Challenges and opportunities of security-aware EDA
J Feldtkeller, P Sasdrich, T Güneysu - ACM Transactions on Embedded …, 2023 - dl.acm.org
The foundation of every digital system is based on hardware in which security, as a core
service of many applications, should be deeply embedded. Unfortunately, the knowledge of …
service of many applications, should be deeply embedded. Unfortunately, the knowledge of …
Overview of Mobile Attack Detection and Prevention Techniques Using Machine Learning.
AK Al Hwaitat, HN Fakhouri… - … of Interactive Mobile …, 2024 - search.ebscohost.com
In light of the increasing sophistication and frequency of mobile attacks, there is a growing
demand for advanced intelligent techniques capable of offering comprehensive mobile …
demand for advanced intelligent techniques capable of offering comprehensive mobile …
Uncertainty-Aware Hardware Trojan Detection Using Multimodal Deep Learning
R Vishwakarma, A Rezaei - 2024 Design, Automation & Test in …, 2024 - ieeexplore.ieee.org
The risk of hardware Trojans being inserted at various stages of chip production has
increased in a zero-trust fabless era. To counter this, various machine learning solutions …
increased in a zero-trust fabless era. To counter this, various machine learning solutions …
A Review of Artificial Intelligence Techniques for Improved Cloud and IoT Security
The current surge in interconnected devices, which includes the Internet of Things (IoT)
devices and the continually expanding cloud infrastructure, marks a new era of digital …
devices and the continually expanding cloud infrastructure, marks a new era of digital …
Power Analysis Side-Channel Attacks on Same and Cross-Device Settings: A Survey of Machine Learning Techniques
Abstract Systems that use secret keys or personal details are seriously at risk from side-
channel attacks, especially if they rely on power analysis. Attackers can use unintentional …
channel attacks, especially if they rely on power analysis. Attackers can use unintentional …
Parameter Extraction From Images Using Multilabel Supervised Learning
J Ezemba, JD Cunningham… - … and Information in …, 2023 - asmedigitalcollection.asme.org
In this work, we propose an approach to predict multiple design parameters of products
using 2D images and supervised learning techniques. Fully parametric 2D or 3D vector …
using 2D images and supervised learning techniques. Fully parametric 2D or 3D vector …
Establishing a Novel CAD-Based Paradigm for Design of VLSI Integrated Circuits
A Agarwal, MM Gour - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
This paper describes growing and enforcing a novel laptop-aided design (CAD) paradigm
for the format of Very-huge-Scale included (VLSI) circuits. This technique integrates the …
for the format of Very-huge-Scale included (VLSI) circuits. This technique integrates the …
[PDF][PDF] Genetic Algorithm for Functionally-Equivalent and Structurally-Divergent Benchmark Generation
A trending topic in nearly every field these days, including electronic design automation
(EDA) is machine learning (ML) and artificial intelligence (AI). However, to properly train and …
(EDA) is machine learning (ML) and artificial intelligence (AI). However, to properly train and …
[引用][C] Statistical methods for detecting recycled electronics: from ICs to PCBs and beyond
K Huang, Y Liu, N Korolija, JM Carulli… - IEEE Design & …, 2023 - ieeexplore.ieee.org
Statistical Methods for Detecting Recycled Electronics: From ICs to PCBs and Beyond Page 1 1
Detecting Recycled Electronics using Statistical Methods Statistical Methods for Detecting …
Detecting Recycled Electronics using Statistical Methods Statistical Methods for Detecting …