Results 1 to 10 of about 5,994 (219)

Robust hardware Trojan detection leveraging dual-domain features and stacked ensemble learning

Cybersecurity
Cyber-physical systems rely on sensors, communication, and computing, all powered by integrated circuits (ICs). These ICs are vulnerable to malicious hardware attacks, with hardware Trojans being one of the stealthiest threats.
Sefatun-Noor Puspa, Abyad Enan, Reek Majumder, M Sabbir Salek, Gurcan Comert, Mashrur Chowdhury   +5 more
doaj   +1 more source

Backdoor Attacks to Deep Neural Networks: A Survey of the Literature, Challenges, and Future Research Directions

IEEE Access
Deep neural network (DNN) classifiers are potent instruments that can be used in various security-sensitive applications. Nonetheless, they are vulnerable to certain attacks that impede or distort their learning process.
Orson Mengara, Anderson Avila, Tiago H. Falk   +2 more
doaj   +1 more source

Defense of hidden backdoor technology for Web

Dianxin kexue, 2020
Rootkit is a set of persistent and undetectable attack technologies,which can hide their attack behavior and backdoor trace by modifying software or kernel in operating system and changing execution path of instruction.Firstly,the basic definition and ...
Liyue CHEN, Xin SUN, Tiansheng CHENG, Chunming WU, Shuangxi CHEN   +4 more
doaj  

System-level protection and hardware Trojan detection using weighted voting. [PDF]

J Adv Res, 2014
Amin HA, Alkabani Y, Selim GM.
europepmc   +1 more source

Dataset for hardware Trojan detection

, 2022
Nowadays, cloud services rely extensively on the use of virtual machines to enforce security by isolation. However, hardware trojan attacks break this assumption. Within these attacks, cache side-channel attacks such as Spectre and Meltdown are the focus of this work.
openaire   +1 more source

A framework for hardware trojan detection based on contrastive learning. [PDF]

Sci Rep
Jiang Z, Ding Q.
europepmc   +1 more source

A Siamese deep learning framework for efficient hardware Trojan detection using power side-channel data. [PDF]

Sci Rep
Nasr A, Mohamed K, Elshenawy A, Zaki M.
europepmc   +1 more source

Nature-Inspired Trojan Materials as Invisible Enablers of Advanced Humidity Sensors. [PDF]

Materials (Basel)
Oliveira DS, Vieira ES, Martins GV, Costa JJ, Meira RM, Ramos CA, Campanhã D, Vilão G, Alves J, Santos PF, Moreira FTC.   +10 more
europepmc   +1 more source

Comprehensive methylome and transcriptome profiling reveals specific biomarkers for bovine viral diarrhea virus persistent infection in calves. [PDF]

Front Immunol
Wang J, Chen S, Lai W, Feng X, Zhao Q, Mi S, Xu C, Qin T, Cao J, Yu Y.   +9 more
europepmc   +1 more source

TCF-CBM: a three-stage collaborative poisoned sample filtering method based on composite backdoor mechanism. [PDF]

Sci Rep
Huang W, Gui W, Chen Y, Chen G, Lv Q, Du Z.   +5 more
europepmc   +1 more source