Guest Editors
Dr. Carlos Enrique Montenegro Marin, District University Francisco José de Caldas, Colombia
Dr. Paulo Alonso Gaona Garcia, District University Francisco José de Caldas, Colombia
Dr. Edward Rolando Nuñez Valdez, University of Oviedo, Spain
Summary
Cyber-physical systems (CPS) can benefit various applications such as smart homes, healthcare, smart transportation, etc. It is an integration of physical and logical systems to comprise interaction between digital, analog, and human components. In the current scenario, CPS plays a vital role across emerging technical requirements and act as an establishment factor for various applications such as the Internet of Things (IoT), Industrial Internet of Things (IIoT), smart cities, industrial internet, smart grid, and several other smart systems (e.g., cars, building, parking, home, etc.). In simple terms, CPS enables complex interaction between various digital and analogous components across the cyberspace. This leads to various intentional and accidental threats across the network enabling increased difficulty with behavior prediction processes (normal or faulty system behavior). Further, the rapid advancement of modern techniques attracts governments, industries, and economies to highly rely on CPS which increases the chance of vulnerable cyberattacks. The above-mentioned factors greatly determine the risk of cyber-attacks across the cyber-physical systems. Besides, the traditional cybersecurity mechanisms such as access control and intrusion detection systems become obsolete, when applied towards modern CPS. This creates the requirement of advanced security measures for CPS.
Cognitive machine intelligence (CMI) is the branch of artificial intelligence (AI) designed to protect threats across CPS using pre-defined patterns formulated from human thoughts. It incorporates human behavior with a high powered computer model with the help of various machine learning techniques such as data mining, pattern recognition, and natural language processing algorithms. CMI makes use of advanced data analytics techniques through which it constantly mines data and acquires significant information. Patterns are generated using the acquired information that anticipates threats and provides proactive solutions for CPS. Further, CMI possesses the capability to process and analyze a huge amount of structured and unstructured data. This makes its applications inevitable for CPS. In particular, this approach is most significant to deal with cyberattacks that manipulate human perception. Thus, the combination CMI with CPS forms an effective CPS security solution.
This special issue targets to bring researchers from academic and industrial backgrounds to share their views on the secure cyber-physical system in the context of cognitive machine intelligence.
The topic of interest includes, but not limited to the following:
• Design and development of efficient architectures for future generation computing systems with cognitive machine intelligence and cyber-physical systems
• Safety and security protocols with cognitive machine intelligence for cyber-physical systems
• Role of ethical computational intelligence in knowledge discovery and pattern recognition across real-time cyber-physical systems
• Advances in cognitive computing for human behavior analysis and threat detection across cyber-physical systems
• Cognitive machine intelligence for multi-sensor data fusion in cyber-physical system applications (healthcare, transportation, etc.)
• Role of cognitive machine intelligence for Internet of Things and cyber-physical system security
• Reinforcement and transfer learning for cyber-physical systems
• Computational intelligence methodologies for design and development of authentication and access control algorithms across blockchain-enabled cyber-physical systems
• Performance optimization of cyber-physical systems with cognitive machine intelligence algorithms
• Cyber-attacks modeling in cyber-physical systems with cognitive machine intelligence algorithms
• Cryptographic engineering with cognitive machine intelligence for smart cyber-physical systems
Keywords
Computational intelligence, cyber-physical systems, Cognitive machine intelligence, Threats
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