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Day by day, we advance deeper into the universe of technology, of devices and applications that provide services throughout the day for a wide variety of use scenarios. We discuss solution development and education for developers addressing privacy issues in today's surveillance society. A significant proportion of widely used applications require locating the user. Regarding privacy, there is no effective guarantee that the services will not sell private information to 3rd parties. Users often agree to Terms and Conditions that in practice allow companies to sell data to 3rd parties. There are numerous instances of data breaches, that overcome legal protection barriers. The need to maintain location privacy is only stronger in today's environment, when context-awareness or locationawareness services are everywhere. Current systems are able to track anyone in real time, with incredible accuracy. We present a solution that provides a way of hiding the exact location, by taking into consideration the user's needs and the most popular areas in a city. The obfuscation range may differ from tens of meters to kilometres. For instance, if people are checking the weather, the location may be set anywhere inside of a city, but if they are looking for restaurants, then it is important to show a nearby obfuscated location. Basic geo indistinguishability solutions are based on Laplace functions. The main drawback is that they are exposed to threats, such as running the application multiple times and getting the distribution formula and the real location. Also, generating fake coordinates without extra checking may lead to wrong positioning, such as over lakes. In order to make the solution reliable, we took into consideration the popular places where someone may be, while avoiding issues related to triangulation. The article evaluates the state-of-the-art solutions and proposes a new algorithm, which has been tested on a dataset from Beijing. We also discuss how this solution can be used as a case study in teaching privacy for undergraduate students, highlighting critical issues and possible ways of developing alternative solutions that address ethical and technological issues at the same time. [ABSTRACT FROM AUTHOR]

In an ecosystem where education is done through software interaction, the security of those systems is one key aspect which should not trouble the educators nor the children and students that interact with them. The article addresses a problem that is growing every day, new malware samples, which steal data [10], encrypt data and ask for a ransom [11], get remote access to a personal computer [12], or use computer resources to mine cryptocurrencies [13]. There are presented malware analysis reports that meticulously describe malicious software's behaviour and help security professionals to mitigate the risk. The need for security brings to light new methods to protect people's devices, like using machine learning or artificial intelligence. Random forest and neural network algorithms are implemented and the results are very encouraging, the accuracy in both cases is over 95%. In the last few years, because of the increasing computer resources and the more frequent usage of cloud services, these machine learning algorithms perform better and have caught the attention of many researchers in this area. The objectives of the project include the study of malicious software in order to find mitigation strategies, important characteristics of malware families that are used to generalize the problem of ransomware and malware detection. Also, it's presented the usage of open source sandbox to capture malware's behaviour and to use the results as the input for machine learning algorithms, and the study of different algorithms which can be used in classification problems. The current work can be a strong baseline to develop more advanced and useful algorithms, using millions of samples as the input dataset. [ABSTRACT FROM AUTHOR]

Technology advances to make life easier for people. We tend to surround us with devices as small as possible and with the highest computing power. The need for data access from everywhere is an important detail. As a consequence, digital documents have been gaining ground on printed ones and for some sectors, the latter were even replaced. The need and the obligation to preserve the written cultural heritage, represented by books and valuable documents, some of them rare and even unique, forced us to imagine a system that protects the patrimony but makes it also accessible. In order to make books easily available to the public and at the lowest possible risk for the protection of the originals, we came to the idea of designing and creating an efficient digitization system of these records. The current article presents the proposed architecture of a Document Image Analysis System that will process the information with individual modules for each type of operation. The main scope for such tool is to recognize information from the documents and extract them for electronic use. The flow of operations are indicated by user, some steps can be eliminated depending on the user’s desire and needs. In order to design an efficient Document Image Analysis System, we need a 3 axis approach: Education - involving students that can receive tasks for replacing modules and validating their homework, Research - performing various tests and Performance - testing the module interconnection and enabling the system to be extremely configurable. No matter what axis is considered, the main scope is the flexibility of the system - performed by individual modules as physical binaries or collection of binaries that are linked via scripts. Each module is designed to accomplish a certain major task by executing several sub-tasks whose results, in most cases, are subject to an intelligent voting process that produces the module’s output data. [ABSTRACT FROM AUTHOR]

We are living in an era where computers govern the educational process. The market is flooded with puzzles, games, quizzes or other kinds of applications destined to help teachers explain different concepts and to enable students to practice their skills and test the knowledge. For all these systems, be them computers, server or embedded devices, the internet connection is the essential aspect. As a result, we have children and students working with devices that are exposed to the highest degree of security issues and threats. Attacks are continuously evolving, becoming more flexible, adaptable and hard to detect, and leaving children and students vulnerable to malicious software that can either collect sensitive information about them or expose them to inappropriate content. Because of this, it is only natural that security solutions became of significant importance for the tech educational industry. Computers, servers and embedded devices are exposed to the highest degree of security issues and threats since the internet became an essential need. Attacks are continuously evolving, becoming more flexible, adaptable and hard to detect. This made only natural the shift towards adaptive security oriented solutions. One of the security those solutions is represented by anomaly based intrusion detection techniques. Anomaly based intrusion detection systems build a baseline of normal behavior. For a Linux based operating system, which represents a great percent of the platforms used in education, this is accomplished by monitoring a given process or sets of processes. Any significant deviation from the baseline model is flagged as malicious activity. This paper proposes a framework for intrusion detection using system call traces captured from services running on a container. The work done is based on The Australian Defence Force Academy Linux Dataset, better known as ADFA-LD. The analysis is done taking into consideration the temporal allocation of the system calls. The classification module is based on supervised machine learning techniques. To test the accuracy of the framework, a case study involving a database application running under a Linux container is analyzed. The results together with the proposed framework implementation are described in details. [ABSTRACT FROM AUTHOR]

