Security and privacy concerns in social networks mathematically modified metaheuristic-based approach

• Published in: Journal of discrete mathematical sciences & cryptography Vol. 27; no. 2-A; pp. 371 - 382
• Main Authors: Krishna, Raguru Jaya, Gopalakrishnan, T., Divyapushpalakshmi, M., Amarendra, K., Dadheech, Pankaj, Sengan, Sudhakar
• Format: Journal Article
• Language: English
• Published: 01.03.2024
• ISSN: 0972-0529; 2169-0065
• DOI: 10.47974/JDMSC-1892

Potential risks and vulnerabilities in Social Networks (SN) that may threaten the confidentiality, accuracy, and accessibility of data provided by users have been identified as safety risks. Unauthorized usage of the system, breaches of data, privacy violations, cyber-attacks, and other malicious behaviors that negatively impact the SN’s reliability and security may be addressed within these. Innovative techniques that use scientifically enhanced metaheuristic algorithms are the subject of the study, which attempts to address evolving issues of security and privacy in SNs. In order to improve the security of online social networking data encryption, researchers recommend implementing the MMCSOA approach, which is the Mathematically Modified Cuckoo Search Optimization Algorithm. An enhanced tuning of elliptic curve parameters can be accomplished by adapting the Cuckoo Search method, which, in consequence, provides an encrypted environment for multi-party computing. Users’ preferences for confidentiality are considered while applying a fuzzy logic (FL) decision matrix to select individuals. Data security is improved, and users receive additional authority over data shared with MMCSOA. Research findings prove that MMCSOA is higher compared to other methods in securing users’ privacy.