
- 2015
- Full Text
- View/download PDF
5. Network Security for Home IoT Devices Must Involve the User: A Position Paper
- Author
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Antonio Mignano and Lorenzo De Carli
- Subjects
business.industry ,Bar (music) ,Computer science ,Security design ,Network security ,05 social sciences ,Fingerprint (computing) ,050801 communication & media studies ,Computer security ,computer.software_genre ,0508 media and communications ,Position paper ,0501 psychology and cognitive sciences ,Internet of Things ,business ,computer ,050107 human factors - Abstract
Many home IoT devices suffer from poor security design and confusing interfaces, lowering the bar for successful cyberattacks. A popular approach to identify compromised IoT devices is network-based detection, in which network traffic is analyzed to fingerprint and identify such devices. However, while several network-based techniques for identifying misbehaving devices have been proposed, the role of the user in remediating IoT security incidents has been conspicuously overlooked.
- Published
- 2021
6. Auto-Generating Examination Paper Based on Genetic Algorithms
- Author
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Na Deng, Yipeng Li, Shudong Liu, Yutian Liu, Deliang Zhong, and Xu Chen
- Subjects
business.industry ,Computer science ,Online learning ,Paper based ,Machine learning ,computer.software_genre ,Test (assessment) ,Order (exchange) ,Factor (programming language) ,Line (geometry) ,Genetic algorithm ,Artificial intelligence ,Informatization ,business ,computer ,computer.programming_language - Abstract
With the acceleration of education informatization, the social demand for online examination papers is increasing. However, there are some problems in the generation of online examination papers. Firstly, it is impossible to randomly generate examination papers quickly. Besides, it is impossible to dynamically adjust examination papers according to test results. Thirdly, it is impossible to generate examination papers based on individual characteristics of students. In order to solve these problems, this paper proposes a new auto-generation examination paper model based on genetic algorithm. The model dynamically adjusts the difficulty factor of individual test questions by analyzing the online learning data and historical user test result data, and then guarantees the difficulty of generating examination papers in line with the changes in the current educational environment. The simulation results show that the algorithm improves the efficiency and accuracy of the generation examination paper, and effectively controls the difficulty coefficient of the examination paper.
- Published
- 2019
7. Talmudic Norms Approach to Mixtures with a Solution to the Paradox of the Heap: A Position Paper
- Author
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Esther David, Rabbi S. David, Uri J. Schild, and Dov M. Gabbay
- Subjects
Programming language ,Computer science ,TheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS ,Sorites paradox ,Position paper ,computer.software_genre ,computer ,Object (philosophy) ,Heap (data structure) - Abstract
This paper offers a Talmudic norms solution to the paradox of the heap. The claim is that the paradox arises because philosophers use the wrong language to discuss it. We need a language about objects which is capable of expressing not only the declarative properties of the object (such as being a heap) but also how the object/heap was constructed. Such a view of objects comes from the Talmudic theory of mixtures.
- Published
- 2020
8. Short Paper - Taming the Shape Shifter: Detecting Anti-fingerprinting Browsers
- Author
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Babak Amin Azad, Pierre Laperdrix, Oleksii Starov, and Nick Nikiforakis
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Current generation ,Computer science ,Data_MISCELLANEOUS ,Fingerprint (computing) ,Short paper ,020206 networking & telecommunications ,02 engineering and technology ,Variation (game tree) ,Computer security ,computer.software_genre ,Credit card ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,computer - Abstract
When it comes to leaked credentials and credit card information, we observe the development and use of anti-fingerprinting browsers by malicious actors. These tools are carefully designed to evade detection, often by mimicking the browsing environment of the victim whose credentials were stolen. Even though these tools are popular in the underground markets, they have not received enough attention by researchers. In this paper, we report on the first evaluation of four underground, commercial, and research anti-fingerprinting browsers and highlight their high success rate in bypassing browser fingerprinting. Despite their success against well-known fingerprinting methods and libraries, we show that even slightest variation in the simulated fingerprint compared to the real ones can give away the presence of anti-fingerprinting tools. As a result, we provide techniques and fingerprint-based signatures that can be used to detect the current generation of anti-fingerprinting browsers.
- Published
- 2020
9. 'BDD Assemble!': A Paper-Based Game Proposal for Behavior Driven Development Design Learning
- Author
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Victor Travassos Sarinho
- Subjects
Design learning ,Higher education ,Computer science ,business.industry ,ComputingMilieux_PERSONALCOMPUTING ,020207 software engineering ,02 engineering and technology ,Behavior-driven development ,Paper based ,computer.software_genre ,Simple (abstract algebra) ,ComputingMilieux_COMPUTERSANDEDUCATION ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,business ,Software engineering ,computer ,Educational game - Abstract
Game-based learning represents a promising alternative to teach computing in higher education. This paper presents “BDD Assemble!”, a paper-based game proposal for teaching Behavior Driven Development (BDD) competences. For this, the proposed game and the evaluation approach with software engineering students are described. As a result, a simple, interactive and colaborative game was provided, able to teach BDD concepts in a practical, competitive and fun way.
- Published
- 2019
10. Deep Learning Application in Security and Privacy – Theory and Practice: A Position Paper
- Author
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Konstantinos Markantonakis, Julia A. Meister, and Raja Naeem Akram
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business.industry ,Computer science ,media_common.quotation_subject ,Deep learning ,Multitude ,02 engineering and technology ,010501 environmental sciences ,Computer security ,computer.software_genre ,01 natural sciences ,Resilience (organizational) ,Adversarial system ,Software ,General Data Protection Regulation ,0202 electrical engineering, electronic engineering, information engineering ,Position paper ,020201 artificial intelligence & image processing ,Quality (business) ,Artificial intelligence ,business ,computer ,0105 earth and related environmental sciences ,media_common - Abstract
Technology is shaping our lives in a multitude of ways. This is fuelled by a technology infrastructure, both legacy and state of the art, composed of a heterogeneous group of hardware, software, services, and organisations. Such infrastructure faces a diverse range of challenges to its operations that include security, privacy, resilience, and quality of services. Among these, cybersecurity and privacy are taking the centre-stage, especially since the General Data Protection Regulation (GDPR) came into effect. Traditional security and privacy techniques are overstretched and adversarial actors have evolved to design exploitation techniques that circumvent protection. With the ever-increasing complexity of technology infrastructure, security and privacy-preservation specialists have started to look for adaptable and flexible protection methods that can evolve (potentially autonomously) as the adversarial actor changes its techniques. For this, Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) were put forward as saviours. In this paper, we look at the promises of AI, ML, and DL stated in academic and industrial literature and evaluate how realistic they are. We also put forward potential challenges a DL based security and privacy protection system has to overcome. Finally, we conclude the paper with a discussion on what steps the DL and the security and privacy-preservation community have to take to ensure that DL is not just going to be hype, but an opportunity to build a secure, reliable, and trusted technology infrastructure on which we can rely on for so much in our lives.
