Zobrazeno 1 - 10
of 239
pro vyhledávání: '"Forte, Domenic"'
Autor:
Shishir, Fairuz Shadmani, Rizvee, Md Mashfiq, Hossain, Tanvir, Hoque, Tamzidul, Forte, Domenic, Shomaji, Sumaiya
Detecting counterfeit integrated circuits (ICs) in unreliable supply chains demands robust tracking and authentication. Physical Unclonable Functions (PUFs) offer unique IC identifiers, but noise undermines their utility. This study introduces the Pe
Externí odkaz:
http://arxiv.org/abs/2408.16950
Cryptosystem implementations often disclose information regarding a secret key due to correlations with side channels such as power consumption, timing variations, and electromagnetic emissions. Since power and EM channels can leak distinct informati
Externí odkaz:
http://arxiv.org/abs/2405.06571
The security of integrated circuits (ICs) can be broken by sophisticated physical attacks relying on failure analysis methods. Optical probing is one of the most prominent examples of such attacks, which can be accomplished in a matter of days, even
Externí odkaz:
http://arxiv.org/abs/2405.03632
Side-channel analysis has been proven effective at detecting hardware Trojans in integrated circuits (ICs). However, most detection techniques rely on large external probes and antennas for data collection and require a long measurement time to detec
Externí odkaz:
http://arxiv.org/abs/2401.12193
Physical side-channel attacks can compromise the security of integrated circuits. Most physical side-channel attacks (e.g., power or electromagnetic) exploit the dynamic behavior of a chip, typically manifesting as changes in current consumption or v
Externí odkaz:
http://arxiv.org/abs/2401.08925
Deploying machine learning-based intrusion detection systems (IDSs) on hardware devices is challenging due to their limited computational resources, power consumption, and network connectivity. Hence, there is a significant need for robust, deep lear
Externí odkaz:
http://arxiv.org/abs/2311.04194
The complexity of modern integrated circuits (ICs) necessitates collaboration between multiple distrusting parties, including thirdparty intellectual property (3PIP) vendors, design houses, CAD/EDA tool vendors, and foundries, which jeopardizes confi
Externí odkaz:
http://arxiv.org/abs/2208.03822
Recent work has highlighted the risks of intellectual property (IP) piracy of deep learning (DL) models from the side-channel leakage of DL hardware accelerators. In response, to provide side-channel leakage resiliency to DL hardware accelerators, se
Externí odkaz:
http://arxiv.org/abs/2208.03806
Autor:
Koblah, David Selasi, Acharya, Rabin Yu, Capecci, Daniel, Dizon-Paradis, Olivia P., Tajik, Shahin, Ganji, Fatemeh, Woodard, Damon L., Forte, Domenic
Artificial intelligence (AI) and machine learning (ML) techniques have been increasingly used in several fields to improve performance and the level of automation. In recent years, this use has exponentially increased due to the advancement of high-p
Externí odkaz:
http://arxiv.org/abs/2204.09579
Side-channel attacks extracting sensitive data from implementations have been considered a major threat to the security of cryptographic schemes. This has elevated the need for improved designs by embodying countermeasures, with masking being the mos
Externí odkaz:
http://arxiv.org/abs/2106.12714