Search

Abstract Image steganography is the art of concealing secret information within images to prevent detection. In deep‐learning‐based image steganography, a common practice is to fuse the secret image with the cover image to directly generate the stego image. However, not all features are equally critical for data hiding, and some insignificant ones may lead to the appearance of residual artifacts in the stego image. In this article, a novel network architecture for image steganography with hybrid attention mechanism based on generative adversarial network is introduced. This model consists of three subnetworks: a generator for generate stego images, an extractor for extracting the secret images, and a discriminator to simulate the detection process, which aids the generator in producing more realistic stego images. A specific hybrid attention mechanism (HAM) module is designed that effectively fuses information across channel and spatial domains, facilitating adaptive feature refinement within deep image representations. The experimental results suggest that the HAM module not only enhances the image quality during both the steganography and extraction processes but also improves the model's undetectability. Stego images are mixed with varying levels of noise in the training process, which can further improve robustness. Finally, it is verified that the model outperforms current steganography approaches on three datasets and exhibits good undetectability.

This paper presents our scalable and interoperable tool for GDPR (General Data Protection Regulation) consent management and automated compliance verification. The tool enables GDPR-compliant data sharing and is beneficial to the industries that process personally identifiable data. The tool has been designed following the GDPR data protection by design principles and has been successfully validated against real-world industrial use case scenarios in smart cities and insurance.

The Industrial Revolution 4.0 and digital transformation have brought significant changes in various aspects of life, including the business and administrative world. This revolution, driven by digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), big data, and cloud computing, enables automation in various industrial sectors and increases efficiency and productivity. This study aims to analyze the process of collecting, processing, and using personal data in using electronic signatures in Indonesia and knowing the compliance and legal consequences of personal data protection violations in using electronic signatures in Indonesia. This research approach is juridical normative. The research found that although the use of electronic signatures has increased rapidly during the COVID-19 pandemic, many challenges are still faced. Electronic signatures are often considered prestigious and challenging, although they have been widely used in signings by notaries. The author realizes that although much progress has been made, there is still room for improvement in adopting and understanding electronic signatures in Indonesia. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) devices have changed how billions of people in the world connect and interact with each other. But, as more people use IoT devices, many questions arise about how these devices handle private data and whether they properly ask for permission when using it. Due to information privacy regulations such as the EU’s General Data Protection Regulation (GDPR), which requires companies to seek permission from data subjects (DS) before using their data, it is crucial for IoT companies to obtain this permission correctly. However, this can be really challenging in the IoT world because people often find it difficult to interact with and manage multiple IoT devices under their control. Also, the rules about privacy are not always clear. As such, this paper proposes a new model to improve how consent is managed in the world of IoT. The model seeks to minimize “consent fatigue” (when people get tired of always being asked for permission) and give DS more control over how their data are shared. This includes having default permission settings, being able to compare similar devices, and, in the future, using AI to give personalized advice. The model allows users to easily review and change their IoT device permissions if previous conditions are not met. It also emphasizes the need for easily understandable privacy rules, clear communication with users, and robust tracking of consent for data usage. By using this model, companies that provide IoT services can do a better job of protecting user privacy and managing DS consent. In addition, companies can more easily comply with data protection laws and build stronger relationships with their customers.

Abstract Requirements engineering is a fundamental process in software development phases. At the same time, it is a difficult phase and exposed many ethical violations. The main purpose is proposing an ethical framework for software requirements engineering that addresses the identified concerns. These concerns include problems associated with a knowledge gap, requirements identification, quality‐related concerns, unwillingness to give requirements, and practicing forbidden activities. These concerns are grouped into a category as the proposed framework components. Each of the categories encompasses more than one problem domain. The proposed framework suggests resolving mechanisms as collections of clauses for each of those concerns. An expert evaluation technique is used to validate the proposed framework. The experts are purposefully selected from software industries and institutions. Questionnaires and focus group discussions were used as data‐gathering tools for the validation of the proposed framework. The validity (face validity, content validity, and construct validity) and the reliability of the proposed framework were checked. The evaluation results show that the proposed framework has an acceptable range of validity and reliability. The proposed framework can be used as a guideline for software engineers to minimise the occurrence of those identified concerns during the requirements engineering process.