- Published
- 2019
11. (Short Paper) Effectiveness of Entropy-Based Features in High- and Low-Intensity DDoS Attacks Detection
- Author
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Abigail Koay, Winston K. G. Seah, and Ian Welch
- Subjects
Rényi entropy ,Computer science ,ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS ,Short paper ,0202 electrical engineering, electronic engineering, information engineering ,020206 networking & telecommunications ,020201 artificial intelligence & image processing ,Denial-of-service attack ,02 engineering and technology ,Data mining ,computer.software_genre ,computer - Abstract
DDoS attack detection using entropy-based features in network traffic has become a popular approach among researchers in the last five years. The use of traffic distribution features constructed using entropy measures has been proposed as a better approach to detect Distributed Denial of Service (DDoS) attacks compared to conventional volumetric methods, but it still lacks in the generality of detecting various intensity DDoS attacks accurately. In this paper, we focus on identifying effective entropy-based features to detect both high- and low-intensity DDoS attacks by exploring the effectiveness of entropy-based features in distinguishing the attack from normal traffic patterns. We hypothesise that using different entropy measures, window sizes, and entropy-based features may affect the accuracy of detecting DDoS attacks. This means that certain entropy measures, window sizes, and entropy-based features may reveal attack traffic amongst normal traffic better than the others. Our experimental results show that using Shannon, Tsallis and Zhou entropy measures can achieve a clearer distinction between DDoS attack traffic and normal traffic than Renyi entropy. In addition, the window size setting used in entropy construction has minimal influence in differentiating between DDoS attack traffic and normal traffic. The result of the effectiveness ranking shows that the commonly used features are less effective than other features extracted from traffic headers.
- Published
- 2019
12. The Current State and Path Forward For Enterprise Image Viewing: HIMSS-SIIM Collaborative White Paper
- Author
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Christopher J. Roth, Louis M. Lannum, Alexander J. Towbin, and Donald K. Dennison
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Diagnostic Imaging ,Imaging informatics ,genetic structures ,Computer science ,education ,Specialty ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Image viewer ,Image display ,computer.software_genre ,Image distribution ,Enterprise imaging ,030218 nuclear medicine & medical imaging ,Management Information Systems ,03 medical and health sciences ,0302 clinical medicine ,White paper ,Digital imaging and communications in medicine (DICOM) ,Integrating healthcare enterprise (IHE) ,Electronic Health Records ,Humans ,Radiology, Nuclear Medicine and imaging ,Use case ,Implementation ,PACS ,Medicine(all) ,Review Paper ,Cardiology PACS ,Radiological and Ultrasound Technology ,Multimedia ,Clinical image viewing ,Interpretation (philosophy) ,Electronic medical record (EMR) ,Enterprise PACS ,Computer Science Applications ,Management information systems ,Radiology Information Systems ,030220 oncology & carcinogenesis ,computer ,Cardiac imaging ,PATH (variable) ,Forecasting - Abstract
Clinical specialties have widely varied needs for diagnostic image interpretation, and clinical image and video image consumption. Enterprise viewers are being deployed as part of electronic health record implementations to present the broad spectrum of clinical imaging and multimedia content created in routine medical practice today. This white paper will describe the enterprise viewer use cases, drivers of recent growth, technical considerations, functionality differences between enterprise and specialty viewers, and likely future states. This white paper is aimed at CMIOs and CIOs interested in optimizing the image-enablement of their electronic health record or those who may be struggling with the many clinical image viewers their enterprises may employ today.
- Published
- 2016
13. Relation Extraction Toward Patent Domain Based on Keyword Strategy and Attention+BiLSTM Model (Short Paper)
- Author
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Junmei Han, Xindong You, Zhian Dong, Xueqiang Lv, and Xiangru Lv
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Computer science ,business.industry ,Short paper ,Pooling ,020206 networking & telecommunications ,02 engineering and technology ,computer.software_genre ,Relationship extraction ,Terminology ,Softmax function ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,Classifier (UML) ,Temporal information ,computer ,Sentence ,Natural language processing - Abstract
Patent terminology relation extraction is of great significance to the construction of patent Knowledge graph. In order to solve the problem of long-distance dependency in traditional depth learning, a new method of patent terminology relation extraction is proposed, which combines attention mechanism and bi-directional LSTM model and with keyword strategy. Category keyword features in each sentence obtained by the improved TextRank with the patent text information vectorization added. BiLSTM neural work and attention mechanism are employed to extract the temporal information and sentence-level global feature information. Moreover, pooling layer is added to obtain the local features of the text. Finally, we fuse the global features and local features, and output the final classification results through the softmax classifier. The addition of category keywords improves the distinction of categories. Substantial experimental results demonstrate that the proposed model outperform the state-of-art neural model in patent terminology relation extraction.
- Published
- 2019
14. Research on Intelligent Test Paper Based on Improved Genetic Algorithm
- Author
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Ruitao Nan and Jingmei Li
- Subjects
Measure (data warehouse) ,business.industry ,Computer science ,Quality education ,Paper based ,Machine learning ,computer.software_genre ,Test (assessment) ,Student achievement ,Genetic algorithm ,ComputingMilieux_COMPUTERSANDEDUCATION ,Artificial intelligence ,business ,computer - Abstract
At present, under the current quality education, the examination is still one of the main measure of teachers’ teaching ability and student achievement. At the same time, different levels of examination are different to the test paper. Aiming at the multi-combination of constraints in the test paper, an improved genetic algorithm is proposed, which combines the constraints of the papers effectively, so that the test papers can be maximized to meet the needs of the users.
- Published
- 2018
15. Paper-Code-Az: Steps for Assembling a Paper-Code for an Educational Robotic System
- Author
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Michael Funk, Armando B. Mendes, Francisco Pedro, José Cascalho, Paulo Novo, and Matthias Funk
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Syntax (programming languages) ,Computer science ,Educational robotics ,Programming language ,Arduino ,Code (cryptography) ,Robot ,Context (language use) ,Pattern matching ,computer.software_genre ,Mobile device ,computer - Abstract
In this article we present the Paper-Code-Az project that aims to implement a tangible programming language platform, in which the code is read by a mobile device camera, to be used by an Arduino robot for elementary school children. A description of the different stages of the project is discussed. In the context of the first phase, a language syntax is proposed, as well as the design of the blocks that constitute the elements of tangible language. Also discussed is the way in which each element of the language has an associated fiduciary label that guarantees its translation so that the program code can be executed by the robot.
- Published
- 2021
16. Cyber-Attacks on Internet of Things (IoT) Devices, Attack Vectors, and Remedies: A Position Paper
- Author
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Amit Singh and Shubham Prajapati
- Subjects
Exploit ,business.industry ,Computer science ,Denial-of-service attack ,Eavesdropping ,Privilege (computing) ,Man-in-the-middle attack ,Computer security ,computer.software_genre ,Information and Communications Technology ,Ransomware ,The Internet ,business ,computer - Abstract
With the upgrade of ICT infrastructure at a rocketed pace, diversification of applications and involvement of the Internet have increased. This evolution has led to the production, development, and implementation of various smart software/hardware solutions in multiple dimensions to make the process faster, smooth, accessible, and inclusive. The story of IoT (Internet of things) is a game-changer in several fields at different levels, starting from an office to home and industries. The term IoT was coined in 1999 by Kevin Ashton, since then it has seen an exponential growth, and now it has become ubiquitous. IoT may be summarized as the group of interrelated/interconnected devices embedded with sensors, software, actuator, and technology over the network for exchanging the data over the Internet without human involvement. Like any other technology, IoT has its pros and cons. In the last decade, cyber criminals have exploited many attack vectors, several of which can be used to exploit and launch attacks on IoT devices too. IoT attacks have increased substantially over the years, and there has been a jump of 900% in such attacks in 2019. Due to various constraints, IoT solutions don’t possess traditional security solutions or mechanisms to identify anomalies. Multiple security issues in IoT devices are persistent because of the limitation of computational power, hardware, and storage. These limitations make IoT devices more prone to cyber-attacks. IoT cyber-attacks are ranging from DDoS, MITM, brute-forcing, eavesdropping, privilege scaling to more sophisticated ransomware attacks and many more. This chapter will discuss multiple cyber-attacks, their mechanisms and TTPs, along with their impact on IoT infrastructure. This will also include security flaws that were exploited and related challenges in a holistic way at a single place. Statistical data leading to trend analysis along with shares of various attack campaigns shall also be highlighted in this study to give the readers more insight. In order to overcome these issues, remedial measures and mitigation policies will also be discussed.
