Comparative Security Analysis of Password Recovery in PDF and Compressed File Formats - Narendar, Dharavath; G, Padmavathi; K, Gangadhara Rao; Nalla, Venu (International Journal of Computer Sciences and Engineering, 2025)
Password protection in widely used file formats such as PDF, ZIP, and RAR is a key mechanism for securing sensitive digital data. While these formats implement strong encryption algorithms, including AES and key derivation functions like PBKDF2, practical security often hinges on the strength of user-chosen passwords, which are frequently weak or predictable. This study provides a comprehensive comparative analysis of password recovery techniques, encompassing conventional methods, brute force, dictionary-based, and rule-based approaches, and AI/ML-assisted strategies, including Markov chains, probabilistic context-free grammar (PCFG), and recurrent neural networks (RNNs). Experiments were performed on CPU-based systems using John the Ripper and Hashcat, evaluating performance across varying password lengths, character sets, and encryption schemes. The results demonstrate that weakly encrypted ZIP files are recovered almost instantly, whereas RAR archives employing PBKDF2-HMAC-SHA256 show substantially higher resistance. PDF files remain vulnerable to short passwords despite AES-256 encryption. Rule-based strategies consistently reduce recovery time compared to brute- force methods, while AI-assisted approaches produce realistic password candidates that closely mimic human password behavior, further enhancing efficiency. The findings underscore that practical security depends more on password quality than on cryptographic strength. This analysis offers actionable insights for security auditing, the enforcement of password policies, and the design of more resilient authentication mechanisms. Future work will explore GPU-accelerated recovery using CUDA frameworks and investigate the implications of quantum computing on large-scale password cracking, providing guidance for addressing emerging digital security challenges.