CYBER SECURITY STRATEGY CALCULATION THROUGH INTEGRATED MACHINE LEARNING AND MULTI-CRITERIA DECISION METHODS (CAHIERS MAGELLANES-NS, 2024)
Objectives: To identify the shortcomings of the Information Technology Act-2000 and recommend measures to strengthen its applicability against emerging forms of cybercrime while fostering development and protecting constitutional rights. Methods: Here MULTIMOORA methodology for multi-criteria decision making is employed on the proposed changes to the IT Act. The historical data on previous changes was evaluated using the Random Forest technique to forecast the anticipated usefulness of further amendments in terms of their efficiency, cost, and integration with other countries. Findings: The proposed methodology suggested amendments that are meant to build India’s cyber legislation to the required standard while also strengthening the country’s defense against AI driven and crypto-jacking attacks. The use of RF algorithm shows the effects of these factors on the success or otherwise of the amendments. The findings underline the need for international collaboration, cost efficiency and efficacy in developing the new laws. These new laws are expected to advance the existing digital governance processes in India. Novelty: The study is distinct as it employs machine learning in the analysis and integrates it with multi-criteria models to analyze the factors affecting it, which reduces the time complexity and enhances the overall throughput.Keywords: Cybercrime, Law Enforcement, Cyber-Disaster Management, MOORA (Multi-Objective Optimization based on a Ratio Analysis).