- Published
- 2021
17. Position Paper on Recent Cybersecurity Trends: Legal Issues, AI and IoT
- Author
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Xuan Wang, Junbin Fang, Frankie Li, Jing Li, Yun Ju Huang, and Yang Xiang
- Subjects
Computer science ,business.industry ,020206 networking & telecommunications ,020207 software engineering ,02 engineering and technology ,Computer security ,computer.software_genre ,Cybercrime ,Mobile security ,General Data Protection Regulation ,0202 electrical engineering, electronic engineering, information engineering ,Ransomware ,Position paper ,Detection performance ,Internet of Things ,business ,computer - Abstract
There is a large number of high-profile cyberattacks identified in the year of 2017, i.e., Ransomware attacks are one of the areas of cybercrime growing the fastest. These increasingly sophisticated cyberattacks are forcing various organisations to face security challenges and invest money building security and trust models. There will also be an increase in the use of recent development of security solutions that can help improve the detection performance and react to malicious events. In this position paper, we mainly introduce recent development trends in cybersecurity, including legal issues (e.g., GDPR), Artificial intelligence (AI), Mobile security and Internet of Things.
- Published
- 2018
18. Position Paper on Blockchain Technology: Smart Contract and Applications
- Author
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Weizhi Meng, Zuoxia Yu, Sherman S. M. Chow, Joseph K. Liu, Jin Li, Jianfeng Wang, Yongjun Zhao, and Xianmin Wang
- Subjects
Cryptocurrency ,Blockchain ,Smart contract ,Computer science ,business.industry ,020207 software engineering ,02 engineering and technology ,Computer security ,computer.software_genre ,Component (UML) ,0202 electrical engineering, electronic engineering, information engineering ,Position paper ,020201 artificial intelligence & image processing ,business ,Database transaction ,computer ,Financial services ,Risk management - Abstract
Blockchain technology enables a transaction to be handled in a decentralized fashion. In this position paper, we aim to introduce the background of blockchain technology, discuss one of its important component — smart contract, and present its recent applications in many fields such as cryptocurrency, financial services, risk management, and Internet of Things.
- Published
- 2018
19. (Short Paper) Evidence Collection and Preservation System with Virtual Machine Monitoring
- Author
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Toru Nakamura, Hiroshi Ito, Toshihiro Yamauchi, and Shinsaku Kiyomoto
- Subjects
Database ,Computer science ,Virtual machine ,Hash function ,Overhead (computing) ,Hypervisor ,Information technology audit ,Evidence collection ,computer.software_genre ,computer ,PATH (variable) ,Semantic gap - Abstract
In a system audit and verification, it is important to securely collect and preserve evidence of execution environments, execution processes, and program execution results. Evidence-based verification of program processes ensures their authenticity; for example, the processes include no altered/infected program library. This paper proposes a solution for collection of evidence on program libraries based on Virtual Machine Monitor (VMM). The solution can solve semantic gap by obtaining library file path names. This paper also shows a way to obtain hash values of library files from a guest OS. Furthermore, this paper provides examples of evidence on program execution and the overhead of the solution.
- Published
- 2021
20. Semantic Recommendation System for Bilingual Corpus of Academic Papers
- Author
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Irina Nikishina, Anna Safaryan, Petr Filchenkov, Andrey Kutuzov, and Weijia Yan
- Subjects
Word embedding ,Computer science ,business.industry ,Bilingual dictionary ,Cosine similarity ,Semantic search ,Recommender system ,computer.software_genre ,Task (project management) ,Semantic similarity ,Relevance (information retrieval) ,Artificial intelligence ,business ,computer ,Natural language processing - Abstract
We tested four methods of making document representations cross-lingual for the task of semantic search for the similar papers based on the corpus of papers from three Russian conferences on NLP: Dialogue, AIST and AINL. The pipeline consisted of three stages: preprocessing, word-by-word vectorisation using models obtained with various methods to map vectors from two independent vector spaces to a common one, and search for the most similar papers based on the cosine similarity of text vectors. The four methods used can be grouped into two approaches: 1) aligning two pretrained monolingual word embedding models with a bilingual dictionary on our own (for example, with the VecMap algorithm) and 2) using pre-aligned cross-lingual word embedding models (MUSE). To find out, which approach brings more benefit to the task, we conducted a manual evaluation of the results and calculated the average precision of recommendations for all the methods mentioned above. MUSE turned out to have the highest search relevance, but the other methods produced more recommendations in a language other than the one of the target paper.
- Published
- 2021
21. ContriSci: A BERT-Based Multitasking Deep Neural Architecture to Identify Contribution Statements from Research Papers
- Author
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Asif Ekbal, Ammaar Ahmad, Tirthankar Ghosal, and Komal Gupta
- Subjects
Statement (computer science) ,Comprehension ,Identification (information) ,Information extraction ,Information retrieval ,Computer science ,Human multitasking ,Scientific literature ,computer.software_genre ,Literature survey ,computer ,Sentence - Abstract
With the rapid growth of scientific literature, it is becoming increasingly difficult to identify scientific contribution from the deluge of research papers. Automatically identifying the specific contribution made in a research paper would help quicker comprehension of the work, faster literature survey, comparison with the related works, etc. Here in this work, we investigate methods to automatically extract the contribution statements from research articles. We design a multitask deep neural network leveraging section identification and citance classification of scientific statements to predict whether a given scientific statement specifies a contribution or not. In the long-run, we envisage to create a knowledge graph of scientific contributions for machine comprehension and more straightforward navigation of research contributions in a particular domain. Our approach achieves the best performance over earlier methods (a relative improvement of 8.08% in terms of \(F_1\) score) for contributing sentence identification over a dataset of Natural Language Processing (NLP) papers. We make our code available at here (https://github.com/ammaarahmad1999/Sem-Eval-2021-Task-A).