Abstract The internet and related technologies have promoted the development of medical and health fields, especially remote diagnosis. As medical images may be stolen in the transmission process, the patient's personal information could be leaked. Aiming at the problem of privacy disclosure of colour medical images, a hybrid domain watermarking scheme based on improved differential evolution (DE) and the singular value block embedding (SVBE) is proposed in this study. Through this scheme, the image containing the patient's information is hidden in the patient's medical carrier image as a watermark. First, redistributed invariant lifting wavelet transform (RILWT), discrete wavelet transform (DWT), and singular value decomposition (SVD) are used to process the colour medical carrier image, and the high‐frequency information in the integer wavelet domain of the watermark is embedded into the processed carrier image using the proposed singular value block embedding method based on the improved differential evolution algorithm. At the same time, to increase the security of the watermark scheme, a digital signature based on the SHA‐384 hash function is designed for verification before watermark extraction. Compared with recent related research, the scheme has strong invisibility and robustness.

This paper introduces the issue of personal and non-personal data in autonomous vehicles. Its main objective is to provide a procedure for determining the processed and retained data, to explain the current legal regulation that must be met, and to propose appropriate recommendations for each data category. Current law (and the regulatory framework which it has produced) generally distinguishes between two basic types of data, i.e. non-personal data and personal data. The phenomenon that a combination of several pieces of non-personal data may, under certain circumstances2, result in processing of personal data, which is subject to significant regulation, is not limited solely to the field of autonomous mobility. This paper deals with data classification in autonomous vehicles, focusing on the challenging cases of non-personal data that can turn into personal data. The initial stage involves identifying the data to be processed, followed by the classification of the identified data. Based on this classification, relevant legal obligations and recommendations are described. The primary objective of this article is to provide guidance to data administrators (or, to use the terminology of data protection laws, data controllers) in autonomous mobility, enabling them to identify data and take appropriate measures to ensure compliance with legal regulations. The ultimate aim is to ensure that data controllers adhere to legal requirements, a goal that is critical for all data controllers. Beyond that, this article should be relevant also for other stakeholders in the autonomous mobility ecosystem, such as vehicle manufacturers and their suppliers, software application and service providers, and others. [ABSTRACT FROM AUTHOR]

End-to-end security is essential for relational database software. Most database management software provide data protection at the server side and in transit, but data are no longer protected once they arrive at the client software. In this paper, we present a methodology that, in addition to server-side security, protects data in transit and at rest on the application client side. Our solution enables flexible attribute-based and role-based access control, such that, for a given role or user with a given set of attributes, access can be granted to a relation, a column, or even to a particular data cell of the relation, depending on the data content. Our attribute-based access control model considers the client's attributes, such as versions of the operating system and the web browser, as well as type of the client's device. The solution supports decentralized data access and peer-to-peer data sharing in the form of an encrypted and digitally signed spreadsheet container that stores data retrieved by SQL queries from a database, along with data privileges. For extra security, keys for data encryption and decryption are generated on the fly. We show that our solution is successfully integrated with the PostgreSQL® database management system and enables more flexible access control for added security. [ABSTRACT FROM AUTHOR]

