Onur Aciicmez

Bio: Onur Aciicmez is an academic researcher from Samsung. The author has contributed to research in topics: Cache & CPU cache. The author has an hindex of 29, co-authored 72 publications receiving 3638 citations. Previous affiliations of Onur Aciicmez include Intel & Oregon State University.

Detecting unauthorized use of computing devices based on behavioral patterns

Abstract: Techniques for detecting unauthorized use (e.g., malicious attacks) of the computing systems (e.g., computing devices) are disclosed. Unauthorized use can be detected based on patterns of use (e.g., behavioral patterns of use typically associated with a human being) of the computing systems. Acceptable behavioral pattern data can be generated for a computing system by monitoring the use of a support system (e.g., an operating system, a virtual environment) operating on the computing system. For example, a plurality of system support provider components of a support system (e.g., system calls, device drivers) can be monitored in order to generate the acceptable behavioral pattern data in a form which effectively defines an acceptable pattern of use (usage pattern) for the monitored system support provider components, thereby allowing detection of unauthorized use of a computing system by detecting any deviation from the acceptable pattern of use of the monitored system support provider components.

Predicting secret keys via branch prediction

Abstract: This paper announces a new software side-channel attack — enabled by the branch prediction capability common to all modern high-performance CPUs. The penalty paid (extra clock cycles) for a mispredicted branch can be used for cryptanalysis of cryptographic primitives that employ a data-dependent program flow. Analogous to the recently described cache-based side-channel attacks our attacks also allow an unprivileged process to attack other processes running in parallel on the same processor, despite sophisticated partitioning methods such as memory protection, sandboxing or even virtualization. In this paper, we will discuss several such attacks for the example of RSA, and experimentally show their applicability to real systems, such as OpenSSL and Linux. Moreover, we will also demonstrate the strength of the branch prediction side-channel attack by rendering the obvious countermeasure in this context (Montgomery Multiplication with dummy-reduction) as useless. Although the deeper consequences of the latter result make the task of writing an efficient and secure modular exponentiation (or scalar multiplication on an elliptic curve) a challenging task, we will eventually suggest some countermeasures to mitigate branch prediction side-channel attacks.

On the Power of Simple Branch Prediction Analysis.

Abstract: Very recently, a new software side-channel attack, called Branch Prediction Analysis (BPA) attack, has been discovered and also demonstrated to be practically feasible on popular commodity PC platforms. While the above recent attack still had the flavor of a classical timing attack against RSA, where one uses many execution-time measurements under the same key in order to statistically amplify some small but key-dependent timing differences, we dramatically improve upon the former result. We prove that a carefully written spy-process running simultaneously with an RSA-process, is able to collect during one single RSA signing execution almost all of the secret key bits. We call such an attack, analyzing the CPU’s Branch Predictor states through spying on a single quasi-parallel computation process, a Simple Branch Prediction Analysis (SBPA) attack — sharply differentiating it from those one relying on statistical methods and requiring many computation measurements under the same key. The successful extraction of almost all secret key bits by our SBPA attack against an OpenSSL RSA implementation proves that the often recommended blinding or so called randomization techniques to protect RSA against side-channel attacks are, in the context of SBPA attacks, totally useless. Additional to that very crucial security implication, targeted at such implementations which are assumed to be at least statistically secure, our successful SBPA attack also bears another equally critical security implication. Namely, in the context of simple side-channel attacks, it is widely believed that equally balancing the operations after branches is a secure countermeasure against such simple attacks. Unfortunately, this is not true, as even such “balanced branch” implementations can be completely broken by our SBPA attacks. Moreover, despite sophisticated hardware-assisted partitioning methods such as memory protection, sandboxing or even virtualization, SBPA attacks empower an unprivileged process to successfully attack other processes running in parallel on the same processor. Thus, we conclude that SBPA attacks are much more dangerous than previously anticipated, as they obviously do not belong to the same category as pure timing attacks.

On the power of simple branch prediction analysis

Abstract: Very recently, a new software side-channel attack, called Branch Prediction Analysis (BPA) attack, has been discovered and also demonstrated to be practically feasible on popular commodity PC platforms. While the above recent attack still had the flavor of a classical timing attack against RSA, where one uses many execution-time measurements under the same key in order to statistically amplify some small but key-dependent timing differences, we dramatically improve upon the former result. We prove that a carefully written spy-process running simultaneously with an RSA-process, is able to collect during one single RSA signing execution almost all of the secret key bits. We call such an attack, analyzing the CPU's Branch Predictor states through spying on a single quasi-parallel computation process, a Simple Branch Prediction Analysis (SBPA) attack --- sharply differentiating it from those one relying on statistical methods and requiring many computation measurements under the same key. The successful extraction of almost all secret key bits by our SBPA attack against an openSSL RSA implementation proves that the often recommended blinding or so called randomization techniques to protect RSA against side-channel attacks are, in the context of SBPA attacks, totally useless. Additional to that very crucial security implication, targeted at such implementations which are assumed to be at least statistically secure, our successful SBPA attack also bears another equally critical security implication. Namely, in the context of simple side-channel attacks, it is widely believed that equally balancing the operations after branches is a secure countermeasure against such simple attacks. Unfortunately, this is not true, as even such "balanced branch" implementations can be completely broken by our SBPA attacks. Moreover, despite sophisticated hardware-assisted partitioning methods such as memory protection, sandboxing or even virtualization, SBPA attacks empower an unprivileged process to successfully attack other processes running in parallel on the same processor. Thus, we conclude that SBPA attacks are much more dangerous than previously anticipated, as they obviously do not belong to the same category as pure timing attacks.