- Published
- 2021
22. Predicting the Age of Scientific Papers
- Author
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Pavel Savov, Adam Jatowt, and Radoslaw Nielek
- Subjects
business.industry ,Computer science ,Aggregate (data warehouse) ,Scientometrics ,computer.software_genre ,Ordinal regression ,Task (project management) ,Binary classification ,Artificial intelligence ,business ,computer ,Natural language processing ,Period (music) ,Sentence ,Social simulation - Abstract
In this paper we show how the age of scientific papers can be predicted given a diachronic corpus of papers from a particular domain published over a certain time period. We first train ordinal regression models for the task of predicting the age of individual sentences by fine-tuning series of BERT models for binary classification. We then aggregate the prediction results on individual sentences into a final result for entire papers. Using two corpora of publications from the International World Wide Web Conference and the Journal of Artificial Societies and Social Simulation, we compare various result aggregation methods, and show that the sentence-based approach produces better results than the direct document-level method.
- Published
- 2021
23. A Multi-view Active Learning Approach for the Hierarchical Multi-label Classification of Research Papers
- Author
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Mohamed Jmaiel, Hatem Bellaaj, and Abir Masmoudi
- Subjects
Multi-label classification ,Hierarchy (mathematics) ,Computer science ,business.industry ,Active learning (machine learning) ,Disjoint sets ,Machine learning ,computer.software_genre ,Oracle ,Field (computer science) ,Task (project management) ,Set (abstract data type) ,ComputingMethodologies_PATTERNRECOGNITION ,Artificial intelligence ,business ,computer - Abstract
In this paper, we focus on the hierarchical multi-label classification task of scientific papers, which consists in assigning to a paper the set of relevant classes, which are organized in a hierarchy. The difficulty of manually constructing sufficient labeled datasets renders challenging the automatic classification task of research papers according to hierarchical labels. Multi-view active learning is a widely adopted method to address this issue, by iteratively selecting the most useful unlabeled samples for the multi-view classifiers exploiting disjoint data’ views, and querying an oracle on their real labels. However, none of the state of the art studies in this field is proposed for the hierarchical multi-label classification task. In this paper, we propose an effective multi-view active learning framework for the hierarchical multi-label classification task, applied on scientific papers. Our approach adopts a novel selection strategy that relies on both uncertainty and representativeness criteria when selecting the most informative unlabeled samples in each iteration. Experimental results on a real world dataset of ACM research papers show the efficiency of our approach over several baseline methods.
- Published
- 2021
24. STellaR – A Stationary Telepresence Counselling System for Collaborative Work on Paper Documents
- Author
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Philipp Waag, Udo Seelmeyer, Anne-Kathrin Schmitz, Marc Weinhardt, Dominic Becking, and Matti Laak
- Subjects
Multimedia ,Microphone ,business.industry ,Computer science ,media_common.quotation_subject ,Sound system ,computer.software_genre ,Videoconferencing ,Work (electrical) ,The Internet ,Quality (business) ,business ,computer ,media_common - Abstract
This paper gives an overview of the ongoing project STellaR – A stationary telepresence counselling system for collaborative work on paper documents. The system consists of dedicated rooms for video counselling, which clients can use to connect to a remotely located counselor without requiring any knowledge about computers or the internet. STellaR rooms are equipped with a large monitor, high quality microphone, camera, and sound system, which represent the counselor in life size.
- Published
- 2021
25. Automatic Classification of Research Papers Using Machine Learning Approaches and Natural Language Processing
- Author
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Segarra-Faggioni Veronica and Ortiz Yesenia
- Subjects
Vocabulary ,business.industry ,Computer science ,media_common.quotation_subject ,Scopus ,020206 networking & telecommunications ,02 engineering and technology ,computer.software_genre ,Linear discriminant analysis ,Machine learning ,ComputingMethodologies_PATTERNRECOGNITION ,0202 electrical engineering, electronic engineering, information engineering ,Neighbor classifier ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,computer ,Natural language processing ,media_common - Abstract
This paper shows the automatic classification of research papers published in Scopus. Our classification is based on the research lines of the university. We apply the K-nearest neighbor classifier and linear discriminant analysis (LDA). Various stages were used from information gathering, creating the vocabulary, pre-processing and data training, and supervised classification in this work. The experiment involved 596 research articles published in SCOPUS from 2003–2017. The results show an overall accuracy of 88.44%.
- Published
- 2021
26. Coreference Resolution in Research Papers from Multiple Domains
- Author
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Ralph Ewerth, Daniel Uwe Müller, Anett Hoppe, and Arthur Brack
- Subjects
0301 basic medicine ,education.field_of_study ,Coreference ,Computer science ,business.industry ,Population ,02 engineering and technology ,Resolution (logic) ,computer.software_genre ,Task (project management) ,03 medical and health sciences ,Information extraction ,030104 developmental biology ,0202 electrical engineering, electronic engineering, information engineering ,Question answering ,020201 artificial intelligence & image processing ,Artificial intelligence ,education ,F1 score ,Transfer of learning ,business ,computer ,Natural language processing - Abstract
Coreference resolution is essential for automatic text understanding to facilitate high-level information retrieval tasks such as text summarisation or question answering. Previous work indicates that the performance of state-of-the-art approaches (e.g. based on BERT) noticeably declines when applied to scientific papers. In this paper, we investigate the task of coreference resolution in research papers and subsequent knowledge graph population. We present the following contributions: (1) We annotate a corpus for coreference resolution that comprises 10 different scientific disciplines from Science, Technology, and Medicine (STM); (2) We propose transfer learning for automatic coreference resolution in research papers; (3) We analyse the impact of coreference resolution on knowledge graph (KG) population; (4) We release a research KG that is automatically populated from 55,485 papers in 10 STM domains. Comprehensive experiments show the usefulness of the proposed approach. Our transfer learning approach considerably outperforms state-of-the-art baselines on our corpus with an F1 score of 61.4 (+11.0), while the evaluation against a gold standard KG shows that coreference resolution improves the quality of the populated KG significantly with an F1 score of 63.5 (+21.8).
- Published
- 2021
27. The Construction of a Collocation List Based on Academic Papers of Teaching Chinese to Speakers of Other Languages
- Author
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Qihong Zhou
- Subjects
Structure (mathematical logic) ,Collocation ,Computer science ,Dependency grammar ,Python (programming language) ,Collocation extraction ,Attributive ,Construct (philosophy) ,computer ,Linguistics ,Adverbial ,computer.programming_language - Abstract
This paper builds a collocation list in academic papers of teaching Chinese to speakers of other languages, based on the dependency parsing analysis. It adopts python to extract the Chinese academic collocations, analyzes the accuracy of collocation extraction, and compares with the collocation distribution of Wang Shuo's works. After setting the frequency and automatic threshold of mutual information, 12,357 pieces of collocations were obtained from academic papers of teaching Chinese to speakers of other languages, and there are 5,298 collocations from Wang Shuo's works. It is found that in the academic Chinese collocation list, the collocation frequency of attributive is the highest, followed by adverbials. The most overlapping part between academic Chinese and Wang Shuo's works is the adverbial structure. This study attempts to construct the collocation list in academic papers of teaching Chinese to speakers of other languages, which bears certain insights to academic Chinese teaching.
