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Jakub Szefer

Publications and source records attributed to Jakub Szefer.

43 records · Page 3Linked to original sources

Power Side-Channel Attacks on BNN Accelerators in Remote FPGAs

To lower cost and increase the utilization of Cloud Field-Programmable Gate Arrays (FPGAs), researchers have recently been exploring the concept of multi-tenant FPGAs, where multiple independent users simultaneously share the same remote FPGA. Despite its benefits, multi-tenancy opens up the possibility of malicious users co-locating on the same FPGA as a victim user, and extracting sensitive information. This issue becomes especially serious when the user is running a machine learning algorithm that is processing sensitive or private information. To demonstrate the dangers, this paper presents a remote, power-based side-channel attack on a deep neural network accelerator running in a variety of Xilinx FPGAs and also on Cloud FPGAs using Amazon Web Services (AWS) F1 instances. This work in particular shows how to remotely obtain voltage estimates as a deep neural network inference circuit executes, and how the information can be used to recover the inputs to the neural network. The attack is demonstrated with a binarized convolutional neural network used to recognize handwriting images from the MNIST handwritten digit database. With the use of precise time-to-digital converters for remote voltage estimation, the MNIST inputs can be successfully recovered with a maximum normalized cross-correlation of 79% between the input image and the recovered image on local FPGA boards and 72% on AWS F1 instances. The attack requires no physical access nor modifications to the FPGA hardware.

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Survey of Transient Execution Attacks

Transient execution attacks, also called speculative execution attacks, have drawn much interest as they exploit the transient execution of instructions, e.g., during branch prediction, to leak data. Transient execution is fundamental to modern computer architectures, yet poses a security risk as has been demonstrated. Since the first disclosure of Spectre and Meltdown attacks in January 2018, a number of new attack types or variants of the attacks have been presented. These attacks have motivated computer architects to rethink the design of processors and propose hardware defenses. This paper summarizes the components and the phases of the transient execution attacks. Each of the components is further discussed and categorized. A set of metrics is proposed for each component to evaluate the feasibility of an attack. Moreover, the data that can be leaked in the attacks are summarized. Further, the existing attacks are compared, and the limitations of these attacks are discussed based on the proposed metrics. In the end, existing mitigations at the micro-architecture level from literature are discussed.

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Leaking Information Through Cache LRU States

The Least-Recently Used cache replacement policy and its variants are widely deployed in modern processors. This paper shows for the first time in detail that the LRU states of caches can be used to leak information: any access to a cache by a sender will modify the LRU state, and the receiver is able to observe this through a timing measurement. This paper presents LRU timing-based channels both when the sender and the receiver have shared memory, e.g., shared library data pages, and when they are separate processes without shared memory. In addition, the new LRU timing-based channels are demonstrated on both Intel and AMD processors in scenarios where the sender and the receiver are sharing the cache in both hyper-threaded setting and time-sliced setting. The transmission rate of the LRU channels can be up to 600Kbps per cache set in the hyper-threaded setting. Different from the majority of existing cache channels which require the sender to trigger cache misses, the new LRU channels work with the sender only having cache hits, making the channel faster and more stealthy. This paper also demonstrates that the new LRU channels can be used in transient execution attacks, e.g., Spectre. Further, this paper shows that the LRU channels pose threats to existing secure cache designs, and this work demonstrates the LRU channels affect the secure PL cache. The paper finishes by discussing and evaluating possible defenses.

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A Benchmark Suite for Evaluating Caches' Vulnerability to Timing Attacks

Timing-based side or covert channels in processor caches continue to present a threat to computer systems, and they are the key to many of the recent Spectre and Meltdown attacks. Based on improvements to an existing three-step model for cache timing-based attacks, this work presents 88 Strong types of theoretical timing-based vulnerabilities in processor caches. To understand and evaluate all possible types of vulnerabilities in processor caches, this work further presents and implements a new benchmark suite which can be used to test to which types of cache timing-based attacks a given processor or cache design is vulnerable. In total, there are 1094 automatically-generated test programs which cover the 88 theoretical vulnerabilities. The benchmark suite generates the Cache Timing Vulnerability Score which can be used to evaluate how vulnerable a specific cache implementation is to different attacks. A smaller Cache Timing Vulnerability Score means the design is more secure, and the scores among different machines can be easily compared. Evaluation is conducted on commodity Intel and AMD processors and shows the differences in processor implementations can result in different types of attacks that they are vulnerable to. Beyond testing commodity processors, the benchmarks and the Cache Timing Vulnerability Score can be used to help designers of new secure processor caches evaluate their design's susceptibility to cache timing-based attacks.

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MagneticSpy: Exploiting Magnetometer in Mobile Devices for Website and Application Fingerprinting

Recent studies have shown that aggregate CPU usage and power consumption traces on smartphones can leak information about applications running on the system or websites visited. In response, access to such data has been blocked for mobile applications starting from Android 8. In this work, we explore a new source of side-channel leakage for this class of attacks. Our method is based on the fact that electromagnetic activity caused by mobile processors leads to noticeable disturbances in magnetic sensor measurements on mobile devices, with the amplitude being proportional to the CPU workload. Therefore, recorded sensor data can be analyzed to reveal information about ongoing activities. The attack works on a number of devices: we evaluated 80 models of modern smartphones and tablets and observed the reaction of the magnetometer to the CPU activity on 56 of them. On selected devices we were able to successfully identify which application has been opened (with up to 90% accuracy) or which web page has been loaded (up to 91% accuracy). The presented side channel poses a significant risk to end users' privacy, as the sensor data can be recorded from native apps or even from web pages without user permissions. Finally, we discuss possible countermeasures to prevent the presented information leakage.

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Intrinsic Rowhammer PUFs: Leveraging the Rowhammer Effect for Improved Security

Physically Unclonable Functions (PUFs) have become an important and promising hardware primitive for device fingerprinting, device identification, or key storage. Intrinsic PUFs leverage components already found in existing devices, unlike extrinsic silicon PUFs, which are based on customized circuits that involve modification of hardware. In this work, we present a new type of a memory-based intrinsic PUF, which leverages the Rowhammer effect in DRAM modules; the Rowhammer PUF. Our PUF makes use of bit flips, which occur in DRAM cells due to rapid and repeated access of DRAM rows. Prior research has mainly focused on Rowhammer attacks, where the Rowhammer effect is used to illegitimately alter data stored in memory, e.g., to change page table entries or enable privilege escalation attacks. Meanwhile, this is the first work to use the Rowhammer effect in a positive context: to design a novel PUF. We extensively evaluate the Rowhammer PUF using commercial, off-the-shelf devices, not relying on custom hardware or an FPGA-based setup. The evaluation shows that the Rowhammer PUF holds required properties needed for the envisioned security applications, and could be deployed today.

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Practical and Scalable Security Verification of Secure Architectures

We present a new and practical framework for security verification of secure architectures. Specifically, we break the verification task into external verification and internal verification. External verification considers the external protocols, i.e. interactions between users, compute servers, network entities, etc. Meanwhile, internal verification considers the interactions between hardware and software components within each server. This verification framework is general-purpose and can be applied to a stand-alone server, or a large-scale distributed system. We evaluate our verification method on the CloudMonatt and HyperWall architectures as examples.

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