Jay Koven, Enrico Bertini, Luke Dubois, and Nasir Memon Large email data sets are often the focus of criminal and civil investigations. This has created a daunting task for investigators due to the extraordinary size of many of these collections. Our work offers an interactive visual analytic alternative to the current, manually intensive methodology used...
Category: Publications
Cybersecurity for Control Systems: A Process-Aware Perspective
Farshad Khorrami, Prashanth Krishnamurthy, and Ramesh Karri The authors argue that it is vital to develop effective real-time attack monitoring and threat mitigation mechanisms.
The Right to be Forgotten in the Media: A Data-Driven Study
Minhui Xue, Gabriel Magno, Evandro Cunha, Virgilio Almeida, and Keith W. Ross Due to the recent “Right to be Forgotten” (RTBF) ruling, for queries about an individual, Google and other search engines now delist links to web pages that contain “inadequate, irrelevant or no longer relevant, or excessive” information about that individual. In this paper...
Cross-layer secure cyber-physical control system design for networked 3D printers
Zhiheng Xu, Quanyan Zhu The authors explore the vulnerabilities of 3D-printing systems, and design a cross-layer approach for the system.
Deterring Financially Motivated Cybercrime
Zachary K. Goldman and Damon McCoy In “Deterring Financially Motivated Cybercrime,” Zachary K. Goldman and Damon McCoy present three strategies for deterring attacks that use malicious cyber capabilities to generate a profit.
The Cybersecurity Competition Experience: Perceptions from Cybersecurity Workers
Colin Wee, Masooda Bashir, and Nasir Memon How do workers within the field of cybersecurity perceive cybersecurity competitions? This study aims to address this question and investigate if competitions left a positive mark on the information security workers who participated in them.
Student research highlight: Secure and resilient distributed machine learning under adversarial environments
Rui Zhang and Quanyan Zhu Machine learning algorithms, such as support vector machines (SVMs), neutral networks, and decision trees (DTs) have been widely used in data processing for estimation and detection. They can be used to classify samples based on a model built from training data. However, under the assumption that training and testing samples come...
Do You Trust Your Chip?
Ozgur Sinanoglu This talk will cover various forms of threats that the electronic chip supply chain is up against, as well as defenses against these threats. The talk will elucidate the development of CAD algorithms/tools for this newly emerging field by mostly leveraging principles from other more mature research domains.
Profiling Underground Merchants Based on Network Behavior
Srikanth Sundaresan, Damon McCoy, Sadia Afroz, and Vern Paxson Online underground forums serve a key role in facilitating information exchange and commerce between gray market or even cybercriminal actors. In order to streamline bilateral communication to complete sales, merchants often publicly post their IM contact details, such as their Skype handle. Merchants that publicly post...
Coding Schemes for Securing Cyber-Physical Systems Against Stealthy Data Injection Attacks
Fei Miao, Quanyan Zhu, Miroslav Pajic, and George J. Pappas This paper considers a method of coding the sensor outputs in order to detect stealthy false data injection attacks.