Blockchain-Enabled Hash-Based Collusion Attack Detection and Prevention Using Redundant Hidden Tracking Software

Abstract

Collusion attacks at the data transmission stage represent one of the most severe threats to data integrity, as two or more malicious entities can jointly modify or manipulate sensitive information in transit. Such attacks are particularly critical in high-stakes environments like financial transactions, share markets, healthcare records or secure government communications, where even minor alterations can lead to catastrophic consequences. This research proposes a robust, multi-layered security framework that leverages blockchain technology, hashing techniques, and redundant hidden tracking software to detect, prevent and mitigate collusion attacks. In the proposed model, every data packet transmitted is backed up both online and offline, with cryptographic hashing applied for integrity verification at every stage of transmission. Blockchain serves as a tamper-resistant ledger, maintaining immutable records of transmitted data and counting the number of modifications attempted. This enables a real-time comparison between the transmitted data and the backup data stored in the blockchain ledger. In addition to cryptographic verification, two or more covert software modules act as hidden trackers, operating independently and periodically altering their communication patterns to remain undetectable to attackers. These modules monitor data transmission activities, verify changes with data owners, and restore original data from backup if unauthorized modifications occur. This dual-layer strategy of cryptographic assurance combined with covert surveillance ensures strong fault tolerance, high data security and uninterrupted protection even if one software module is compromised. The proposed framework is designed to function seamlessly across online and offline states, providing continuous security assurance and real-time alerts of anomalies, thereby significantly reducing the risks posed by collusion attacks.