Machine intelligence security : A methodological blend of fuzzy logic in industry 4.0 algorithms
- Title
- Machine intelligence security : A methodological blend of fuzzy logic in industry 4.0 algorithms
- Creator
- Srilatha P.; Bendale S.P.; Singh M.; Chakole N.; Dhote G.M.; Shelke N.
- Description
- The way things are made has changed a lot because of Industry 4.0. It has also led to a time with great technology and relationships. The paper discusses way to improve security in Machine Intelligence in the setting of Industry 4.0. The study uses a mix of methods to combine Fuzzy Logic with cutting-edge Industry 4.0 algorithms in order to deal with new hacking problems. Because fuzzy logic can deal with doubt and imprecision, it can be used to make current methods more reliable. This creates a complex and flexible security structure. The merger was carefully planned to make the methods for finding anomalies, reducing threats, and responding to incidents work better. The suggested method aims to make machine intelligence systems more resistant to complex cyber dangers by combining the best parts of Fuzzy Logic with Industry 4.0 algorithms. This study adds to the growing conversation about how to keep smart factory settings safe by focusing on a proactive and dynamic security model. The effects of this mix of methods could be felt in many different industries, making it possible to use advanced technologies in a safer and more reliable way in the age of Industry 4.0. 2024, Taru Publications. All rights reserved.
- Source
- Journal of Discrete Mathematical Sciences and Cryptography, Vol-27, No. 2, pp. 689-701.
- Date
- 2024-01-01
- Publisher
- Taru Publications
- Subject
- Algorithms; Decision-making; Fuzzy logic; Intelligent security; Machine intelligence
- Coverage
- Srilatha P., Department of Artificial Intelligence and Data Science, Chaitanya Bharathi Institute of Technology, Telangana, Hyderabad, India; Bendale S.P., Department of Computer Engineering, NBN Sinhgad School of Engineering, Maharashtra, Pune, India; Singh M., School of Sciences, Christ (Deemed to be University), Karnataka, Bengaluru, India; Chakole N., Department of Electronics and Communication Engineering, Shri Ramdeobaba College of Engineering and Management, Maharashtra, Nagpur, India; Dhote G.M., Department of Mechanical Engineering, Yeshwantrao Chavan of Engineering, Maharashtra, Nagpur, India; Shelke N., Department of Computer Science & Engineering, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Nagpur Campus, Maharashtra, Pune, India
- Rights
- Restricted Access
- Relation
- ISSN: 9720529
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Srilatha P.; Bendale S.P.; Singh M.; Chakole N.; Dhote G.M.; Shelke N., “Machine intelligence security : A methodological blend of fuzzy logic in industry 4.0 algorithms,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/13245.