[HTML][HTML] Machine learning-based zero-touch network and service management: A survey

J Gallego-Madrid, R Sanchez-Iborra, PM Ruiz… - Digital Communications …, 2022 - Elsevier
The exponential growth of mobile applications and services during the last years has
challenged the existing network infrastructures. Consequently, the arrival of multiple …

Hardware-assisted machine learning in resource-constrained IoT environments for security: review and future prospective

G Kornaros - IEEE Access, 2022 - ieeexplore.ieee.org
As the Internet of Things (IoT) technology advances, billions of multidisciplinary smart
devices act in concert, rarely requiring human intervention, posing significant challenges in …

Llm for soc security: A paradigm shift

D Saha, S Tarek, K Yahyaei, SK Saha, J Zhou… - IEEE …, 2024 - ieeexplore.ieee.org
As the ubiquity and complexity of system-on-chip (SoC) designs increase across electronic
devices, incorporating security into an SoC design flow poses significant challenges …

Gnn4tj: Graph neural networks for hardware trojan detection at register transfer level

R Yasaei, SY Yu, MA Al Faruque - 2021 Design, Automation & …, 2021 - ieeexplore.ieee.org
The time to market pressure and resource constraints has pushed System-on-Chip (SoC)
designers toward outsourcing the design and using third-party Intellectual Property (IP). It …

Brain-inspired golden chip free hardware trojan detection

S Faezi, R Yasaei, A Barua… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Since 2007, the use of side-channel measurements for detecting Hardware Trojan (HT) has
been extensively studied. However, the majority of works either rely on a golden chip, or …

A survey on hardware vulnerability analysis using machine learning

Z Pan, P Mishra - IEEE Access, 2022 - ieeexplore.ieee.org
Electronic systems rely on efficient hardware, popularly known as system-on-chip (SoC), to
support its core functionalities. A typical SoC consists of diverse components gathered from …

Hardware trojans in chips: A survey for detection and prevention

C Dong, Y Xu, X Liu, F Zhang, G He, Y Chen - Sensors, 2020 - mdpi.com
Diverse and wide-range applications of integrated circuits (ICs) and the development of
Cyber Physical System (CPS), more and more third-party manufacturers are involved in the …

Yamme: a yara-byte-signatures metamorphic mutation engine

A Coscia, V Dentamaro, S Galantucci… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Recognition of known malicious patterns through signature-based systems is unsuccessful
against malware for which no known signature exists to identify them. These include not only …

ReIGNN: State register identification using graph neural networks for circuit reverse engineering

SD Chowdhury, K Yang, P Nuzzo - 2021 IEEE/ACM …, 2021 - ieeexplore.ieee.org
Reverse engineering an integrated circuit netlist is a powerful tool to help detect malicious
logic and counteract design piracy. A critical challenge in this domain is the correct …

Contrastive graph convolutional networks for hardware Trojan detection in third party IP cores

N Muralidhar, A Zubair, N Weidler… - … Security and Trust …, 2021 - ieeexplore.ieee.org
The availability of wide-ranging third-party intellectual property (3PIP) cores enables
integrated circuit (IC) designers to focus on designing high-level features in ASICs/SoCs …