RSA is a widely used public-key cipher and has been ported onto GPUs for signing and decrypting large files. Although performance has been significantly improved, the security of RSA on GPUs is vulnerable to side-channel timing attacks and is an exposure overlooked in previous studies.Luo, Chao...
In this work, we demonstrate how contention for on-chip bandwidth in GPUs can lead to fine-grain information leakage and enable side-channel attacks. As a case study, we demonstrate how RSA key bit information can be leaked on a real GPU. We also describe how interconnect characteristics ...
org.bouncycastle:bctls-jdk18on (Maven) < 1.78 1.78 Description An issue was discovered in Bouncy Castle Java TLS API and JSSE Provider before 1.78. Timing-based leakage may occur in RSA based handshakes because of exception processing. References https://nvd.nist.gov/vuln/detail/CVE-2024-301...
Side-channel attacks are categorised into physical and functional [37]. The physical categorisation is based on a measurable quantity that is the by-product of the implementation. Examples are power output, electromagnetic emission, clock timing, user interaction, acoustic, optical, thermal, and ...
present a new GPU side-channel attack in 2021 by targeting different levels of caching in devices [27]. In 2022, Mojtaba et al. [19] proposed a cash occupancy attack through browser cache side-channel data based on the Prime and Probe technique. It exploits the variations in cache ...
With the in-depth integration of deep learning and side-channel analysis (SCA) technology, the security threats faced by embedded devices based on the Internet of Things (IoT) have become increasingly prominent. By building a neural network model as a discriminator, the correlation between the sid...
In this work, we focus on side-channel analysis (SCA). Side-channel analysis is a non-invasive implementation attack, focusing on extracting leaked information during the algorithm’s execution. Examples of these leakages include the following: timing [1], power consumption [2], electromagnetic ...
However, the majority of existing Deep-Learning Side-Channel Attacks (DLSCAs) primarily focus on the classification accuracy of the trained model at the attack stage, often assuming that adversaries have unlimited computational and time resources during the profiling stage. This might result in an ...