- Published
- 2021
28. Augmented Reality Enhanced Traditional Paper Book Reading Experience Design: A Case for University Library
- Author
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Zhen Liu and Peixuan Li
- Subjects
South china ,Multimedia ,business.industry ,Computer science ,media_common.quotation_subject ,Information technology ,Experience design ,computer.software_genre ,Book reading ,Interactivity ,Reading (process) ,Augmented reality ,business ,computer ,Application methods ,media_common - Abstract
Paper-based books in university libraries are important learning materials for university students, but there are some drawbacks in traditional reading methods, and it is necessary to utilize scientific and technological means to solve the pain points of users, i.e. the students. With the development of information technology, augmented reality (AR) technology has gradually penetrated into all areas of the students’ lives. The fusion of AR technology and traditional paper books brings a potential new approach of reading and a sense of experience. At present, the application of AR technology in library is mainly for book navigation and book protection. AR technology has also appeared in some children’s books, but most of the books are still in the traditional way of reading. Therefore, this research aims to implement AR technology with traditional reading methods, optimize the reading experience of paper books, and enhance the interactivity and interest of paper book reading. This article selects university students in the library of South China University of Technology for the case study. Firstly, it finds the application method of AR technology in the library through the literature, and then observes and interviews the students to summarize the pain points and design opportunities from traditional reading. Based on AR technology, this paper designed a social reading application with a human-oriented design concept, thereby optimizing the reading experience of paper books for library.
- Published
- 2021
29. S2CFT: A New Approach for Paper Submission Recommendation
- Author
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Dac Nguyen, Binh T. Nguyen, Son T. Huynh, Phong Thu Nguyen Huynh, and Cuong V. Dinh
- Subjects
Measure (data warehouse) ,Computer science ,02 engineering and technology ,Recommender system ,computer.software_genre ,Convolutional neural network ,GeneralLiterature_MISCELLANEOUS ,Term (time) ,Recommendation model ,03 medical and health sciences ,0302 clinical medicine ,030221 ophthalmology & optometry ,0202 electrical engineering, electronic engineering, information engineering ,Embedding ,020201 artificial intelligence & image processing ,Data mining ,computer - Abstract
There have been a massive number of conferences and journals in computer science that create a lot of difficulties for scientists, especially for early-stage researchers, to find the most suitable venue for their scientific submission. In this paper, we present a novel approach for building a paper submission recommendation system by using two different types of embedding methods, GloVe and FastText, as well as Convolutional Neural Network (CNN) and LSTM to extract useful features for a paper submission recommendation model. We consider seven combinations of initial attributes from a given submission: title, abstract, keywords, title + keyword, title + abstract, keyword + abstract, and title + keyword + abstract. We measure these approaches’ performance on one dataset, presented by Wang et al., in terms of top K accuracy and compare our methods with the S2RSCS model, the state-of-the-art algorithm on this dataset. The experimental results show that CNN + FastText can outperform other approaches (CNN + GloVe, LSTM + GloVe, LSTM + FastText, S2RSCS) in term of top 1 accuracy for seven types of input data. Without using a list of keywords in the input data, CNN + GloVe/FastText can surpass other techniques. It has a bit lower performance than S2RSCS in terms of the top 3 and top 5 accuracies when using the keyword information. Finally, the combination of S2RSCS and CNN + FastText, namely S2CFT, can create a better model that bypasses all other methods by top K accuracy (K = 1,3,5,10).
- Published
- 2021
30. SAVVIcode: Preventing mafia attacks on visual code authentication schemes (short paper)
- Author
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Jonathan Millican and Frank Stajano
- Subjects
Authentication ,Computer science ,Short paper ,Process (computing) ,computer.file_format ,Computer security ,computer.software_genre ,Login ,law.invention ,46 Information and Computing Sciences ,Order (business) ,Relay ,law ,Code (cryptography) ,Bitmap ,4604 Cybersecurity and Privacy ,computer - Abstract
Most visual code authentication schemes in the literature have been shown to be vulnerable to relay attacks: the attacker logs into the victim’s “account A” using credentials that the victim provides with the intent of logging into “account B”. Visual codes are not human-readable and therefore the victim cannot distinguish between the codes for A and B; on the other hand, codes must be machine-readable in order to automate the login process. We introduce a new type of visual code, the SAVVIcode, that contains an integrity-validated human-readable bitmap. With SAVVIcode, attackers have a harder time swapping visual codes surreptitiously because the integrity check prevents them from modifying or hiding the human-readable distinguisher.
- Published
- 2018
- Full Text
- View/download PDF
31. An Empirical Study of Semantic Mining of Scholarly Papers Using Wordnet API
- Author
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Ahmad Rawashdeh, Mohammad Rawashdeh, and Anvesh Allu
- Subjects
Matching (statistics) ,Point (typography) ,Computer science ,Head (linguistics) ,business.industry ,WordNet ,Ontology (information science) ,computer.software_genre ,Empirical research ,Rule-based machine translation ,Artificial intelligence ,business ,computer ,Word (computer architecture) ,Natural language processing - Abstract
This paper summarizes an empirical study of mining semantic information from the title/abstract of scientific papers’ dataset using the wordnet API. This summary includes description of the background, ideas, and research conducted using a program we wrote which uses Wordnet API and some other libraries. Semantic information from the abstract was obtained using wordnet (after stemming the words and selecting words belonging to certain tags), then these words were expanded, and then evaluated against the textual content of the same paper of which titles/abstracts were used as input. The semantic information is the hypernym (is-a relationship) of the stemmed words found in the title of each selected paper applied recursively (mined) using wordnet. That includes finding the hypernym of words and hypernyms of hypernyms recursively (until level 2). Every title and abstract, when written well, should contain a summary of the paper. By mining their semantic, one can get an insight of how much information can be obtained about the semantic of the paper using wordnet. Then the evaluation of that mining can be conducted by finding the percentage of matches between the semantic information found in the title/abstract and the content (body) of the same paper. It was found that the words/hypernyms: point, head, process are the most frequent matching in all papers. On the other hand, the word “value” is one of the least frequent but matching. It was also found that a paper about Grammars has the highest total number of matches (807 matches), and that the highest percentage of matches is 50%. That and other interesting results.
- Published
- 2020
32. Conference paper
- Author
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Michael Goldsmith, Mary K. Bispham, Ioannis Agrafiotis, Mori, P, Furnell, S, and Camp, O
- Subjects
Exploit ,Computer science ,05 social sciences ,Natural language understanding ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,020206 networking & telecommunications ,02 engineering and technology ,Computer security ,computer.software_genre ,Dialogue management ,050105 experimental psychology ,Speech interface ,Adversarial system ,OODA loop ,0202 electrical engineering, electronic engineering, information engineering ,0501 psychology and cognitive sciences ,computer - Abstract
This paper presents an attack and defence modelling framework for conceptualising the security of the speech interface. The modelling framework is based on the Observe-Orient-Decide-Act (OODA) loop model, which has been used to analyse adversarial interactions in a number of other areas. We map the different types of attacks that may be executed via the speech interface to the modelling framework, and present a critical analysis of the currently available defences for countering such attacks, with reference to the modelling framework. The paper then presents proposals for the development of new defence mechanisms that are grounded in the critical analysis of current defences. These proposals envisage a defence capability that would enable voice-controlled systems to detect potential attacks as part of their dialogue management functionality. In accordance with this high-level defence concept, the paper presents two specific proposals for defence mechanisms to be implemented as part of dialogue management functionality to counter attacks that exploit unintended functionality in speech recognition functionality and natural language understanding functionality. These defence mechanisms are based on the novel application of two existing technologies for security purposes. The specific proposals include the results of two feasibility tests that investigate the effectiveness of the proposed mechanisms in defending against the relevant type of attack.
