TY - JOUR
T1 - SecureCPS
T2 - Cognitive inspired framework for detection of cyber attacks in cyber–physical systems
AU - Makkar, Aaisha
AU - Park, Jong Hyuk
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/5
Y1 - 2022/5
N2 - In the era of autonomous systems, the security is indispensable module for flexible computing environment. Due to increased computer power and network speed, a new computing paradigm, such as cognitive inspired computing, will emerge. Such a paradigm provides human-centered services that are convenient and enjoyable at any time, anywhere, and on any device. On the foundation of smart city environment, human computer interaction, intelligent services, and universal device connectivity, Cyber Physical Computing for Cyber Physical systems has recently been investigated. However, in this proposal, a cognitive inspired framework for securing CPS is scrutinized. The cognitive ability is conceded to the search engines by updating the PageRank ranking methodology. The proposed framework, named SecureCPS is trained with real time collective dataset for marking the relevancy of web page with the support the facial expressions. The eye regions are marked using Focal Point Detector algorithm. The framework is validated with machine learning models and resulted in achieving 98.51% accuracy and its outperforms the existing frameworks.
AB - In the era of autonomous systems, the security is indispensable module for flexible computing environment. Due to increased computer power and network speed, a new computing paradigm, such as cognitive inspired computing, will emerge. Such a paradigm provides human-centered services that are convenient and enjoyable at any time, anywhere, and on any device. On the foundation of smart city environment, human computer interaction, intelligent services, and universal device connectivity, Cyber Physical Computing for Cyber Physical systems has recently been investigated. However, in this proposal, a cognitive inspired framework for securing CPS is scrutinized. The cognitive ability is conceded to the search engines by updating the PageRank ranking methodology. The proposed framework, named SecureCPS is trained with real time collective dataset for marking the relevancy of web page with the support the facial expressions. The eye regions are marked using Focal Point Detector algorithm. The framework is validated with machine learning models and resulted in achieving 98.51% accuracy and its outperforms the existing frameworks.
KW - Artificial intelligence
KW - Cognitive sciences
KW - Cognitive-inspired
KW - Cyber physical systems
KW - Machine learning
UR - http://www.scopus.com/inward/record.url?scp=85126917943&partnerID=8YFLogxK
U2 - 10.1016/j.ipm.2022.102914
DO - 10.1016/j.ipm.2022.102914
M3 - Article
AN - SCOPUS:85126917943
SN - 0306-4573
VL - 59
JO - Information Processing and Management
JF - Information Processing and Management
IS - 3
M1 - 102914
ER -