A lightweight model design approach for few-shot malicious traffic classification. [PDF]
Sci RepWang R +6 more
europepmc +1 more source
Tackling Hardware Trojans via Hardware-based Methodologies
Hardware Trojans (HTs) represent significant challenges to the security and reliability of modern microprocessorbased systems. This manuscript introduces two complementary approaches to enhance hardware security. First, programmable Hardware Security Modules are proposed to detect Hardware Trojan Horses by monitoring instruction-fetch activities ...
openaire +1 more source
Advancing Machine Learning Strategies for Power Consumption-Based IoT Botnet Detection. [PDF]
Sensors (Basel)Wakili AA +4 more
europepmc +1 more source
Improving malware detection performance using hybrid deep representation learning with heuristic search algorithms. [PDF]
Sci RepAnuradha A, Chouhan AS, Srinivas Rao S.
europepmc +1 more source
BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices. [PDF]
PeerJ Comput SciŞafak E +3 more
europepmc +1 more source
A hierarchical deep learning framework with doubly regularized loss for robust malware detection and family categorization. [PDF]
Sci RepAbed Alsaedi S +6 more
europepmc +1 more source
Tackling Hardware Trojan Horses via Hardware-based Methodologies
Hardware-based approaches to detect bit-flips, unauthorized program runs, and tampering.
openaire +1 more source
BioTrojans: viscoelastic microvalve-based attacks in flow-based microfluidic biochips and their countermeasures. [PDF]
Sci RepBaban NS +8 more
europepmc +1 more source
Mobile malware detection method using improved GhostNetV2 with image enhancement technique. [PDF]
Sci RepDu Y +5 more
europepmc +1 more source