Future connected and autonomous vehicles (CAVs) must be secured against cyberattacks
for their everyday functions on the road so that safety of passengers and vehicles can be …

Today's world is highly network interconnected owing to the pervasiveness of small personal
devices (eg, smartphones) as well as large computing devices or services (eg, cloud …

Although the fifth generation (5G) wireless networks are yet to be fully investigated, the
visionaries of the 6th generation (6G) echo systems have already come into the discussion …

Deep learning models have achieved great success in solving a variety of natural language
processing (NLP) problems. An ever-growing body of research, however, illustrates the …

Abstract Adversarial Machine Learning (AML) is a recently introduced technique, aiming to
deceive Machine Learning (ML) models by providing falsified inputs to render those models …

As cybersecurity detectors increasingly rely on machine learning mechanisms, attacks to
these defenses escalate as well. Supervised classifiers are prone to adversarial evasion …

Cyber-security issues on adversarial attacks are actively studied in the field of computer
vision with the camera as the main sensor source to obtain the input image or video data …

Variable binding is a cornerstone of symbolic reasoning and cognition. But how binding can
be implemented in connectionist models has puzzled neuroscientists, cognitive …

Malware programs currently represent the most serious threat to computer information
systems. Despite the performed efforts of researchers in this field, detection tools still have …

Recent studies show that deep person re-identification (re-ID) models are vulnerable to
adversarial examples, so it is critical to improving the robustness of re-ID models against …