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Full-Text Articles in Engineering
Supercomputers And Quantum Computing On The Axis Of Cyber Security, Haydar Yalcin, Tugrul Daim, Mahdieh Mokhtari Moughari, Alain Mermoud
Supercomputers And Quantum Computing On The Axis Of Cyber Security, Haydar Yalcin, Tugrul Daim, Mahdieh Mokhtari Moughari, Alain Mermoud
Engineering and Technology Management Faculty Publications and Presentations
Cybersecurity has become a very critical area to address for governments, industry and the academic community. Cyber attacks are on the rise so is research to address the challenges presented by these attacks. Research yields several technological advancements. This paper explores the development of quantum computing and supercomputers within the context of cybersecurity. As many governments and organizations are under the threat of cyber-attacks, it is critical and timely to explore the status of technological development. We use advanced scientometric techniques to disclose the development status and identify the centers of excellence. The research uses bibliometric data of published papers …
Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy
Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy
Turkish Journal of Electrical Engineering and Computer Sciences
Local differential privacy (LDP) has recently emerged as an accepted standard for privacy-preserving collection of users’ data from smartphones and IoT devices. In many practical scenarios, users’ data needs to be collected repeatedly across multiple iterations. In such cases, although each collection satisfies LDP individually by itself, a longitudinal collection of multiple responses from the same user degrades that user’s privacy. To demonstrate this claim, in this paper, we propose longitudinal attacks against iterative data collection with LDP. We formulate a general Bayesian adversary model, and then individually show the application of this adversary model on six popular LDP protocols: …
Using Feature Selection Enhancement To Evaluate Attack Detection In The Internet Of Things Environment, Khawlah Harahsheh, Rami Al-Naimat, Chung-Hao Chen
Using Feature Selection Enhancement To Evaluate Attack Detection In The Internet Of Things Environment, Khawlah Harahsheh, Rami Al-Naimat, Chung-Hao Chen
Electrical & Computer Engineering Faculty Publications
The rapid evolution of technology has given rise to a connected world where billions of devices interact seamlessly, forming what is known as the Internet of Things (IoT). While the IoT offers incredible convenience and efficiency, it presents a significant challenge to cybersecurity and is characterized by various power, capacity, and computational process limitations. Machine learning techniques, particularly those encompassing supervised classification techniques, offer a systematic approach to training models using labeled datasets. These techniques enable intrusion detection systems (IDSs) to discern patterns indicative of potential attacks amidst the vast amounts of IoT data. Our investigation delves into various aspects …