- Published
- 2020
33. Generative Program Analysis and Beyond: The Power of Domain-Specific Languages (Invited Paper)
- Author
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Bernhard Steffen and Alnis Murtovi
- Subjects
050101 languages & linguistics ,Domain-specific language ,Binary decision diagram ,Generalization ,Computer science ,Programming language ,05 social sciences ,02 engineering and technology ,Mathematical proof ,computer.software_genre ,Operational semantics ,Program analysis ,Component (UML) ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,0501 psychology and cognitive sciences ,Temporal logic ,computer - Abstract
In this paper we position Linear Time Temporal Logic (LTL), structural operational semantics (SOS), and a graphical generalization of BNF as central DSLs for program analysis and verification tasks in order to illustrate the impact of language to the mindset: (1) Specifying program analyses in LTL changes the classical algorithmic ‘HOW’ thinking into a property-oriented ‘WHAT’ thinking that allows one to logically combine analysis goals and eases proofs. (2) Playing with the original store component in SOS configurations allows one to elegantly realize variants of abstract program interpretations, and to align different aspects, like e.g., the symbolic values of variables and path conditions. (3) Specializing languages by refining their BNF-like meta models has the power to lift certain verification tasks from the program to the programming language level. We will illustrate the advantages of the change of mindset imposed by these three DSLs, as well as the fact that these advantages come at low price due to available adequate generator technology.
- Published
- 2021
34. Research on the Evaluation Words Recognition in Scholarly Papers’ Peer Review Texts
- Author
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Liang Yang, Xinhang Zhao, Kun Ding, Kaiqiao Wang, and Yuan Lin
- Subjects
Computer science ,business.industry ,Sentiment analysis ,Academic evaluation ,computer.software_genre ,Public domain ,Viewpoints ,Order (business) ,Artificial intelligence ,Direct evaluation ,business ,Transfer of learning ,computer ,Word (computer architecture) ,Natural language processing - Abstract
Peer review is an important means of academic evaluation. The evaluation words in peer review texts reflect the important viewpoints of reviewers. In this paper, An evaluation words recognition method for peer review texts (TransPeerBCC) is proposed based on transfer learning method and BiLSTM-CNN-CRF framework. TransPeerBCC first classifies direct evaluation word and indirect evaluation word, and then uses BiLSTM-CNN-CRF framework to identify these words. At the same time, in order to improve the recognition accuracy, the model parameters of public domain data are transferred to the peer review texts’ using the transfer learning method. The effectiveness of the method is verified by the experimental dataset, and the identified evaluation words are quantitatively analyzed.
- Published
- 2021
35. Data Mining Methods for Analysis and Forecast of an Emerging Technology Trend: A Systematic Mapping Study from SCOPUS Papers
- Author
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Nguyen Thanh Viet, Tu Duong Quoc Hoang, and Alla G. Kravets
- Subjects
Trend analysis ,Emerging technologies ,Computer science ,Scopus ,Economic shortage ,Data mining ,Systematic mapping ,computer.software_genre ,Data type ,Competitive advantage ,computer ,Limited resources - Abstract
To stay competitive in an environment of rapidly changing science, it is important to monitor the development of existing technology and to discover new and promising technologies. Similarly, it is necessary for a firm to establish a technology development strategy through emerging technology forecast to gain a competitive edge while utilizing limited resources. Numerous methods of emerging technology trend analysis and forecast (TTAF) have been proposed; however, no study described data mining methods’ review of this research area in a systematic and structured procedure. Hence, this paper intends to give a review of TTAF data mining methods and shortages by surveying and constructing challenging problems, research and resolving approaches. Moreover, the study highlights adopted data mining methods and types of data sources. Specifically, 50 documents from SCOPUS over a ten-year timespan between 2010 and 2019 were systematically reviewed, and each performing step was followed properly in accordance with systematic mapping study.
- Published
- 2021
36. An Ensemble Learning System to Mitigate Malware Concept Drift Attacks (Short Paper)
- Author
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Meiqi Tian, Junnan Wang, Wang Zhi, and Chunfu Jia
- Subjects
021110 strategic, defence & security studies ,Concept drift ,Horizontal and vertical ,Computer science ,business.industry ,Core component ,Short paper ,0211 other engineering and technologies ,02 engineering and technology ,computer.software_genre ,Machine learning ,Ensemble learning ,Hybrid system ,0202 electrical engineering, electronic engineering, information engineering ,Malware ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,Gradient descent ,computer - Abstract
Machine learning is widely used in malware detection systems as a core component. However, machine learning algorithm is based on the assumption that the underlying malware concept is stable for training and testing. The assumption is vulnerable to well-crafted concept drift attacks, such as mimicry attacks, gradient descent attacks, poisoning attacks and so on. This paper proposes an ensemble learning system which combines vertical and horizontal correlation learning models. The significant diversity among vertical and horizontal correlation models increases the difficulty of concept drift attacks. And average p-value assessment is applied to fortify the system to be sensitive to hidden concept drift. The experiment results show that the hybrid system could actively recognize the concept drift among different Miuref variants.
- Published
- 2017
37. Short Paper: TLS Ecosystems in Networked Devices vs. Web Servers
- Author
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Mohammad Mannan and Nayanamana Samarasinghe
- Subjects
Web server ,computer.internet_protocol ,business.industry ,Computer science ,ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS ,Short paper ,020206 networking & telecommunications ,02 engineering and technology ,Computer security ,computer.software_genre ,IPv4 ,Networking hardware ,Preliminary analysis ,SCADA ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,Search interface ,Internet of Things ,business ,computer - Abstract
Recently, high-speed IPv4 scanners, such as ZMap, have enabled rapid and timely collection of TLS certificates and other security-sensitive parameters. Such large datasets led to the development of the Censys search interface, facilitating comprehensive analysis of TLS deployments in the wild. Several recent studies analyzed TLS certificates as deployed in web servers. Beyond public web servers, TLS is deployed in many other Internet-connected devices, at home and enterprise environments, and at network backbones. In this paper, we report the results of a preliminary analysis using Censys on TLS deployments in such devices (e.g., routers, modems, NAS, printers, SCADA, and IoT devices in general). We compare certificates and TLS connection parameters from a security perspective, as found in common devices with Alexa 1M sites. Our results highlight significant weaknesses, and may serve as a catalyst to improve TLS security for these devices.
- Published
- 2017
38. Justifying Security Measures — a Position Paper
- Author
-
Cormac Herley
- Subjects
Computer science ,020204 information systems ,Brake ,0202 electrical engineering, electronic engineering, information engineering ,Position paper ,020207 software engineering ,02 engineering and technology ,Computer security ,computer.software_genre ,computer - Abstract
There is a problem with the way we reason about problems in security. The justifications that we offer for many security measures reduce to unfalsifiable claims or circular statements. This position paper argues that reliance on less-than-solid arguments acts as a brake on progress in security.