In this paper we examine the evolving roles of digital technology in shaping the professional identity and therapeutic encounters of homeopathic practitioners. Homeopathy is a form of alternative medicine that relies almost exclusively in making a diagnostic on patients' verbal description of their symptoms. In contrast to the biomedical diagnosis, the homeopathic diagnosis does not place the patient in a disease category, but in a remedy category. The software that aids homeopathic professionals in their practice is based on a digitalization of books that organized the homeopathic knowledge of remedies and symptoms (repertories and Materia Medica). Organized as an inventory of descriptions of remedies and symptoms, the software operates algorithmically in helping the homeopath to match patients' symptoms to possible remedies and select the most adequate remedy. During the consultation, the homeopath makes a patient file by writing a selection of words extracted from patients' talk that express symptoms in great detail - including feelings, signs of suffering and various lifestyle preferences. In this process the homeopath and the software co-create the patient's "person" as a collection of more-or-less idiosyncratic symptoms, in their attempt to match the patient's symptomatology with the description of one single remedy. Drawing on interviews with patients and homeopaths, observations of consultations and homeopathic seminars, we argue that the use of digital technology is practiced as boundary work. Firstly, digital technology becomes a boundary marker between the patient and the homeopath. Secondly, digital technology helps homeopaths to legitimize their practice as a rigorous one, being one of the strategies used to gain acceptance in the health-care ecosystem. Last but not least, by presenting the software as only a time-saving device, a neutral aide for making "intelligent suggestions" that can be confirmed but also rejected by the homeopath's judgment, homeopaths create a distinct professional identity oriented around a central principle of their practice: "Treat the patient as a whole person". [ABSTRACT FROM AUTHOR]

World wide data infrastructure has increased in dimension and complexity due to consolidation, centralization and virtualization trends during the last 10 years. Being able to discriminate quickly between large-scale non-directional attacks and targeted APT (advanced persistent threats) or between script kiddies and experienced hackers is key for protecting critical IT infrastructures. While the first case can be easily handled by existing solutions, the latter raises significant challenges. Implementing honeytokens and honeypots is an extremely efficient intrusion detection system based on setting traps for hackers by deliberately placing enticing resources within existing environments. Previous research has used honeypots to understand hacking TTPs (tactics, techniques and procedures) and to generate more realistic honeytokens. In this paper we build on existing results to quickly categorize attacks, map the attacker persona and focus on targeted attacks. We influence the execution flow by trapping the attackers into a maze with three purposes. The first aim consists in distracting them from the real data and understanding their motivation; this is done by placing low hanging fruits in his path. The second aim refers to getting to know the attackers, gathering forensic evidence and using this information to adapt incident response. The last goal is the most difficult: to completely remove the threat by revealing the attackers' identity, getting in contact, handing them over to law enforcement agencies, or deterring them. We deploy a series of interconnected honeytokens, working together as a whole. Each honeytoken will have an exploitation difficulty in order to map out the attacker's skills and will lead to the next honeytoken, thus forming a real-world hacking scenario. We are also analysing the possibility of deploying dynamic traps based on how the attack develops in real time. From a technical perspective we propose a zero-touch approach for existing environments, by deploying the honeytokens as a service in the cloud, with minimum overhead for the customer. [ABSTRACT FROM AUTHOR]

Scholarly social networks such as Academia.edu and ResearchGate.net introduce a novel approach in literature search, bringing authors to the fore as nodes in exploration paths. While traditional literature search occurs in a text-based environment, academic social sites bring forward the authors. They make use of actionable researcher personas to facilitate discovery and encourage user engagement. Still, the topic of search and exploration remains underrepresented in the discussions on academic social networks. Current interface design limits the potential of researcher personas to facilitate discovery, and the potential of literature discovery to enrich researcher personas. We study through observation the profiles of 207 Game Studies researchers on Academia.edu and ResearchGate, documenting a significant space for improving engagement beyond current median levels. By introducing the concept of actionable researcher personas and discussing actual limits and opportunities in its implementation, we contribute to a better understanding of the potential of academic social networks to change literature discovery and create a novel experience of search, centered on authors' mediated presence. When exploring research publications on the two platforms, authors are no longer attributes of texts: they become contexts for making sense of publications and for charting new routes in the research landscape. Such an author-centric experience of literature discovery can emerge and consolidate in time, as users incorporate novel ways of relating to authors and using their personas as tools for navigation. Higher engagement can lead to richer and more relevant home feeds that, in turn, can create new opportunities to practice an emerging skill of literature discovery through actionable researcher personas. [ABSTRACT FROM AUTHOR]

