05 April 2017, 09:35, Track 2
Session chair: Jianying Zhou, Institute for Infocomm Research, Singapore
VTBPEKE: Verifier-based Two-Basis Password Exponential Key Exchange
David Pointcheval, Guilin Wang
PAKE protocols, for Password-Authenticated Key Exchange, enable two parties to establish a shared cryptographically strong key over an insecure network using a short common secret as authentication means. After the seminal work by Bellovin and Merritt, with the famous EKE, for Encrypted Key Exchange, various settings and security notions have been defined, and many protocols have been proposed. In this paper, we revisit the promising SPEKE, for Simple Password Exponential Key Exchange, proposed by Jablon. The only known security analysis works in the random oracle model under the CDH assumption, but in the multiplicative groups of finite fields only (subgroups of Zp*), which means the use of large elements and so huge communications and computations. Our new instantiation (TBPEKE, for Two-Basis Password Exponential Key Exchange) applies to any group, and our security analysis requires a DLIN-like assumption to hold. In particular, one can use elliptic curves, which leads to a better efficiency, at both the communication and computation levels. We additionally consider server corruptions, which immediately leak all the passwords to the adversary with symmetric PAKE. We thus study an asymmetric variant, also known as VPAKE, for Verifier-based Password Authenticated Key Exchange. We then propose a verifier-based variant of TBPEKE, the so-called VTBPEKE, which is also quite efficient, and resistant to server-compromise.
Boosting the Guessing Attack Performance on Android Lock Patterns with Smudge Attacks
Seunghun Cha, Sungsu Kwag, Hyoungshick Kim, Jun Ho Huh
Android allows 20 consecutive fail attempts on unlocking a device. This makes it difficult for pure guessing attacks to crack user patterns on a stolen device before it permanently locks itself. We investigate the effectiveness of combining Markov model-based guessing attacks with smudge attacks on unlocking Android devices within 20 attempts. Detected smudges are used to pre-compute all the possible segments and patterns, significantly reducing the pattern space that needs to be brute-forced. Our Markov-model was trained using 70% of a real-world pattern dataset that consists of 312 patterns. We recruited 12 participants to draw the remaining 30% on Samsung Galaxy S4, and used smudges they left behind to analyze the performance of the combined attack. Our results show that this combined method can significantly improve the performance of pure guessing attacks, cracking 74.17% of patterns compared to just 13.33% when the Markov model-based guessing attack was performed alone—those results were collected from a naive usage scenario where the participants were merely asked to unlock a given device. Even under a more complex scenario that asked the participants to use the Facebook app for a few minutes—obscuring smudges were added as a result—our combined attack, at 31.94%, still outperformed the pure guessing attack at 13.33%. Obscuring smudges can significantly affect the performance of smudge-based attacks. Based on this finding, we recommend that a mitigation technique should be designed to help users add obscurity, e.g., by asking users to draw a second random pattern upon unlocking a device.
Short Paper: What You See is Not What You Get: Leakage-Resilient Password Entry Schemes for Smart Glasses
Yan Li, Yao Cheng, Yingjiu Li, Robert H. Deng
Smart glasses are becoming popular for users to access various services such as email. To protect these services, password-based user authentication is widely used. Unfortunately, the password-based user authentication has inherent vulnerability against password leakage. Many efforts have been put on designing leakage-resilient password entry schemes on PCs and mobile phones with traditional input equipment including keyboards and touch screens. However, such traditional input equipment is not available on smart glasses. Existing password entry on smart glasses relies on additional PCs or mobile devices. Such solutions force users to switch between different systems, which causes interrupted experience and may lower the practicability and usability of smart glasses. In this paper, we propose a series of leakage-resilient password entry schemes on stand-alone smart glasses, which are gTapper, gRotator, and gTalker. These schemes ensure no leakage in password entry by breaking the correlation between the underlying password and the interaction observable to adversaries. They are practical in the sense that they only require a touch pad, a gyroscope, and a microphone which are commonly available on smart glasses. The usability of the proposed schemes is evaluated by user study under various test conditions which are common in users’ daily usage. The results of our user study reveal that the proposed schemes are easy-to-use so that users enter their passwords within moderate time, at high accuracy, and in various situations.