With sensitive data being increasingly stored on mobile devices and laptops, hard disk encryption is more important than ever. In particular, being able to plausibly deny that a hard disk contains certain information is a very useful and interesting research goal. However, it has been known for some time that existing "hidden volume" solutions, like TrueCrypt, fail in the face of an adversary who is able to observe the contents of a disk on multiple, separate occasions. In this work, we explore more robust constructions for hidden volumes and present HIVE, which is resistant to more powerful adversaries with multiple-snapshot capabilities. In pursuit of this, we propose the first security definitions for hidden volumes, and prove HIVE secure under these definitions. At the core of HIVE, we design a new write-only Oblivious RAM. We show that, when only hiding writes, it is possible to achieve ORAM with optimal O(1) communication complexity and only poly-logarithmic user memory. This is a significant improvement over existing work and an independently interesting result. We go on to show that our writeonly ORAM is specially equipped to provide hidden volume functionality with low overhead and significantly increased security. Finally, we implement HIVE as a Linux kernel block device to show both its practicality and usefulness on existing platforms.

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As more and more Internet-based attacks arise, organizations are responding by deploying an assortment of security products that generate situational intelligence in the form of logs. These logs often contain high volumes of interesting and useful information about activities in the network, and are among the first data sources that information security specialists consult when they suspect that an attack has taken place. However, security products often come from a patchwork of vendors, and are inconsistently installed and administered. They generate logs whose formats differ widely and that are often incomplete, mutually contradictory, and very large in volume. Hence, although this collected information is useful, it is often dirty.We present a novel system, Beehive, that attacks the problem of automatically mining and extracting knowledge from the dirty log data produced by a wide variety of security products in a large enterprise. We improve on signaturebased approaches to detecting security incidents and instead identify suspicious host behaviors that Beehive reports as potential security incidents. These incidents can then be further analyzed by incident response teams to determine whether a policy violation or attack has occurred. We have evaluated Beehive on the log data collected in a large enterprise, EMC, over a period of two weeks. We compare the incidents identified by Beehive against enterprise Security Operations Center reports, antivirus software alerts, and feedback from enterprise security specialists. We show that Beehive is able to identify malicious events and policy violations which would otherwise go undetected.

Abstract.A poorly designed web browser extension with a security vulnerability may expose the whole system to an attacker. Therefore, attacks directed at "benign-but-buggy" extensions, as well as extensions that have been written with malicious intents pose significant security threats to a system running such components. Recent studies have indeed shown that many Firefox extensions are over-privileged, making them attractive attack targets. Unfortunately, users currently do not have many options when it comes to protecting themselves from extensions that may potentially be malicious. Once installed and executed, the extension needs to be trusted. This paper introduces Sentinel, a policy enforcer for the Firefox browser that gives fine-grained control to the user over the actions of existing JavaScript Firefox extensions. The user is able to define policies (or use predefined ones) and block common attacks such as data exfiltration, remote code execution, saved password theft, and preference modification. Our evaluation of Sentinel shows that our prototype implementation can effectively prevent concrete, realworld Firefox extension attacks without a detrimental impact on users' browsing experience.