演讲人：王晓峰教授｜印第安纳大学
时间：6 月 5 日（周五）上午 10:00-11:00
地点：软件楼 102 第二会议室
联系人：杨哲慜 yangzhemin@fudan.edu.cn
Abstract:
Stealing of sensitive information from apps is always considered to be one of the most critical threats to Android security. Recent studies show that this can happen even to the apps without explicit implementation flaws, through exploiting some design weaknesses of the operating system, e.g., shared communication channels such as Bluetooth, and side channels like memory, network-data usages, etc. In all these attacks, a malicious app needs to run side-by-side with the target app (the victim) to collect its runtime information. Examples include recording phone conversations from the phone app, gathering WebMD’s data usages to infer the disease condition the user looks at, etc. This runtime-information-gathering (RIG) threat is realistic and serious, as demonstrated by prior research and our new findings, which reveal that the malware monitoring popular Android-based home security systems can figure out when the house is empty and the user is not looking at surveillance cameras, and even turn off the alarm delivered to her phone.
To defend against this new category of attacks, we propose a novel technique that changes neither the operating system nor the target apps, and provides immediate protection as soon as an ordinary app (with only normal and dangerous permissions) is installed. This new approach, called App Guardian, thwarts a malicious app’s runtime monitoring attempt by pausing all suspicious background processes when the target app (called principal) is running in the foreground, and resuming them after the app stops and its runtime environment is cleaned up. Our technique leverages a unique feature of Android, on which third party apps running in the background are often considered to be disposable and can be stopped anytime with only a minor performance and utility implication. We further limit such an impact by only focusing on a small set of suspicious background apps, which are identified by their behaviors inferred from their side channels (e.g., thread names, CPU scheduling and kernel time). App Guardian is also carefully designed to choose the right moments to start and end the protection procedure, and effectively protect itself against malicious apps. Our experimental studies show that this new technique defeated all known RIG attacks, with small impacts on the utility of legitimate apps and the performance of the OS. Most importantly, the idea underlying our approach, including app-level protection, side-channel based defense and lightweight response, not only significantly raises the bar for the RIG attacks and the research on this subject but can also inspire the follow-up effort on new detection systems practically deployable in the fragmented Android ecosystem.
Bio:
Dr. XiaoFeng Wang is a professor in the School of Informatics and Computing at Indiana University, Bloomington. He received his Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University in 2004, and has since been a faculty member at IU. Dr. Wang is a well-recognized active researcher on system and network security. His work focuses on cloud and mobile security, and data privacy (particularly the privacy challenges in large-scale analysis and dissemination of human genomic data). He is a recipient of 2011 Award for Outstanding Research in Privacy Enhancing Technologies (the PET Award) and the Best Practical Paper Award at the 32nd IEEE Symposium on Security and Privacy. His work frequently receives attention from the media, including CNN, MSNBC, Slashdot, CNet, PC World, etc. His research is supported by the NIH, NSF, Department of Homeland Security, the Air Force and Microsoft Research. He has been serving as the director for the Center for Security Informatics at IU since 2011.