- Published
- 2017
39. Towards Inverse Uncertainty Quantification in Software Development (Short Paper)
- Author
-
Carlo Bellettini, Patrizia Scandurra, Angelo Gargantini, and Matteo Camilli
- Subjects
Online model ,021103 operations research ,Computer science ,business.industry ,Calibration (statistics) ,Short paper ,0211 other engineering and technologies ,Software development ,Inverse ,020207 software engineering ,02 engineering and technology ,computer.software_genre ,Bayesian inference ,Formal specification ,0202 electrical engineering, electronic engineering, information engineering ,Data mining ,Uncertainty quantification ,business ,computer - Abstract
With the purpose of delivering more robust systems, this paper revisits the problem of Inverse Uncertainty Quantification that is related to the discrepancy between the measured data at runtime (while the system executes) and the formal specification (i.e., a mathematical model) of the system under consideration, and the value calibration of unknown parameters in the model. We foster an approach to quantify and mitigate system uncertainty during the development cycle by combining Bayesian reasoning and online Model-based testing.
- Published
- 2017
40. Home Location Protection in Mobile Social Networks: A Community Based Method (Short Paper)
- Author
-
Jin Li, Yong Xiang, Wanlei Zhou, Kun Wang, Shui Yu, Bo Liu, and Yu Wang
- Subjects
Community based ,Scheme (programming language) ,Focus (computing) ,Computer science ,Information sharing ,Short paper ,020206 networking & telecommunications ,02 engineering and technology ,Computer security ,computer.software_genre ,Location prediction ,Mobile social network ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,computer ,computer.programming_language - Abstract
Location privacy has drawn much attention among mobile social network users, as the geo-location information can be used by the adversaries to launch localization attacks which focus on finding people’s sensitive locations such as home and office place. In this paper, we propose a community based information sharing scheme to help the users to protect their home locations. First, we study the existing home location prediction algorithms and conclude that they are all mainly based on the spatial and temporal features of the check-in data. Then we design the community based information sharing scheme which aggregates the check-ins of all community members, thus change the overall spatial and temporal features. Finally, our simulation results validate that our proposed scheme greatly reduces the home location predication accuracy and therefore can protect the user’s privacy effectively.
- Published
- 2017
41. X-Platform Phishing: Abusing Trust for Targeted Attacks Short Paper
- Author
-
Toan Nguyen, Nasir Memon, and Hossein Siadati
- Subjects
060201 languages & linguistics ,business.industry ,Computer science ,InformationSystems_INFORMATIONSYSTEMSAPPLICATIONS ,Phishing attack ,Internet privacy ,Short paper ,06 humanities and the arts ,02 engineering and technology ,Service provider ,Computer security ,computer.software_genre ,Phishing ,ComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMS ,0602 languages and literature ,0202 electrical engineering, electronic engineering, information engineering ,ComputingMilieux_COMPUTERSANDSOCIETY ,020201 artificial intelligence & image processing ,business ,computer - Abstract
The goal of anti-phishing techniques is to reduce the delivery rate of phishemails, and anti-phishing training aims to decrease the phishing click-through rates. This paper presents the X-Platform Phishing Attack, a deceptive phishing attack with an alarmingly high delivery and click-through rates, and highlights a subclass of phishing attacks that existing anti-phishing methods do not seem to be able to address. The main characteristic of this attack is that an attacker is able to embed a malicious link within a legitimate message generated by service providers (e.g., Github, Google, Amazon) and sends it using their infrastructure to his targets. This technique results in the bypassing of existing anti-phishing filters because it utilizes reputable service providers to generate seemingly legitimate emails. This also makes it highly likely for the targets of the attack to click on the phishing link as the email id of a legitimate provider is being used. An X-Platform Phishing attack can use email-based messaging and notification mechanisms such as friend requests, membership invitations, status updates, and customizable gift cards to embed and deliver phishing links to their targets. We have tested the delivery and click-through rates of this attack experimentally, based on a customized phishing email tunneled through GitHub’s pull-request mechanism. We observed that 100% of X-Platform Phishing emails passed the anti-phishing systems and were delivered to the inbox of the target subjects. All of the participants clicked on phishing messages, and in some cases, forwarded the message to other project collaborators who also clicked on the phishing links.
- Published
- 2017
42. Paper Co-citation Analysis Using Semantic Similarity Measures
- Author
-
Mohamed Ben Aouicha, Mohamed Ali Hadj Taieb, and Houcemeddine Turki
- Subjects
Citation network ,Computer science ,business.industry ,Lexical similarity ,Judgement ,WordNet ,02 engineering and technology ,Bibliometrics ,computer.software_genre ,Co-citation ,Semantic similarity ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries) ,computer ,Natural language processing - Abstract
Co-citation analysis can be exploited as a bibliometric technique used for mining information on the relationships between scientific papers. Proposed methods rely, however, on co-citation counting techniques that slightly take the semantic aspect into consideration. The present study proposes a new technique based on the measure of Semantic Similarity (SS) between the titles of co-cited papers. Several computational measures rely on knowledge resources to quantify the semantic similarity, such as the WordNet «is a» taxonomy. Our proposal analyzes the SS between the titles of co-cited papers using word-based SS measures. Two major analytical experiments are performed: the first includes the benchmarks designed for testing word-based SS measures; the second exploits the dataset DBLP (DBLP: Digital Bibliography & Library Project.) citation network. As a result, we found the SS measures behave the same as human judgement for the lexical similarity and can be consequently used for the automatic assessment of similarity between co-cited papers. The analysis of highly repeated co-citations demonstrates that the different SS measures display almost similar behaviours, with slight differences due to the distribution of the provided SS values. Furthermore, we note a low percentage of similar referred papers into the co-citations.
- Published
- 2020
43. NLPExplorer: Exploring the Universe of NLP Papers
- Author
-
Naman Jain, P. Jayakrishna Sahit, Shruti Singh, Soham Pachpande, Mayank Singh, Monarch Parmar, and Pranjali Jain
- Subjects
Topic model ,050101 languages & linguistics ,System development ,Syntax (programming languages) ,Computer science ,business.industry ,05 social sciences ,Search engine indexing ,Contrast (statistics) ,02 engineering and technology ,computer.software_genre ,Popularity ,Automatic summarization ,Bottleneck ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,0501 psychology and cognitive sciences ,Artificial intelligence ,business ,computer ,Natural language processing - Abstract
Understanding the current research trends, problems, and their innovative solutions remains a bottleneck due to the ever-increasing volume of scientific articles. In this paper, we propose NLPExplorer, a completely automatic portal for indexing, searching, and visualizing Natural Language Processing (NLP) research volume. NLPExplorer presents interesting insights from papers, authors, venues, and topics. In contrast to previous topic modelling based approaches, we manually curate five course-grained non-exclusive topical categories namely Linguistic Target (Syntax, Discourse, etc.), Tasks (Tagging, Summarization, etc.), Approaches (unsupervised, supervised, etc.), Languages (English, Chinese, etc.) and Dataset types (news, clinical notes, etc.). Some of the novel features include a list of young popular authors, popular URLs and datasets, list of topically diverse papers and recent popular papers. Also, it provides temporal statistics such as yearwise popularity of topics, datasets, and seminal papers. To facilitate future research and system development, we make all the processed dataset accessible through API calls. The current system is available at http://nlpexplorer.org.
