Peer-reviewed work.

The growing dependence on third-party foundries for integrated circuit (IC) fabrication has created major security concerns because of hardware Trojan (HT) insertion risks.

Anomaly detection is a cornerstone of modern intelligent systems, with critical applications in healthcare, cybersecurity, smart grids, and IoT environments.

Ensuring the security of critical infrastructure has become increasingly vital with the proliferation of Internet of Things (IoT) systems. However, the heterogeneous nature of IoT data and the lack of human-comprehensible insights from anomaly detection models remain significant challenges.

With the rapid growth of IoT devices, ensuring robust network security has become a critical challenge. Traditional intrusion detection systems (IDSs) often face limitations in detecting sophisticated attacks within high-dimensional and complex data environments.

Reverse engineering process serves essential functions in software analysis and security auditing and malware detection but requires significant time and effort. Researchers and practitioners now investigate how Artificial Intelligence (AI) technology can automate and improve different reverse engineering procedures.

Hardware Trojans are deliberate malicious hardware modifications inserted in semiconductor Integrated Circuits (ICs) for the purpose of stealing or leaking sensitive information, as well as disrupting critical systems upon activation.

Drug discovery, which aids to identify potential novel treatments, entails a broad range of fields of science, including chemistry, pharmacology, and biology. In the early stages of drug development, predicting drug-target affinity is crucial.