No abstract

Android's graphical authentication mechanism requires users to unlock their devices by "drawing" a pattern that connects a sequence of contact points arranged in a 3x3 grid. Prior studies demonstrated that human-generated 3x3 patterns are weak (CCS'13); large portions can be trivially guessed with sufficient training. An obvious solution would be to increase the grid size to increase the complexity of chosen patterns. In this paper we ask the question: Does increasing the grid size increase the security of human-generated patterns? We conducted two large studies to answer this question, and our analysis shows that for both 3x3 and 4x4 patterns, there is a high incidence of repeated patterns and symmetric pairs (patterns that derive from others based on a sequence of flips and rotations), and many 4x4 patterns are expanded versions of 3x3 patterns. Leveraging this information, we developed an advanced guessing algorithm and used it to quantified the strength of the patterns using the partial guessing entropy. We find that guessing the first 20% (G0.2) of patterns for both 3x3 and 4x4 can be done as efficiently as guessing a random 2-digit PIN. While guessing larger portions of 4x4 patterns (G0.5) requires 2-bits more entropy than guessing the same ratio of 3x3 patterns, it remains on the order of cracking random 3-digit PINs. Of the patterns tested, our guessing algorithm successful cracks 15% of 3x3 patterns within 20 guesses (a typical phone lockout) and 19% of 4x4 patterns within 20 guesses; however, after 50,000 guesses, we correctly guess 95.9% of 3x3 patterns but only 66.7% of 4x4 patterns. While there may be some benefit to expanding the grid size to 4x4, we argue the majority of patterns chosen by users will remain trivially guessable and insecure against broad guessing attacks. Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

Given the nature of mobile devices and unlock procedures, unlock authentication is a prime target for credential leaking via shoulder sur ng, a form of an observation a ack. While the research community has investigated solutions to minimize or prevent the threat of shoulder sur ng, our understanding of how the a ack performs on current systems is less well studied. In this paper, we describe a large online experiment (n = 1173) that works towards establishing a baseline of shoulder sur ng vulnerability for current unlock authentication systems. Using controlled video recordings of a victim entering in a set of 4-and 6-length PINs and Android unlock pa erns on di erent phones from di erent angles, we asked participants to act as a ackers, trying to determine the authentication input based on the observation. We nd that 6-digit PINs are the most elusive a acking surface where a single observation leads to just 10.8% successful a acks (26.5% with multiple observations). As a comparison, 6-length Android pa erns, with one observation, were found to have an a ack rate of 64.2% (79.9% with multiple observations). Removing feedback lines for pa erns improves security to 35.3% (52.1% with multiple observations). is evidence, as well as other results related to hand position, phone size, and observation angle, suggests the best and worst case scenarios related to shoulder sur ng vulnerability which can both help inform users to improve their security choices, as well as establish baselines for researchers. CCS CONCEPTS•Security and privacy → Graphical / visual passwords; Social aspects of security and privacy;

We present a new oblivious RAM that supports variable-sized storage blocks (vORAM), which is the first ORAM to allow varying block sizes without trivial padding. We also present a new historyindependent data structure (a HIRB tree) that can be stored within a vORAM. Together, this construction provides an efficient and practical oblivious data structure (ODS) for a key/value map, and goes further to provide an additional privacy guarantee as compared to prior ODS maps: even upon client compromise, deleted data and the history of old operations remain hidden to the attacker. We implement and measure the performance of our system using Amazon Web Services, and the single-operation time for a realistic database (up to 2 18 entries) is less than 1 second. This represents a 100x speed-up compared to the current best oblivious map data structure (which provides neither secure deletion nor history independence) by Wang et al. (CCS 14).

Software Defined Networks (SDNs) are an appealing platform for network security applications. However, existing approaches to building security applications on SDNs are not practical because of performance and deployment challenges. Network security applications often need to analyze and process traffic in more advanced ways than SDN data plane implementations, such as OpenFlow, allow. Much of an application ends up running on the centralized controller, which forms an inherent bottleneck. Researchers have proposed application specific modifications to the underlying data plane to gain performance, but this results in a solution that is not deployable as it requires new switches and does not support all network security applications. In this paper, we introduce OFX (the OpenFlow Extension Framework) which harnesses the processing power of network switches to enable practical SDN security applications within an existing OpenFlow infrastructure. OFX allows applications to dynamically load software modules directly onto unmodified network switches where application-dependent processing/monitoring can execute closer to the data plane at a rate much closer to line speed. We implemented OFX modules for security applications including Silverline (ACSAC'13), BotMiner (Sec'08), and several others motivated by the custom OpenFlow extensions in Avant-Guard (CCS'13). We evaluated OFX on a Pica 8 3290 switch and found that processing traffic in an OFX module running on the switch had orders of magnitude less overhead than processing traffic at the controller. OFX increased the performance of the evaluated security application by 20-40x as compared to standard OpenFlow implementations and up to 1.25x when compared to middlebox implementations running on dedicated servers. This is all achieved without the need for additional or modified hardware. Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.