The cyber era heralded unparalleled opportunities for the advancement of science, technology and communication, and unleashed a range of new attack vectors for rogue elements, criminals and virtual terrorists. The era of machine learning is doing much the same, for the promise of advancement has gone hand in hand with a range of new perils and an expanded set of actors capable of carrying out attacks using artificial intelligence (AI) and machine learning systems. This flows naturally from the efficiency, scalability and ease of diffusion of AI systems, which can increase the number of actors who can carry out attacks against civilian, business and military targets.
While the debate about Artificial Intelligence (AI) and augmented reality rages, virtual terrorists—those who operate primarily on the Dark Web—are getting smarter and thinking of new ways to benefit from both, creating methods to operate autonomously in this brave new world. Malware is being designed with adaptive, success-based learning to improve the accuracy and efficacy of cyberattacks. The coming generation of malware will be situation-aware, meaning that it will understand the environment it is in and make calculated decisions about what to do next, behaving like a human attacker: performing reconnaissance, identifying targets, choosing methods of attack, and intelligently evading detection.