Yet another MicroArchitectural Attack: exploiting I-Cache

Abstract: MicroArchitectural Attacks (MA), which can be considered as a special form of Side-Channel Analysis, exploit microarchitectural functionalities of processor implementations and can compromise the security of computational environments even in the presence of sophisticated protection mechanisms like virtualization and sandboxing. This newly evolving research area has attracted significant interest due to the broad application range and the potentials of these attacks. Cache Analysis and Branch Prediction Analysis were the only types of MA that had been known publicly. In this paper, we introduce Instruction Cache (I-Cache) as yet another source of MA and present our experimental results which clearly prove the practicality and danger of I-Cache Attacks.

Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds

Abstract: Third-party cloud computing represents the promise of outsourcing as applied to computation. Services, such as Microsoft's Azure and Amazon's EC2, allow users to instantiate virtual machines (VMs) on demand and thus purchase precisely the capacity they require when they require it. In turn, the use of virtualization allows third-party cloud providers to maximize the utilization of their sunk capital costs by multiplexing many customer VMs across a shared physical infrastructure. However, in this paper, we show that this approach can also introduce new vulnerabilities. Using the Amazon EC2 service as a case study, we show that it is possible to map the internal cloud infrastructure, identify where a particular target VM is likely to reside, and then instantiate new VMs until one is placed co-resident with the target. We explore how such placement can then be used to mount cross-VM side-channel attacks to extract information from a target VM on the same machine.

Spectre Attacks: Exploiting Speculative Execution

Abstract: Modern processors use branch prediction and speculative execution to maximize performance. For example, if the destination of a branch depends on a memory value that is in the process of being read, CPUs will try to guess the destination and attempt to execute ahead. When the memory value finally arrives, the CPU either discards or commits the speculative computation. Speculative logic is unfaithful in how it executes, can access the victim's memory and registers, and can perform operations with measurable side effects. Spectre attacks involve inducing a victim to speculatively perform operations that would not occur during correct program execution and which leak the victim's confidential information via a side channel to the adversary. This paper describes practical attacks that combine methodology from side channel attacks, fault attacks, and return-oriented programming that can read arbitrary memory from the victim's process. More broadly, the paper shows that speculative execution implementations violate the security assumptions underpinning numerous software security mechanisms, including operating system process separation, containerization, just-in-time (JIT) compilation, and countermeasures to cache timing and side-channel attacks. These attacks represent a serious threat to actual systems since vulnerable speculative execution capabilities are found in microprocessors from Intel, AMD, and ARM that are used in billions of devices. While makeshift processor-specific countermeasures are possible in some cases, sound solutions will require fixes to processor designs as well as updates to instruction set architectures (ISAs) to give hardware architects and software developers a common understanding as to what computation state CPU implementations are (and are not) permitted to leak.

On lightweight mobile phone application certification

Abstract: Users have begun downloading an increasingly large number of mobile phone applications in response to advancements in handsets and wireless networks. The increased number of applications results in a greater chance of installing Trojans and similar malware. In this paper, we propose the Kirin security service for Android, which performs lightweight certification of applications to mitigate malware at install time. Kirin certification uses security rules, which are templates designed to conservatively match undesirable properties in security configuration bundled with applications. We use a variant of security requirements engineering techniques to perform an in-depth security analysis of Android to produce a set of rules that match malware characteristics. In a sample of 311 of the most popular applications downloaded from the official Android Market, Kirin and our rules found 5 applications that implement dangerous functionality and therefore should be installed with extreme caution. Upon close inspection, another five applications asserted dangerous rights, but were within the scope of reasonable functional needs. These results indicate that security configuration bundled with Android applications provides practical means of detecting malware.

FLUSH+RELOAD: a high resolution, low noise, L3 cache side-channel attack

Abstract: Sharing memory pages between non-trusting processes is a common method of reducing the memory footprint of multi-tenanted systems In this paper we demonstrate that, due to a weakness in the Intel X86 processors, page sharing exposes processes to information leaks We present FLUSH+RELOAD, a cache side-channel attack technique that exploits this weakness to monitor access to memory lines in shared pages Unlike previous cache side-channel attacks, FLUSH+RELOAD targets the Last-Level Cache (ie L3 on processors with three cache levels) Consequently, the attack program and the victim do not need to share the execution core We demonstrate the efficacy of the FLUSH+RELOAD attack by using it to extract the private encryption keys from a victim program running GnuPG 1413 We tested the attack both between two unrelated processes in a single operating system and between processes running in separate virtual machines On average, the attack is able to recover 967% of the bits of the secret key by observing a single signature or decryption round

Last-Level Cache Side-Channel Attacks are Practical

Abstract: We present an effective implementation of the Prime Probe side-channel attack against the last-level cache. We measure the capacity of the covert channel the attack creates and demonstrate a cross-core, cross-VM attack on multiple versions of GnuPG. Our technique achieves a high attack resolution without relying on weaknesses in the OS or virtual machine monitor or on sharing memory between attacker and victim.