Smart contract, as the representative application of blockchain, has recently fueled extensive research interests from both academia and industry. However, with its wide applications, the weaknesses of smart contract have been gradually revealed. The major barrier to the widespread adoption of smart contract involves concerns about on-chain privacy which refers to the details of input/output privacy. To address privacy concerns, we propose in this paper, P-Chain, a privacy-aware framework for smart contracts of permissioned blockchain to protect sensitive data of users based on Secure Multi-party Computation (SMPC). Unlike existing work that suffer several key drawbacks, including introducing a third party who could get the details of the deal, and high overhead for on-chain and off-chain communication, as well as lacking a privacy protection for output data, we enhance the privacy protection for smart contracts system by adding a new secure multi-party computation layer in P-Chain. Through secure multi-party computing, sensitive inputs of smart contracts are divided into multiple sub-inputs and sent to computing participants for operation respectively, which ensures that each participant can only access part of the user's information. A stochastic strategy based on (t ; n) threshold secret sharing to select calculating parties is also been proposed, which makes it difficult for an attacker to aggregate t of n participants for launching a collusive attack. In addition, we propose the output privacy protection method that makes it possible to reach a consensus without the need to know the output. The extensive experimental evaluation and analysis demonstrate that our scheme enjoys the advantages of calculation correctness, input–output privacy as well as anti-collusion. [ABSTRACT FROM AUTHOR]

Abstract Artificial intelligence (AI) algorithms achieve outstanding results in many application domains such as computer vision and natural language processing. The performance of AI models is the outcome of complex and costly model architecture design and training processes. Hence, it is paramount for model owners to protect their AI models from piracy – model cloning, illegitimate distribution and use. IP protection mechanisms have been applied to AI models, and in particular to deep neural networks, to verify the model ownership. State‐of‐the‐art AI model ownership protection techniques have been surveyed. The pros and cons of AI model ownership protection have been reported. The majority of previous works are focused on watermarking, while more advanced methods such fingerprinting and attestation are promising but not yet explored in depth. This study has been concluded by discussing possible research directions in the area.

Copyright of Computer und Recht is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article presents the discussion on ownership of scientific data, databases, and processing software within the intellectual property law framework. Topics include substantial body of intellectual property and neighbouring laws developed for addressing the tension between the public interest in access to information and the private interests; and regarding the future of private ownership of software and data and the ability for controling access.

Data security has become indispensable, with a view to keep sensitive information confidential. One important method is through image encryption, upon which features in an image would no longer be visible. The original image with its features could only be restored upon decryption using a set of keys. There are prestigious works in the literature regarding image encryption. However, there is a lack of easy-to-use, GUI-based, user-customizable computer programs for image encryption. In the present work, we developed a GUI-based image encryption and decryption program with server file transfer support, namely, SecureVision. A custom-made random number generator using the equation of an ellipse was developed to randomly shuffle the pixel positions. SecureVision was found to be robust, user-friendly and fast in both encryption and decryption. The program was highly sensitive to the supplied keys, which prevented brute-force attacks. SecureVision provided full user control, where users could modify the program modules to match their desired applications, which was particularly desirable for pedagogical purposes in that interested parties had the freedom to explore the concept of image encryption and decryption. SecureVision is distributed under a GPLv3 license, which would allow everyone to use, modify and distribute the program without any restriction. [ABSTRACT FROM AUTHOR]

The hiding of internal invariants creates a mismatch between procedure specifications in an interface and proof obligations on the implementations of those procedures. The mismatch is sound if the invariants depend only on encapsulated state, but encapsulation is problematic in contemporary software due to the many uses of shared mutable objects. The mismatch is formalized here in a proof rule that achieves flexibility via explicit restrictions on client effects, expressed using ghost state and ordinary first order assertions. The restrictions amount to a stateful frame condition that must be satisfied by any client; this dynamic encapsulation boundary complements conventional scope-based encapsulation. The technical development is based on a companion article, Part I, that presents Region Logic--a programming logic with stateful frame conditions for commands. [ABSTRACT FROM AUTHOR]

The article talks about security of data and secrecy in the GeschGehG contract and contractual obligations for the technical protection of non-personal data. It mentions that regardless of the protection of data now de lege ferenda, they naturally play in contractual practice plays a role; and their should be agreement that they like software due to a lack of material quality.

