6,877 research outputs found
iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
To meet the demand of the world's largest population, smart manufacturing has accelerated the adoption of smart factoriesâwhere autonomous and cooperative instruments across all levels of production and logistics networks are integrated through a Cyber-Physical Production System (CPPS). However, these networks are comprised of various heterogeneous devices with varying computational power and memory capabilities. As a result, many secure communication protocols â that demand considerably high computational power and memory â can not be verbatim employed on these networks, and thereby, leaving them more vulnerable to security threats and attacks over conventional networks. These threats can largely be tackled by employing a Trust Management Model (TMM) by exploiting the behavioural patterns of nodes to identify their trust class. In this context, ML-based models are best suited due to their ability to capture hidden patterns in data, learning and improving the pattern detection accuracy over time to counteract and tackle threats of a dynamic nature, which is absent in most of the conventional models. However, among the existing ML-based solutions in detecting attack patterns, many of them are computationally expensive, require a long training time, and a considerably large amount of training dataâwhich are seldom available. An aid to this is the association rule learning (ARL) paradigm, whose models are computationally inexpensive and do not require a long training time. Therefore, this paper proposes an ARL-based intelligent Behavioural Trust Model (iBUST) for securing the CPPS. For this intelligent TMM, a variant of Frequency Pattern Growth (FP-Growth), called enhanced FP-Growth (EFP-Growth) algorithm is developed by altering the internal data structures for faster execution and by developing a modified exponential decay function (MEDF) to automatically calculate minimum supports for adapting trust evolution characteristics. In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. Afterwards, the trust class of an object is identified employing the NaĂŻve Bayes classifier. This proposed model is evaluated on a trust evolution-supported experimental environment along with other compared models taking a benchmark dataset into consideration, where it outperforms its counterparts
Development of an Event Management Web Application For Students: A Focus on Back-end
Managing schedules can be challenging for students, with different calendars on various platforms leading to confusion and missed events. To address this problem, this thesis presents the development of an event management website designed to help students stay organized and motivated. With a focus on the application's back-end, this thesis explores the technology stack used to build the website and the implementation details of each chosen technology. By providing a detailed case study of the website development process, this thesis serves as a helpful resource for future developers looking to build their web applications
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Understanding the Impact of Covid-19 on Ethnic Minority Students: a Case Study of Open University Level 1 Computing Modules
As reported in [1] âOf the disparities that exist within higher education, the gap between the likelihood of White students and students from Black, Asian or minority ethnic backgrounds getting a first- or upper-second-class degree is among the starkestâ. In the Open University (OU) for example, a recent research [2] found students from ethnic minorities to be at least 20% less likely to achieve excellent grades and to spend 4-12% more of study time to achieve the same performance as white students. Moreover, with the advent of COVID-19, a growing body of research suggested that students from these groups of the population, suffer disproportionally from the impacts of the pandemic [3], which inevitably impacts on their study experiences. However, recent research in the OU found that some COVID-19 arrangements such as the change of examination mode and change in work-life patterns have impacted students from ethnic minority backgrounds differently. In this paper we present findings from a project aiming to understand the impact of COVID-19 on ethnic minority studentsâ study experiences and performance. By means of a combination of qualitative and quantitative data analytics we first analysed the study performance and the patterns of progression, then by conducting focus groups with the teaching staff we assessed the impact of COVID-19 on the lived experiences of the students.
[1] Black, Asian and Minority Ethnic Student Attainment at UK Universities (2022). Available at: https://www.universitiesuk.ac.uk.
[2] Nguyen Q., Rienties B. Richardson J.T.E. (2020) Learning analytics to uncover inequality in behavioural engagement and academic attainment in a distance learning setting, Assessment & Evaluation in Higher Education, 45:4, 594-606.
