Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.
The authors have designed a platform for research and consulting through a high-level collaborative seminar series to promote networking in proactive artificial intelligence (AI) for cybersecurity (SPAIC). The primary objective is to cover a wide range of techniques in cyber threat intelligence gathering from various social media to dark-net and deep-net, hacker forum discussions, and malicious hacking. The secondary objective is to bring together researchers and consultants in the field to come up with automated and advanced methods of attack vector recognition and isolation using AI and machine learning (ML). In most cases, the hidden nature of security issues makes it hard for fixes in real time. Advanced AI techniques have proven to be superior to the current static methods in cyber threat detection. There have been numerous recent advances in the field of AI, especially in algorithmic approaches such as Speech and Signal Processing, Machine and Deep Learning, Computer Vision, Robotics, Data Mining, Augmented/Virtual Reality, Blockchain, and Cognitive Computing. These highly advanced methods provide tremendous opportunities for behavior/trend based automated analysis, detection, and prevention of cyber attacks/threats. In addition to the potential of development of concepts and whitepapers for a large-scale center, the seminar series will result in identification and recruitment of industrial, academic and/or government partnerships in support of initiatives and research and consulting collaborations as well as creation and support of resources such as research consortia, collaboration sites or social networking tools to facilitate large-scale inter-university research programs in AI and ML in cybersecurity.
