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- W4214689945 abstract "Technological advancement in the recent decades enhanced the calibre of human life. Contemporary research in machine learning (ML) exhibits a mock-up to make decisions on its own and is applied in various fields including medical diagnosis, email filtering, banking, computer vision, financial marketing, image processing, cyber security. The systems inter-connected across the world via internet are attacked by hackers, and it is prevented by cyber security. The optimum solution for cyber-attacks is attained by collaborating ML techniques with cyber security and envisioned issues are designed by cyber machine learning models. In this chapter, an algorithm is proposed to defend data by encoding the text to an unintelligent text and decoding it to original text by applying graph labelling in cryptography. Symmetric key is designed based on the edge label of an odd-even congruence graph to achieve secured communication in CPS. In addition, a program is suggested using Python programming to attain cipher text and its converse." @default.
- W4214689945 created "2022-03-02" @default.
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- W4214689945 date "2022-01-01" @default.
- W4214689945 modified "2023-10-17" @default.
- W4214689945 title "Application of Odd-Even Congruence Graph Labeling in Secured Cyber Physical Systems" @default.
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- W4214689945 doi "https://doi.org/10.4018/978-1-7998-9308-0.ch006" @default.
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