This essay is based on a presentation made on January' 24,2020 at the invitation of the Texas Journal of International Law and the Strauss Center for National Security at the University of Texas. That presentation focused on the two questions mentioned in the title of this essay - Do Blockchain Technologies Make Us Safer? And Do Cryptocurrencies Necessarily Make Us Less Safe? The essay presents answers to the two questions: "yes" and "probably yes." This essay begins with some level-setting on different types of blockchain technologies and of cryptocurrencies, and gives some background materials on global and national responses to certain cryptocurrencies, such as El Petro sponsored by Venezuela's PDVSA and Facebook's Libra. [ABSTRACT FROM AUTHOR]

A quarter of a century ago, under the new TRIPS Agreement, copyright protection for software became the international norm. Whether copyright is in fact an appropriate form of protection for software was and still is debated; the issues raised in the ongoing high-profile Google v. Oracle dispute, now before the U.S. Supreme Court, are among the continuing and significant problems that the extension of copyright to software have generated. This article reviews the coexistence between software and copyright law; it focuses on their mutual effects and the adjustments in each that resulted from their coexistence. The article notes the technological changes that coincided with or followed the adoption of the international norm and that significantly affected the coexistence between software and copyright law. [ABSTRACT FROM AUTHOR]

The article examines whether the concept of privacy by design responsible for the definition of data protection law can support software requirements. It notes that instructions in the company recommend a work instruction to the purchase or an addition to any existing procurement guidelines. Topics discussed include informational risks, privacy by design, and catalog for data security towards an individual risk assessment.

Copyright of Crónica Tributaria is the property of Instituto de Estudios Fiscales, Ministerio de Hacienda y Funcion Publica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract The advent of cloud computing has brought the computing power of corporate data processing and storage centers to lightweight devices. Software-as-a-service cloud subscribers enjoy the convenience of personal devices along with the power and capability of a service. Using logical as opposed to physical partitions across cloud servers, providers supply flexible and scalable resources. Furthermore, the possibility for multitenant accounts promises considerable freedom when establishing access controls for cloud content. For forensic analysts conducting data acquisition, cloud resources present unique challenges. Inherent properties such as dynamic content, multiple sources, and nonlocal content make it difficult for a standard to be developed for evidence gathering in satisfaction of United States federal evidentiary standards in criminal litigation. Development of such standards, while essential for reliable production of evidence at trial, may not be entirely possible given the guarantees to privacy granted by the Fourth Amendment and the Electronic Communications Privacy Act. Privacy of information on a cloud is complicated because the data is stored on resources owned by a third-party provider, accessible by users of an account group, and monitored according to a service level agreement. This research constructs a balancing test for competing considerations of a forensic investigator acquiring information from a cloud. [ABSTRACT FROM AUTHOR]

Advanced persistent threats (APTs) are a major threat to cyber-security, causing significant financial and privacy losses each year. In this paper, cumulative prospect theory (CPT) is applied to study the interactions between a cyber system and an APT attacker when each of them makes subjective decisions to choose their scan interval and attack interval, respectively. Both the probability distortion effect and the framing effect are applied to model the deviation of subjective decisions of end-users from the objective decisions governed by expected utility theory, under uncertain attack durations in a pure-strategy game and scan interval in a mixed-strategy game. The CPT-based APT detection game incorporates both the probability weighting distortion and the framing effect of the subjective attacker and security agent of the cyber system, rather than discrete decision weights, as in earlier prospect theoretic study of APT detection. The Nash equilibria of the APT detection game are derived, showing that a subjective attacker becomes risk-seeking if the frame of reference for evaluating the utility is large, and becomes risk-averse if the frame of reference for evaluating the utility is small. A policy hill-climbing (PHC) based detection scheme is proposed to increase the policy uncertainty to fool the attacker in the dynamic game, and a “hotbooting” technique that exploits experiences in similar scenarios to initialize the quality values is developed to accelerate the learning speed of PHC-based detection. A practical example of a mobile network is presented to evaluate the performance of the proposed detection strategy. Simulation results show that the proposed strategy can improve detection performance with a higher data protection level and utilities of the cloud in the presence of an attacker compared with a standard Q-learning strategy. [ABSTRACT FROM AUTHOR]

