MSD: Multi-stage deception for data privacy protection - Tamer Abdel Latif Ali; Mostafa M. Elsherbini (PLoS ONE, 2025)
With the exponential growth of electronically transmitted and stored data, ensuring data privacy and security has become a fundamental challenge for organizations and enterprises. Traditional encryption methods have limitations, such as vulnerability to advanced attacks and high computational complexity, that lead to the exploration of complementary strategies like deception techniques for enhanced protection. These methods aim to mislead unauthorized users by presenting protected data as if it were authentic, but the attack resilience is still insufficient. Multi-stage deception (MSD) methods leverage multiple deception strategies, such as complement, swapping, and stack reversal, to improve data protection levels and resistance against decryption attempts. Combining these techniques addresses gaps in single-stage approaches and offers a more robust defense. The proposed MSD method incorporates a classification of encryption and deception techniques and introduces a novel evaluation approach targeting critical performance factors. A tailored pseudocode algorithm is designed to optimize deception for various attribute types, validated through simulations. Simulation results reveal that the MSD method achieves a 100% value change in the first stage and 92% in the second stage, with an overall accuracy exceeding 95%. These findings demonstrate the method’s effectiveness in elevating data protection levels while maintaining low computational complexity. The study highlights the potential of multi-stage deception as a powerful tool for safeguarding sensitive information, achieving superior performance in data security. By offering a scalable and adaptable framework, the MSD method addresses emerging challenges in data protection while setting the stage for further advancements.