[3] Arday, J. and Jones, C. (2022) âSame storm, different boats: The impact of covid-19 on black students and academic staff in UK and US higher education,â Higher Education. Available at:
https://doi.org/10.1007/s10734-022-00939-0
Deteção de intrusÔes de rede baseada em anomalias
Dissertação de mestrado integrado em EletrĂłnica Industrial e ComputadoresAo longo dos Ășltimos anos, a segurança de hardware e software tornou-se uma grande preocupação. Ă medida
que a complexidade dos sistemas aumenta, as suas vulnerabilidades a sofisticadas tĂ©cnicas de ataque tĂȘm
proporcionalmente escalado. Frequentemente o problema reside na heterogenidade de dispositivos conectados ao
veĂculo, tornando difĂcil a convergĂȘncia da monitorização de todos os protocolos num Ășnico produto de segurança.
Por esse motivo, o mercado requer ferramentas mais avançadas para a monitorizar ambientes crĂticos Ă vida
humana, tais como os nossos automĂłveis.
Considerando que existem vĂĄrias formas de interagir com os sistemas de entretenimento do automĂłvel como
o Bluetooth, o Wi-fi ou CDs multimédia, a necessidade de auditar as suas interfaces tornou-se uma prioridade,
uma vez que elas representam um sério meio de aceeso à rede interna do carro. Atualmente, os mecanismos de
segurança de um carro focam-se na monitotização da rede CAN, deixando para trås as tecnologias referidas e não
contemplando os sistemas nĂŁo crĂticos. Como exemplo disso, o Bluetooth traz desafios diferentes da rede CAN,
uma vez que interage diretamente com o utilizador e estĂĄ exposto a ataques externos.
Uma abordagem alternativa para tornar o automĂłvel num sistema mais robusto Ă© manter sob supervisĂŁo as
comunicaçÔes que com este são estabelecidas. Ao implementar uma detecção de intrusão baseada em anomalias,
esta dissertação visa analisar o protocolo Bluetooth no sentido de identificar interaçÔes anormais que possam
alertar para uma situação fora dos padrĂ”es de utilização. Em Ășltima anĂĄlise, este produto de software embebido
incorpora uma grande margem de auto-aprendizagem, que é vital para enfrentar quaisquer ameaças desconhecidas
e aumentar os nĂveis de segurança globais. Ao longo deste documento, apresentamos o estudo do problema seguido
de uma metodologia alternativa que implementa um algoritmo baseado numa LSTM para prever a sequĂȘncia de
comandos HCI correspondentes a trĂĄfego Bluetooth normal. Os resultados mostram a forma como esta abordagem
pode impactar a deteção de intrusĂ”es nestes ambientes ao demonstrar uma grande capacidade para identificar padrĂ”es anĂłmalos no conjunto de dados considerado.In the last few years, hardware and software security have become a major concern. As the systemsâ complexity
increases, its vulnerabilities to several sophisticated attack techniques have escalated likewise. Quite often, the
problem lies in the heterogeneity of the devices connected to the vehicle, making it difficult to converge the monitoring
systems of all existing protocols into one security product. Thereby, the market requires more refined tools to monitor
life-risky environments such as personal vehicles.
Considering that there are several ways to interact with the carâs infotainment system, such as Wi-fi, Bluetooth,
or CD player, the need to audit these interfaces has become a priority as they represent a serious channel to reach
the internal car network. Nowadays, security in car networks focuses on CAN bus monitoring, leaving behind the
aforementioned technologies and not contemplating other non-critical systems. As an example of these concerns,
Bluetooth brings different challenges compared to CAN as it interacts directly with the user, being exposed to external
attacks.