The partial multi-view clustering is an emerging hot research area. For example, in web page clustering, the web page content or its linkage information may suffer from the missing of some data. Traditional multi-view clustering methods deal with this kind of problem by completing and clustering separately and thus degrade the clustering performance. In this paper, we propose a new method, named as partial multi-view spectral clustering (PVSC), to cluster partial multi-view data directly. We propose a unified objective function to optimize clustering results of both individual part on each view and shared part among different views, without requiring the full representations of all views. Based on the assumption that an example in multiple views would be assigned to the same cluster with high probability, these shared parts whose examples appear in multiple views have coherent clustering relationships. Meanwhile, the nonnegative and orthogonal constraints are also added to enhance the robustness and efficiency of our methods. Besides, we provide an iterative algorithm for solving our formulated objective. The experimental results on partial multi-view datasets validate the effectiveness of our proposed method [ABSTRACT FROM AUTHOR]

The widespread availability of hand-held devices like tablets, phablets and smart phones, along with their new handwriting digitizing and their increased computing powers, enable these to process the graphomotor dimension and the lognormal trends of human handwriting. By exploiting such capacity, it becomes possible to extend these mobile devices into Personal Digital Bodyguards ( PDB s). PDBs will be able to supplement people's sensitive data protection with signature verification, equipment use security with writer authentication and handwritten CAPTCHAs processing (e-security ), and to enhance human-machine interaction performances through words spotting and handwriting recognition (e-recognition). For young children, these tools will turn into interactive toys helping them to learn and master their fine motor control and become better writers. For advanced students they will enable sophisticated systems for (e-learning) and (e-testing) . Moreover, PDBs will also be able to provide the user with fine motor control monitoring, which can detect stress, aging and health problems (e-health) . This paper presents a prospective survey of various projects dealing with these five e-fields of investigation, focussing on state of the art results and providing directions in research and development, under the theoretical umbrella of the Kinematic Theory of human movements and its Lognormality Principle. From a practical point of view, the concept of lognormality provides a fundamental common thread, an integrative psychophysical standpoint to track the graphomotor problems of signature verification, writer identification, handwriting generation, recognition and learning. [ABSTRACT FROM AUTHOR]

Control flow confusion is a software protection technique. There is uncertainty of obfuscation strength and extra cost by using the traditional garbage code control flow obfuscation algorithm. To solve this problem, a control flow obfuscation algorithm based on nested complexity is proposed. The cost introduced by obfuscation is calculated quantitatively, and the complexity of control flow is measured by nested complexity. The knapsack decision table is constructed based on the idea of packet knapsack. Considering the obfuscation strength and the cost, the garbage code insertion point is selected, and the obfuscation strength is increased as much as possible within the cost threshold. The results show that the obfuscation strength of the algorithm in this paper is higher than that of the control flow obfuscation algorithm using the traditional random insertion strategy. [ABSTRACT FROM AUTHOR]

Developments in information and communication technology have changed the way healthcare processes are experienced by both patients and healthcare professionals: more and more services are now available through computers and mobile devices. Smartphones are becoming useful tools for managing one's health, and today, there are many available apps meant to increase self-management, empowerment and quality of life. However, there are concerns about the implications of using mHealth and apps: data protection issues, concerns about sharing information online, and the patients' capacity for discerning effective and valid apps from useless ones. The new General Data Protection Regulation has been introduced in order to give uniformity to data protection regulations among European countries but shared guidelines for mHealth are yet to develop. A unified perspective across Europe would increase the control over mHealth exploitation, making it possible to think of mHealth as effective and standard tools for future medical practice. [ABSTRACT FROM AUTHOR]

