Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Khalid, Faiq"'
The global semiconductor supply chain involves design and fabrication at various locations, which leads to multiple security vulnerabilities, e.g., Hardware Trojan (HT) insertion. Although most HTs target digital circuits, HTs can be inserted in anal
Externí odkaz:
http://arxiv.org/abs/2310.03994
Autor:
Ahmadi, Mahya Morid, Khalid, Faiq, Vaidya, Radha, Kriebel, Florian, Steininger, Andreas, Shafique, Muhammad
Dynamic partial reconfiguration enables multi-tenancy in cloud-based FPGAs, which presents security challenges for tenants, IPs, and data. Malicious users can exploit FPGAs for remote side-channel attacks (SCAs), and shared on-chip resources can be u
Externí odkaz:
http://arxiv.org/abs/2303.06486
Autor:
KHALID, FAIQ HASSAN1 frana82@gmail.com, AHMED, NAEEM2 naeem@uok.edu.pk
Publikováno v:
Janus.Net: e-Journal of International Relations. May-Oct2024, Vol. 15 Issue 1, p3-20. 18p.
The traditional convolution neural networks (CNN) have several drawbacks like the Picasso effect and the loss of information by the pooling layer. The Capsule network (CapsNet) was proposed to address these challenges because its architecture can enc
Externí odkaz:
http://arxiv.org/abs/2109.11041
Side-channel attacks on microprocessors, like the RISC-V, exhibit security vulnerabilities that lead to several design challenges. Hence, it is imperative to study and analyze these security vulnerabilities comprehensively. In this paper, we present
Externí odkaz:
http://arxiv.org/abs/2106.08877
Publikováno v:
IEEE Access, vol. 9, pp. 115370-115387, 2021
To reduce the time-to-market and access to state-of-the-art techniques, CNN hardware mapping and deployment on embedded accelerators are often outsourced to untrusted third parties, which is going to be more prevalent in futuristic artificial intelli
Externí odkaz:
http://arxiv.org/abs/2106.06895
From tiny pacemaker chips to aircraft collision avoidance systems, the state-of-the-art Cyber-Physical Systems (CPS) have increasingly started to rely on Deep Neural Networks (DNNs). However, as concluded in various studies, DNNs are highly susceptib
Externí odkaz:
http://arxiv.org/abs/2105.03251
Autor:
Alrahis, Lilas, Patnaik, Satwik, Khalid, Faiq, Hanif, Muhammad Abdullah, Saleh, Hani, Shafique, Muhammad, Sinanoglu, Ozgur
In this paper, we propose GNNUnlock, the first-of-its-kind oracle-less machine learning-based attack on provably secure logic locking that can identify any desired protection logic without focusing on a specific syntactic topology. The key is to leve
Externí odkaz:
http://arxiv.org/abs/2012.05948
Publikováno v:
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ( Volume: 39, Issue: 11, Nov. 2020)
Traditional learning-based approaches for run-time Hardware Trojan detection require complex and expensive on-chip data acquisition frameworks and thus incur high area and power overhead. To address these challenges, we propose to leverage the power
Externí odkaz:
http://arxiv.org/abs/2011.11632
Autor:
Naseer, Mahum, Minhas, Mishal Fatima, Khalid, Faiq, Hanif, Muhammad Abdullah, Hasan, Osman, Shafique, Muhammad
With a constant improvement in the network architectures and training methodologies, Neural Networks (NNs) are increasingly being deployed in real-world Machine Learning systems. However, despite their impressive performance on "known inputs", these
Externí odkaz:
http://arxiv.org/abs/1912.01978