An alternative approach to converting modern vehicles and their set of computers into more robust systems
is to keep track of established communications with them. By enforcing anomaly-based intrusion detection this
dissertation aims to analyze the Bluetooth protocol to identify abnormal user interactions that may alert for a non conforming pattern. Ultimately, such embedded software product incorporates a self-learning edge, which is vital to
face newly developed threats and increasing global security levels. Throughout this document, we present the study
case followed by an alternative methodology that implements an LSTM based algorithm to predict a sequence of
HCI commands corresponding to normal Bluetooth traffic. The results show how this approach can impact intrusion
detection in such environments by expressing a high capability of identifying abnormal patterns in the considered
data
Reframing museum epistemology for the information age: a discursive design approach to revealing complexity
This practice-based research inquiry examines the impact of an epistemic shift, brought about by the dawning of the information age and advances in networked communication technologies, on physical knowledge institutions - focusing on museums. The research charts adapting knowledge schemas used in museum knowledge organisation and discusses the potential for a new knowledge schema, the network, to establish a new epistemology for museums that reflects contemporary hyperlinked and networked knowledge. The research investigates the potential for networked and shared virtual reality spaces to reveal new âknowledge monumentsâ reflecting the epistemic values of the network society and the space of flows.
The central practice for this thesis focuses on two main elements. The first is applying networks and visual complexity to reveal multi-linearity and adapting perspectives in relational knowledge networks. This concept was explored through two discursive design projects, the Museum Collection Engine, which uses data visualisation, cloud data, and image recognition within an immersive projection dome to create a dynamic and searchable museum collection that returns new and interlinking constellations of museum objects and knowledge. The second discursive design project was Shared Pasts: Decoding Complexity, an AR app with a unique âanti-personalisationâ recommendation system designed to reveal complex narratives around historic objects and places. The second element is folksonomy and co-design in developing new community-focused archives using the community's language to build the dataset and socially tagged metadata. This was tested by developing two discursive prototypes, Women Reclaiming AI and Sanctuary Stories
A Closer Look into Recent Video-based Learning Research: A Comprehensive Review of Video Characteristics, Tools, Technologies, and Learning Effectiveness
People increasingly use videos on the Web as a source for learning. To
support this way of learning, researchers and developers are continuously
developing tools, proposing guidelines, analyzing data, and conducting
experiments. However, it is still not clear what characteristics a video should
have to be an effective learning medium. In this paper, we present a
comprehensive review of 257 articles on video-based learning for the period
from 2016 to 2021. One of the aims of the review is to identify the video
characteristics that have been explored by previous work. Based on our
analysis, we suggest a taxonomy which organizes the video characteristics and
contextual aspects into eight categories: (1) audio features, (2) visual
features, (3) textual features, (4) instructor behavior, (5) learners
activities, (6) interactive features (quizzes, etc.), (7) production style, and
(8) instructional design. Also, we identify four representative research
directions: (1) proposals of tools to support video-based learning, (2) studies
with controlled experiments, (3) data analysis studies, and (4) proposals of
design guidelines for learning videos. We find that the most explored
characteristics are textual features followed by visual features, learner
activities, and interactive features. Text of transcripts, video frames, and
images (figures and illustrations) are most frequently used by tools that
support learning through videos. The learner activity is heavily explored
through log files in data analysis studies, and interactive features have been
frequently scrutinized in controlled experiments. We complement our review by
contrasting research findings that investigate the impact of video
characteristics on the learning effectiveness, report on tasks and technologies
used to develop tools that support learning, and summarize trends of design
guidelines to produce learning video
Enabling changeability with typescript and microservices architecture in web applications
Changeability is a non-functional property of software that affects the length of its lifecycle. In this work, the microservices architectural pattern and TypeScript are studied through a literature review, focusing on how they enable the changeability of a web application.
The modularity of software is a key factor in enabling changeability. The micro-services architectural pattern and the programming language TypeScript can impact the changeability of web applications with modularity. Microservices architecture is a well-suited architectural pattern for web applications, as it allows for the creation of modular service components that can be modified and added to the system individually. TypeScript is a programming language that adds a type system and class-based object-oriented programming to JavaScript offering an array of features that enable modularity.
