Biblio

Filters: Author is Zhang, Yinqian  [Clear All Filters]
2019-11-12
Zhang, Tianwei, Zhang, Yinqian, Lee, Ruby B..  2018.  Analyzing Cache Side Channels Using Deep Neural Networks. Proceedings of the 34th Annual Computer Security Applications Conference. :174-186.

Cache side-channel attacks aim to breach the confidentiality of a computer system and extract sensitive secrets through CPU caches. In the past years, different types of side-channel attacks targeting a variety of cache architectures have been demonstrated. Meanwhile, different defense methods and systems have also been designed to mitigate these attacks. However, quantitatively evaluating the effectiveness of these attacks and defenses has been challenging. We propose a generic approach to evaluating cache side-channel attacks and defenses. Specifically, our method builds a deep neural network with its inputs as the adversary's observed information, and its outputs as the victim's execution traces. By training the neural network, the relationship between the inputs and outputs can be automatically discovered. As a result, the prediction accuracy of the neural network can serve as a metric to quantify how much information the adversary can obtain correctly, and how effective a defense solution is in reducing the information leakage under different attack scenarios. Our evaluation suggests that the proposed method can effectively evaluate different attacks and defenses.

2018-09-28
Gu, Yufei, Zhao, Qingchuan, Zhang, Yinqian, Lin, Zhiqiang.  2017.  PT-CFI: Transparent Backward-Edge Control Flow Violation Detection Using Intel Processor Trace. Proceedings of the Seventh ACM on Conference on Data and Application Security and Privacy. :173–184.
This paper presents PT-CFI, a new backward-edge control flow violation detection system based on a novel use of a recently introduced hardware feature called Intel Processor Trace (PT). Designed primarily for offline software debugging and performance analysis, PT offers the capability of tracing the entire control flow of a running program. In this paper, we explore the practicality of using PT for security applications, and propose to build a new control flow integrity (CFI) model that enforces a backward-edge CFI policy for native COTS binaries based on the traces from Intel PT. By exploring the intrinsic properties of PT with a system call based synchronization primitive and a deep inspection capability, we have addressed a number of technical challenges such as how to make sure the backward edge CFI policy is both sound and complete, how to make PT enforce our CFI policy, and how to balance the performance overhead. We have implemented PT-CFI and evaluated with a number of programs including SPEC2006 and HTTP daemons. Our experimental results show that PT-CFI can enforce a perfect backward-edge CFI with only small overhead for the protected program.
2018-06-07
Xiao, Yuan, Li, Mengyuan, Chen, Sanchuan, Zhang, Yinqian.  2017.  STACCO: Differentially Analyzing Side-Channel Traces for Detecting SSL/TLS Vulnerabilities in Secure Enclaves. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :859–874.
Intel Software Guard Extension (SGX) offers software applications a shielded execution environment, dubbed enclave, to protect their confidentiality and integrity from malicious operating systems. As processors with this extended feature become commercially available, many new software applications are developed to enrich to the SGX-enabled ecosystem. One important primitive for these applications is a secure communication channel between the enclave and a remote trusted party. The SSL/TLS protocol, which is the de facto standard for protecting transport-layer network communications, has been broadly regarded a natural choice for such purposes. However, in this paper, we show that the marriage between SGX and SSL may not be smooth sailing. Particularly, we consider a category of side-channel attacks against SSL/TLS implementations in secure enclaves, which we call the control-flow inference attacks. In these attacks, the malicious operating system kernel may perform a powerful man-in-the-kernel attack to collect execution traces of the enclave programs at the page level, the cacheline level, or the branch level, while positioning itself in the middle of the two communicating parties. At the center of our work is a differential analysis framework, dubbed Stacco, to dynamically analyze the SSL/TLS implementations and detect vulnerabilities-discernible execution traces-that can be exploited as decryption oracles. Surprisingly, in spite of the prevailing constant-time programming paradigm adopted by many cryptographic libraries, we found exploitable vulnerabilities in the latest versions of all the SSL/TLS libraries we have examined. To validate the detected vulnerabilities, we developed a man-in-the-kernel adversary to demonstrate Bleichenbacher attacks against the latest OpenSSL library running in the SGX enclave (with the help of Graphene) and completely broke the PreMasterSecret encrypted by a 4096-bit RSA public key with only 57286 queries. We also conducted CBC padding oracle attacks against the latest GnuTLS running in Graphene-SGX and an open-source SGX implementation of mbedTLS (i.e., mbedTLS-SGX) that runs directly inside the enclave, and showed that it only needs 48388 and 25717 queries, respectively, to break one block of AES ciphertext. Empirical evaluation suggests these man-in-the-kernel attacks can be completed within 1 or 2 hours. Our results reveal the insufficient understanding of side-channel security in SGX settings, and our study will provoke discussions on the secure implementation and adoption of SSL/TLS in secure enclaves.
2018-04-11
Wang, Wenhao, Chen, Guoxing, Pan, Xiaorui, Zhang, Yinqian, Wang, XiaoFeng, Bindschaedler, Vincent, Tang, Haixu, Gunter, Carl A..  2017.  Leaky Cauldron on the Dark Land: Understanding Memory Side-Channel Hazards in SGX. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :2421–2434.

Side-channel risks of Intel SGX have recently attracted great attention. Under the spotlight is the newly discovered page-fault attack, in which an OS-level adversary induces page faults to observe the page-level access patterns of a protected process running in an SGX enclave. With almost all proposed defense focusing on this attack, little is known about whether such efforts indeed raise the bar for the adversary, whether a simple variation of the attack renders all protection ineffective, not to mention an in-depth understanding of other attack surfaces in the SGX system. In the paper, we report the first step toward systematic analyses of side-channel threats that SGX faces, focusing on the risks associated with its memory management. Our research identifies 8 potential attack vectors, ranging from TLB to DRAM modules. More importantly, we highlight the common misunderstandings about SGX memory side channels, demonstrating that high frequent AEXs can be avoided when recovering EdDSA secret key through a new page channel and fine-grained monitoring of enclave programs (at the level of 64B) can be done through combining both cache and cross-enclave DRAM channels. Our findings reveal the gap between the ongoing security research on SGX and its side-channel weaknesses, redefine the side-channel threat model for secure enclaves, and can provoke a discussion on when to use such a system and how to use it securely.

2017-10-10
Zhang, Xiaokuan, Xiao, Yuan, Zhang, Yinqian.  2016.  Return-Oriented Flush-Reload Side Channels on ARM and Their Implications for Android Devices. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :858–870.

Cache side-channel attacks have been extensively studied on x86 architectures, but much less so on ARM processors. The technical challenges to conduct side-channel attacks on ARM, presumably, stem from the poorly documented ARM cache implementations, such as cache coherence protocols and cache flush operations, and also the lack of understanding of how different cache implementations will affect side-channel attacks. This paper presents a systematic exploration of vectors for flush-reload attacks on ARM processors. flush-reload attacks are among the most well-known cache side-channel attacks on x86. It has been shown in previous work that they are capable of exfiltrating sensitive information with high fidelity. We demonstrate in this work a novel construction of flush-reload side channels on last-level caches of ARM processors, which, particularly, exploits return-oriented programming techniques to reload instructions. We also demonstrate several attacks on Android OS (e.g., detecting hardware events and tracing software execution paths) to highlight the implications of such attacks for Android devices.