Enhancing ransomware defense: deep learning-based detection and family-wise classification of evolving threats. [PDF]
Hussain A +4 more
europepmc +1 more source
A Survey on ML Techniques for Multi-Platform Malware Detection: Securing PC, Mobile Devices, IoT, and Cloud Environments. [PDF]
Ferdous J +3 more
europepmc +1 more source
Surgical revision in the presence of an S. aureus infection increases virulence factor expression and activates a multi-tissue inflammatory response. [PDF]
Smith CJ +10 more
europepmc +1 more source
RNN-based detection of IoT malware using diverse feature engineering methods. [PDF]
Abd-Ellah MK +3 more
europepmc +1 more source
A high performance hybrid LSTM CNN secure architecture for IoT environments using deep learning. [PDF]
Sinha P +5 more
europepmc +1 more source
Novel Multi-Classification Dynamic Detection Model for Android Malware Based on Improved Zebra Optimization Algorithm and LightGBM. [PDF]
Zhou S, Li H, Fu X, Han D, He X.
europepmc +1 more source
Threats and vulnerabilities in artificial intelligence and agentic AI models. [PDF]
Radanliev P, Santos O, Maple C.
europepmc +1 more source
Real-world case studies for a process-aware IDS. [PDF]
Menzel V, Hurink J, Remke A.
europepmc +1 more source
Emerging trend of outsourcing the design and fabrication services to external facilities as well as increasing reliance on third-party Intellectual Property (IP) cores and electronic design automation tools makes integrated circuits (ICs) increasingly vulnerable to hardware Trojan attacks at different stages of its life-cycle.
Seetharam Narasimhan, Swarup Bhunia
openaire +3 more sources
Hardware Trojan detection via rewriting logic
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Irina Mariuca Asavoae +3 more
openaire +3 more sources