In this paper we introduce a quasi-experimental methodology to assess the benefits of an entrepreneurial learning program, based on LinkedIn profile data. We compare the career paths of two cohorts of participants in the mentoring sessions of the Innovation Labs pre-accelerator, compared with a control group formed by persons of similar age and entrepreneurial interest who did not benefit from the added value of the mentorship program. We appraise the advantages and limitations of studying online traces of professional identity in LinkedIn public profiles. We discuss how a content analysis of LinkedIn public profiles illuminates the impact of Innovation Labs as a significant learning experience. In this sense, we present our proposed quasi-experimental method in terms of: (1) objectivity: digitally mediated factuality as a product of design; (2) narrativity: modes of subjectification through self-making practices; (3) sociality: social relations, systems of acknowledgment, and reputation building processes; (4) performativity: the role of digital traces and online inscriptions in reality construction. In order to assess the learning benefits of Innovation Labs, we take into consideration various forms of capital which are circulated on the participants' profiles, and we reflect on processes through which social capital is converted into symbolic resources, intellectual assets and career horizons. We also explore how participation in the program is framed and described, on LinkedIn public profiles, as a significant experience in one's professional development. Therefore, our study is significant not only in refining impact evaluation theory and research, but also in understanding how technology shapes our knowledge of the professional world, with practical implications on developing effective strategies of professional self-presentation and reputation consolidation. [ABSTRACT FROM AUTHOR]

In this paper, we consider the potential of gamified platforms to teach young people entrepreneurial values. We start from exploring a specific learning environment, #AntreprenorulLunii (Eng. #theentrepreneurofthemonth), designed to increase visibility of self-driven careers, while promoting the diversity of trajectories, motivations and models in successful Romanian businesses. The environment is supported by a digital platform used to assemble stories of leading entrepreneurs whose experience and products are made to account as subject of discussion. The gamified component of the platform consists in a competition organized to award users who propose valuable comments on the presented products. Therefore, #AntreprenorulLunii also functions as a campaign developed both to enrich public discourse around the values of business creation and to increase awareness on the role of IT instruments in developing successful entrepreneurial projects. The digital platform unfolds a jointly constructed culture in which different actors collaboratively establish entrepreneurship as the referential system of ongoing interactions. The platform facilitates actions in which the meaning of entrepreneurship is socially defined and negotiated through locally orchestrated modes of engagement. In this sense, #AntreprenorulLunii becomes a medium to invite questioning on how entrepreneurship might be known, approached and learned, and on what type of resources might be integrated in the process. We consider that analytically employing the concept of "voices", understood as an accountable embodiment of "perspective, conceptual horizon, intention and worldview" (Engeström, 1995, p. 199) represents an effective practice in the design and implementation of powerful learning environments. By exploring different interactional patterns and discursive episodes in the production, use and evaluation of #AntreprenorulLunii digital environment, we propose a framework to analyse multivoicedness (Wertsch, 1991) in gamified learning platforms. We claim that voices are embedded in the design and rhetoric of the digital medium, becoming a function of framing discourse, positioning actors, mediating actions, and building technological infrastructure. Accordingly, we develop a typology that differentiates between (1) discursively-framed voices (voices that are intentionally introduced to stage subjective positions of various actors), (2) relationally-emergent voices (voices that arise in sequences of interactions and relations between various actors), (3) action-based voices (voices that develop in processes of acting upon the platform and engaging with it), (4) objectifiedconstructed voices (voices of objects, digital artefacts and technological infrastructure integrated within the platform), and (5) performative meta-voices (voices resulting in how the platform acts in the world as an independent reality). We illustrate how these types of voices operate in achieving the meaning of entrepreneurship within #AntreprenorulLunii media platform, thus theorizing on how learning process is being constituted by a multiplicity of dynamic and interacting cultural, institutional and socio-economic settings. [ABSTRACT FROM AUTHOR]

We examine patterns of evaluation on the open peer review forum of the AltCHI panel of the ACM SIGCHI Conference on Human Factors in Computing Systems, 2012-2013. By analyzing a dataset including all available reviews posted on the AltCHI online platforms, we find that author reviewers are more critical than external commentators, and later submission reviews are more favorable than earlier ones. We find substantial inter-reviewer agreement, partly explainable through persuasive convergence and anchoring effects. Final article acceptance through juried selection is strongly correlated with the average grade in open review, while the number of article reviews is less consequential for selection. The communication design of AltCHI open review balances several conflicting participation incentives, in order to support juried selection for atypical and potentially controversial papers. [ABSTRACT FROM AUTHOR]

We examine the gamification debate of recent years and we propose an alternative, heuristic definition for gamification in learning situations. After considering several critiques of the gamification concept, we privilege in our definition 'interaction' over 'motivation', 'simple gameplay' over 'game mechanics', and we highlight the diverse and changing behaviors of user/players. We re-define gamification in learning contexts as 'simple gameplay to support productive interaction for expected types of learners and instructors'. We argue that this definition offers a lowest common denominator to inform gamification in education. [ABSTRACT FROM AUTHOR]