Results 61 to 70 of about 8,384 (195)

Towards Trust Hardware Deployment of Edge Computing: Mitigation of Hardware Trojans Based on Evolvable Hardware

Applied Sciences, 2022
Hardware Trojans (HTs) are malicious hardware components designed to leak confidential information or cause the chip/circuit on which they are integrated to malfunction during operation.
Zeyu Li, Junjie Wang, Zhao Huang, Nan Luo, Quan Wang   +4 more
doaj   +1 more source

A New Paradigm in Split Manufacturing: Lock the FEOL, Unlock at the BEOL

, 2019
Split manufacturing was introduced as an effective countermeasure against hardware-level threats such as IP piracy, overbuilding, and insertion of hardware Trojans.
Knechtel, Johann, Nabeel, Mohammed, Sengupta, Abhrajit, Sinanoglu, Ozgur   +3 more
core   +1 more source

Security Challenges and Solutions in Self‐Driving Vehicles: A Comprehensive Review

IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.
This article presents a comprehensive review of cybersecurity challenges and solutions in self‐driving vehicles, focusing on threats across vehicular communication, sensors, artificial intelligence (AI) systems, and data privacy. It categorises attacks based on autonomous vehicle architecture layers and highlights advanced countermeasures such as AI ...
Yaw Opoku Mensah Sekyere, Priscilla Ajiboye Oyelandun, Francis Boafo Effah   +2 more
wiley   +1 more source

Cybersecurity Driven Quantum Digital Twin for Proactive Threat Reversal in Open RAN

IET Quantum Communication, Volume 7, Issue 1, January/December 2026.
This paper presents a novel cybersecurity‐driven quantum digital twin (CQDT) architecture for proactive defence in 6G Open RAN. By integrating quantum observables and reinforcement learning, the framework maintains high fidelity and suppresses entropy under adversarial CPTP noise. CQDT achieves real‐time adaptation with sub‐20 ms latency, meeting URLLC
Yassir Al‐Karawi, Raad S. Alhumaima, Hamed Al‐Raweshidy   +2 more
wiley   +1 more source

A Novel Two-Level Protection Scheme against Hardware Trojans on a Reconfigurable CNN Accelerator

Cryptography
With the boom in artificial intelligence (AI), numerous reconfigurable convolution neural network (CNN) accelerators have emerged within both industry and academia, aiming to enhance AI computing capabilities.
Zichu Liu, Jia Hou, Jianfei Wang, Chen Yang   +3 more
doaj   +1 more source

Spartan Daily September 9, 2009 [PDF]

, 2009
Volume 133, Issue 7https://scholarworks.sjsu.edu/spartandaily/1276/thumbnail ...
San Jose State University, School of Journalism and Mass Communications
core   +2 more sources

Resisting Quantum Key Distribution Attacks Using Quantum Machine Learning

IET Quantum Communication, Volume 7, Issue 1, January/December 2026.
Quantum key distribution (QKD) promises secure communication but remains vulnerable to advanced quantum attacks. We propose a hybrid quantum long short‐term memory (QLSTM) model that combines quantum‐enhanced learning with classical deep learning to detect attacks such as photon‐number splitting, Trojan‐Horse and detector blinding.
Ali Al‐Kuwari, Noureldin Mohamed, Saif Al‐Kuwari, Ahmed Farouk, Bikash K. Behera   +4 more
wiley   +1 more source

Quantum Key Distribution Networks Design: Overview and Challenges

IET Quantum Communication, Volume 7, Issue 1, January/December 2026.
This paper explores the potential of using established QKD network design techniques in the context of quantum key distribution, which is based on the principles of quantum mechanics. ABSTRACT Quantum cryptography has increasingly attracted interest from both industry and academia for its potential in real‐world applications.
Pankaj Kumar, Neel Kanth Kundu, Binayak Kar   +2 more
wiley   +1 more source

Device‐Independent Quantum Key Distribution: Protocols, Quantum Games and Security

IET Quantum Communication, Volume 7, Issue 1, January/December 2026.
Device‐independent quantum key distribution (DIQKD) removes the need to trust internal device behaviour by certifying security through Bell‐inequality violations, thereby closing practical loopholes in conventional QKD. This paper systematically reviews DIQKD foundations (Bell tests and security definitions), protocol frameworks (CHSH‐based and ...
Syed M. Arslan, Saif Al‐Kuwari, M. T. Rahim, Hashir Kuniyil   +3 more
wiley   +1 more source

AI‐Powered Defense: Leveraging Deep Learning for Effective Malware Detection

Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.
Traditional malware detection techniques frequently fail to detect and stop malicious activity in an era where cyber threats are becoming more complex. Any software that enters a computer system without the administrator’s consent is considered malicious software.
Nancy Awadallah Awad, Dimitrios A. Karras   +1 more
wiley   +1 more source