In the paper are studied methods for protection of interactive systems and digital archives against unauthorized distribution of digital content. We make an overview of steganographic methods and image protection schemes. An improved watermark error correction scheme is presented. The studies contribute to the overall development of the North+region, provide future generations with widespread public access to digital materials. We achieve a long-term storage, secure data protection and interactive web presence. [ABSTRACT FROM AUTHOR]

Nowadays the protection of life, health and property of individuals is in the centre of public interest. There is not a distinction between the provision of such protection by private or public sector. The private security services play an important role in protection of persons and property. The subjects of protection are not only people and property, but also sensitive information which is relevant for the state interest or business entities. Based on research, the private security services do not make a selection of employees systematically. One of the reasons is the absence of an analysis of candidates' personal competencies which should take into account the requirements of the protected subject. The aim of the article is therefore a software solution for modelling the personal competencies of applicants for the job in private security services. [ABSTRACT FROM AUTHOR]

The security of encrypted data depends not only on the theoretical properties of cryptographic primitives but also on the robustness of their implementations in software and hardware. Threshold cryptography introduces a computational paradigm that enables higher assurance for such implementations. [ABSTRACT FROM AUTHOR]

Secure Simple Pairing, a Bluetooth-pairing protocol, suffers from passive off-line and active online-guessing attack. These assaults are a direct result of the shortcomings in Bluetooth specification. Bluetooth technology uses the principles of device inquiry and inquiry scan. Scanning devices listen in on known frequencies for devices that are actively inquiring. If two Bluetooth devices know absolutely nothing about each other, one must run an inquiry to try to discover the other. One device sends out the inquiry request, and any device listening for such a request will respond with its address, and possibly its name, Input/Output capability and other information. Before connection, each device knows the address, their name, their capability, Quality-of-Service, etc. During pairing, Man-In-The-Middle attacker may capture all the information of connecting devices and impersonate them. This paper introduces the security augmentation in Bluetooth pairing by postponing exchange of Input-Output capability and other information like Quality-of-Service until it is essentially required and by casing the link key with a pair of Elliptic Curve Diffie-Hellman keys. Consequently, this leads to increased pairing time. Yet, we overlooked the increased pairing time, as the proposed Bluetooth-pairing protocol improves security by strengthening the link key. [ABSTRACT FROM PUBLISHER]

The critical sections with the lock protection greatly limit the concurrency of multi-threaded applications. The prior lock elision based technique is presented to exploit the parallelism between critical sections accessing the disjoint shared data, but still fails to notice and expose a high degree of concurrency between critical sections that contend for the same shared data, i.e., conflicting critical sections (CCS). This paper focuses on exploiting the CCS parallelism. The key insight of this work is that, for each running CCS, a large proportion ( $>$ 73.4%) of parallelism between CCSs can be exploited as fully as possible by simply allowing the parallel execution of their first conflict-free code fragment at runtime. We therefore present BSOptimizer, a new microarchitecture, to perform the partial reversion integrated with a series of sophisticated hardware and software strategies for the CCS parallelization. We complement the off-the-shelf cache coherency protocol to perceive the conflict location of CCS, present a predictive checkpoint mechanism to register and predict the concerned conflict point in a lightweight and accurate fashion, and redefine the traditional mutual exclusive semantics with a binary relationship. With these collaborative techniques, each CCS can be scheduled in parallel. Our experimental results on a wide variety of real programs and PARSEC benchmarks show that, compared to the native execution and two state-of-the-art lock elision techniques (including SLE and SLR), BSOptmizer can dramatically improves the performance of programs with a slight ($<$ 0.8%) energy consumption and ($<$ 3.9%) extra runtime overhead. Our evaluation on a micro-benchmark with software based optimization also verifies that BSOptimizer can accurately exploit the CCS parallelism as promised. [ABSTRACT FROM AUTHOR]