Through discussion on relationships between the changeability of web applications and their three key characteristics, scalability, robustness, and security, this work demonstrates the importance of designing for change to ensure that web applications remain maintainable, extensible, restructurable, and portable over time. Combined, the micro-services architecture and TypeScript can enhance the modularity and thus changeability of web applications
Assessing Text Representation Methods on Tag Prediction Task for StackOverflow
A large part of knowledge evolves outside of the operations of an organization. Question and answer online social platforms provide an important source of information to explore the underlying communities. StackOverflow (SO) is one of the most popular question and answer platforms for developers, with more than 23 million questions asked. Organizing and categorizing data is crucial to manage knowledge in such large quantities. Questions posted on SO are assigned a set of tags and textual content of each question may contain coding syntax. In this paper, we evaluate the performance of multiple text representation methods in the task of predicting tags for SO questions and empirically prove the impact of code syntax in text representations. The SO dataset was sampled and questions without code syntax were identified. Two classical text representation methods consisting of BoW and TF-IDF were selected along four other methods based on pre-trained models including Fasttext, USE, Sentence-BERT and Sentence-RoBERTa. Multi-label k'th Nearest Neighbors classifier was used to learn and predict tags based on the similarities between feature-vector representations of the input data. Our results indicate a consistent superiority of the representations generated from Sentence-RoBERTa. Overall, the classifier achieved a 17% or higher improvement on F1 score when predicting tags for questions without any code syntax in content
The Politics of Platformization: Amsterdam Dialogues on Platform Theory
What is platformization and why is it a relevant category in the contemporary political landscape? How is it related to cybernetics and the history of computation? This book tries to answer such questions by engaging in multidisciplinary dialogues about the first ten years of the emerging fields of platform studies and platform theory. It deploys a narrative and playful approach that makes use of anecdotes, personal histories, etymologies, and futurable speculations to investigate both the fragmented genealogy that led to platformization and the organizational and economic trends that guide nowadays platform sociotechnical imaginaries
IMAGINING, GUIDING, PLAYING INTIMACY: - A Theory of Character Intimacy Games -
Within the landscape of Japanese media production, and video game production in particular, there is a niche comprising video games centered around establishing, developing, and fulfilling imagined intimate relationships with anime-manga characters. Such niche, although very significant in production volume and lifespan, is left unexplored or underexplored. When it is not, it is subsumed within the scope of wider anime-manga media. This obscures the nature of such video games, alternatively identified with descriptors including but not limited to âvisual novelâ, âdating simulatorâ and âadult computer gameâ.
As games centered around developing intimacy with characters, they present specific ensembles of narrative content, aesthetics and software mechanics. These ensembles are aimed at eliciting in users what are, by all intents and purposes, parasocial phenomena towards the gameâs characters. In other words, these software products encourage players to develop affective and bodily responses towards characters. They are set in a way that is coherent with shared, circulating scripts for sexual and intimate interaction to guide player imaginative action. This study defines games such as the above as âcharacter intimacy gamesâ, video game software where traversal is contingent on players knowingly establishing, developing, and fulfilling intimate bonds with fictional characters. To do so, however, player must recognize themselves as playing that type of game, and to be looking to develop that kind of response towards the gameâs characters. Character Intimacy Games are contingent upon player developing affective and bodily responses, and thus presume that players are, at the very least, non-hostile towards their development. This study approaches Japanese character intimacy games as its corpus, and operates at the intersection of studies of communication, AMO studies and games studies.
The study articulates a research approach based on the double need of approaching single works of significance amidst a general scarcity of scholarly background on the subject. It juxtaposes data-driven approaches derived from fan-curated databases â The Visual Novel Database and Erogescape -ErogÄ HyĆron KĆ«kan â with a purpose-created ludo-hermeneutic process. By deploying an observation of character intimacy games through fan-curated data and building ludo-hermeneutics on the resulting ontology, this study argues that character intimacy games are video games where traversal is contingent on players knowingly establishing, developing, and fulfilling intimate bonds with fictional characters and recognizing themselves as doing so. To produce such conditions, the assemblage of software mechanics and narrative content in such games facilitates intimacy between player and characters. This is, ultimately, conductive to the emergence of parasocial phenomena. Parasocial phenomena, in turn, are deployed as an integral assumption regarding player activity within the gameâs wider assemblage of narrative content and software mechanics
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