data security

Securing data against non-conventional adversaries

Prof. Mohammad Mannan, Concordia Institute for Information Systems Engineering, Concordia University, Montreal

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B4 L5 R5220.

I will discuss four related proposals: Gracewipe (coercion-resistant disk data deletion), Hypnoguard (cold-boot protection for RAM data in sleep), SafeKeeper (protecting web credentials from rougue IT admins), and Blindfold (protecting PKI private keys from human admins). While our solutions are possibly a step forward, more importantly, we highlight pitfalls of such solutions against a strong adversary.

Tackling credential abuse together

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B9 L2 H2 H2.

Despite long-ago predictions (e.g., see Bill Gates, 2004) that other user-authentication technologies would replace passwords, passwords remain not only pervasive but have flourished as the dominant form of account protection, especially at websites such as retailers that require a low-friction user experience. This talk will describe our research on methods to tackle three key ingredients of account takeovers for password-protected accounts today: (i) site database breaches, which is the largest source of stolen passwords for internet sites; (ii) the tendency of users to reuse the same or similar passwords across sites; and (iii) credential stuffing, in which attackers submit breached credentials for one site in login attempts for the same users' accounts at another.

Xiaojie Zhu

Xiaojie Zhu is a staff research scientist at KAUST. Prior to that, he was an assistant professor of cybersecurity in the Department of Computer Science and Information Technology, College of Engineering, Abu Dhabi University. He received his Ph.D. from the Department of Computer Science, University of Oslo, Norway. Xiaojie's research interests are data security and privacy, software security, decentralized trust and infrastructure, and applied cryptography. He has published in prestigious journals such as IEEE TDSC, IEEE TPDS, JNCA, and JOS. One of his articles was included in the 21st annual

Muhamad Felemban

Muhamad Felemban obtained his Master's degree in Computer Science under the supervision of Professor Basem Shihada at King Abdullah University of Science and Technology (KAUST) in 2011. Muhamad received a B.S. degree from King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, in 2008, and a Ph.D. degree from the School of Electrical and Computer Engineering, Purdue University, in 2018. Currently, he is an Assistant Professor in the Computer Engineering department at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. Master's Thesis title: " Optimal Node