- Published
- 2020
44. Development of a Matlab Code for the Evaluation of Spray Distribution with Water-Sensitive Paper
- Author
-
Alberto Sassu, Gian Luca Marcialis, Davide Piccirilli, Luca Ghiani, and Filippo Gambella
- Subjects
Scanner ,Computer science ,business.industry ,Drop (liquid) ,Environmental pollution ,Image processing ,Matlab code ,Software ,Image analysis ,MATLAB ,Process engineering ,business ,computer ,computer.programming_language - Abstract
One of the biggest problems of agriculture is the reckless use of pesticides and their incorrect application with consequent waste of product and environmental pollution. The spray application characterization is a good preventive technique to limit the volume of a distributed product, to perform a more efficient application and to restrict the spray drift. Since there is no specific sampling technique useful for every context, it is necessary that every methodology is known in all its aspects before being employed. The colorimetry, fluorimetry and spectrometry methods are very accurate, but they are costly and time-consuming compared to a Water-Sensitive Paper (WSP) assessment performed by an image analysis software. This kind of software can detect and estimate many drops features using an image often obtained from a scanner. The objective of work was to develop a MATLAB code to evaluate the spray distribution over WSPs. After a pre-processing step in which the WSPs were isolated inside the image, the individual drops were identified using the difference between their color (blue) and the remaining dry part of the paper (yellow). Once the surface of every drop was estimated, it was possible to assess the number of the drops per cm2, the Normal Median Diameter (NMD) and the Normal Volume Diameter (VMD).
- Published
- 2020
45. High Fidelity and Objectivity in Balance Assessment—A Comparative Study of the 6-Degree Motion Tracking for Body Balance Assessment to the Conventional Paper Test
- Author
-
Antoinette Louw, Pei-Fen Chang, and Jeff Feng
- Subjects
Body balance ,Computer science ,business.industry ,Motion sensing ,Tracking system ,Body movement ,Kinematics ,Machine learning ,computer.software_genre ,High fidelity ,Match moving ,Artificial intelligence ,Objectivity (science) ,business ,computer - Abstract
Body balance is an essential capability for an individual to perform functional activities. There are various performance-based balance measures available to occupational therapists. However, conventional balance measures are limited due to subjectivity. There is a prominent need for a more objective and accurate assessment. NIMBLE, using motion sensing and tracking system was developed for a more objective and accurate measure of body movement with high-resolution recording. A pilot study was conducted in 20 participants for functional sitting balance measures by using both paper-based assessment and the NIMBLE. Results showed substantial discrepancies when the NIMBLE was able to detect balance deficits when the paper-based measures failed. The NIMBLE system can accurately capture the extraction of joint centers and segment orientation, providing the ability to calculate joint kinematics and spatiotemporal aspects of the movement. With this low cost and friendly interface, it has great potential to be widely used in healthcare practices.
- Published
- 2020
46. Mining Publication Papers via Text Mining: A Case Study
- Author
-
Sally Saad, Mostafa Aref, and Ahmed Ibrahim
- Subjects
0209 industrial biotechnology ,Information retrieval ,Computer science ,business.industry ,Process (engineering) ,Document classification ,02 engineering and technology ,computer.software_genre ,020901 industrial engineering & automation ,Text mining ,Named-entity recognition ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,business ,computer - Abstract
The amount of data that produced is increased day after day especially data as a text, so with this massive production it would be difficult to analyze or extract information to discover the patterns from the unstructured text. Text mining is used for availing the massive amount of knowledge that is in the text and deriving high quality information from the text automatically. This Process would save effort and time. Text mining considered as a subset of data mining where data mining is more generic. This paper proposes a methodology of mining a text for a case study related to publication papers. Some of text mining approaches will be introduced for mining the publication papers using machine learning (ML) and natural language processing (NLP) techniques. Describing each phase as following: First phase is keywords extraction using natural language processing techniques, second phase named entity recognition and last phase is document classification. The last two phases are using the ML techniques. Then a case study is built to simulate the system phases, showing what is the input and the output in each phase.
- Published
- 2020
47. Research of Paper Recommendation System Based on Citation Network Model
- Author
-
Sun Yu and Sun Jing
- Subjects
Citation network ,Computer science ,InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL ,Recommender system ,computer.software_genre ,Graph model ,law.invention ,PageRank ,law ,Graph (abstract data type) ,Word2vec ,Learning to rank ,Data mining ,Citation ,computer - Abstract
In view of the increasing number of existing papers, this paper is a study of paper recommendation system. The data set used in this paper is the DBLP citation network in AMiner. First of all, we build a three layers citation network graph model. In this model, we integrate the citation relationship, paper’s feature information, co-authorship relationship and research field information into this model. Secondly, we proposed the algorithm PAFRWR. This algorithm combines three layers citation network graph mode with RWR. And, the search vector is constructed by word2vec model. Finally, in this experiment, using Recall@N and NDCG@N as evaluation metric. Then the restart probability of PAFRWR is determined by experiments. And the most effective search vector is determined by comparison. The Recall@N and NDCG@N of PAFRWR are higher than PageRank, LDA and Link-PLSA-LDA through the experiment. So the recommendation model and algorithm in this paper are more accurate and effective.
- Published
- 2020
48. Developing an Online Music Teaching and Practicing Platform via Machine Learning: A Review Paper
- Author
-
Daniela Marghitu, Fatemeh Jamshidi, and Richard Chapman
- Subjects
Performance feedback ,Focus (computing) ,Class (computer programming) ,Computer science ,business.industry ,media_common.quotation_subject ,Music technology ,Machine learning ,computer.software_genre ,Music education ,Adaptability ,Learning styles ,Online music ,Artificial intelligence ,business ,computer ,media_common - Abstract
This article aims to lay a foundation for learning and practicing music online. Massive Open Online Courses (MOOCs) are growing as we are moving to online classes. Current music courses through MOOCs mostly focus on peer evaluation for assessing the students’ performance. However, this technique may not be practical when it is applied to larger class sizes. Therefore, in this research, the main goal is to reduce the instructor’s load and provide online real-time performance feedback. As a contribution to music education, we propose a new technological framework to automate music lessons for learning how to play any favorite songs via existing machine learning (ML) techniques for adaptability to various learning styles.
- Published
- 2021
49. Selected Papers from the 12th International Networking Conference
- Author
-
Bogdan Ghita and Stavros Shiaeles
- Subjects
Engineering ,business.industry ,computer.internet_protocol ,IPsec ,business ,Computer security ,computer.software_genre ,computer - Published
- 2021
50. A Distributed Ledger Based Cyber-Physical Architecture to Enforce Social Contracts: Paper Cup Recycling
- Author
-
Yingqi Gu, Tarun Goel, Francesco Pilla, and Robert Shorten
- Subjects
Social contract ,Computer science ,Cyber-physical system ,020206 networking & telecommunications ,02 engineering and technology ,Computer security ,computer.software_genre ,Iota ,020210 optoelectronics & photonics ,Sharing economy ,Distributed ledger ,0202 electrical engineering, electronic engineering, information engineering ,Architecture ,computer - Abstract
In this paper, we describe a distributed ledger re-cycling system to encourage responsible disposal of paper cups. A complete working prototype is described. Real measurements are presented to illustrate the potential suitability of the IOTA based distributed ledger for this application.
- Published
- 2019
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