Description
Hardware Trojan Horses that are software-exploitable can be inserted into microprocessors, allowing attackers to run unauthorized code or escalate privileges. Additionally, it has been demonstrated that attackers could observe certain microprocessor features - seemingly unrelated to the program's execution - to exfiltrate secrets or private data. So, even devices produced in secure foundries could be vulnerable to such attacks. A promising defense strategy involves implementing Hardware Security Modules that monitor the runtime behavior of microprocessors to detect ongoing attacks. But why do we need Hardware Security Modules? Are software-based solutions not sufficient? Hardware Security Modules are essential because if attackers manage to execute malicious code, they could bypass or disable software defenses, leading to privilege escalation and other serious consequences. In contrast, hardware-based countermeasures raise the bar significantly, as modifying fabricated chips is far more difficult than compromising software, making Hardware Security Module implementations a more robust and resilient defense mechanism.
Practical infos
Next sessions
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I know what your compiler did: Optimization Effects on Power Side-Channel Leakage for RISC-V
Speaker : Ileana Buhan - Radboud University Nijmegen
With the growing prevalence of software-based cryptographic implementations in high-level languages, understanding the role of architectural and micro-architectural components in side-channel security is critical. The role of compilers in case of software implementations towards contribution to side-channel leaks is not investigated. While timing-based side-channel leakage due to compiler effects[…]-
SemSecuElec
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Side-channel
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Covert Communication Channels Based On Hardware Trojans: Open-Source Dataset and AI-Based Detection
Speaker : Alan Díaz Rizo - Sorbonne Université Lip6
The threat of Hardware Trojan-based Covert Channels (HT-CCs) presents a significant challenge to the security of wireless communications. In this work, we generate in hardware and make open-source a dataset for various HT-CC scenarios. The dataset represents transmissions from a HT-infected RF transceiver hiding a CC that leaks information. It encompasses a wide range of signal impairments, noise[…]-
SemSecuElec
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Machine learning
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Hardware trojan
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Measurement the thermal component of clock jitter used as entropy source by TRNGs
Speaker : Arturo GARAY - STMicroelectronics
Introduction Measuring the thermal component of clock jitter as an entropy source for True Random Number Generators (TRNGs) is compulsory for the security and evaluation of clock-jitter based TRNGs. However, identifying and isolating the local thermal noise component from other noise sources, particularly flicker noise, while performing a precise measurement remains a challenge. Current[…]-
SemSecuElec
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TRNG
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Cryptanalytical extraction of complex Neural Networks in black-box settings
Speaker : Benoit COQUERET - INRIA, Thales CESTI
With the widespread development of artifical intelligence, Deep Neural Networks (DNN) have become valuable intellectual property (IP). In the past few years, software and hardware-based attacks targetting at the weights of the DNN have been introduced allowing potential attacker to gain access to a near-perfect copy of the victim's model. However, these attacks either fail against more complex[…]-
SemSecuElec
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Side-channel
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Machine learning
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