Joseph, Asha, George, Shiju, and Shatte, Adrian (2026) Quantum-Driven Digital Forensics: Evidence Acquisition, Intrusion Detection, Cybercrime Simulation, and DNA Profiling. In: Lecture Notes in Networks and Systems (1928) pp. 102-115. From: SCIS 2025: International Conference on Sustainable Computing and Intelligent Systems, 7-8 November 2025, Canberra, ACT, Australia.

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Abstract

Quantum computing introduces a new paradigm in digital forensics by enabling faster cryptographic analysis, enhanced machine learning, and secure data acquisition. This research examines the potential to apply quantum computing to forensics and how it can be used to transform the field through its disruptive capabilities in the evidence collection process, detection of intrusions, modeling of cybercrime, and DNA analysis. It also underrates the dangers that quantum technologies bring to the data security and the urgency of post-quantum encryption technologies. The article presents a blueprint of quantum-driven forensic investigation of the near future by conducting a survey of recent advances and new applications. We combine theory and practice by using datasets such as NSL-KDD, Qiskit simulations, and diagrams of how quantum machine learning models, DNA profiling and intrusion detection systems are used. Pattern matching in the DNA profiling algorithm with quantum computing is determined to have a time complexity of O(n) in the application of the Grover algorithm and O(n) of the corresponding classical algorithm.

Item ID:	92415
Item Type:	Conference Item (Research - E1)
ISBN:	978-3-032-22914-4
ISSN:	23673370
Keywords:	block chain security, Digital Forensics, DNA profiling, Post Quantum Cryptography, Quantum computing, Quantum machine learning
Copyright Information:	© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2026
Date Deposited:	23 Jun 2026 23:18
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