A Nano-Tagging–Based Framework for Secure Drone Evidence Handling

DOI

10.2991/978-94-6239-610-4_36How to use a DOI?

Keywords

Drone forensics; UAVs; Robustness; Nano-tagging; and Chain of custody

Abstract

With the rapid increase in drone usage for both legitimate and criminal activities, digital forensic analysts face growing challenges in preserving, authenticating, and verifying evidence collected from UAVs (Unmanned Aerial Vehicles)^[3][6]. By using drones as evidence, there can be many other challenges, such as components duplication (counterfeit or cloned parts), chain of custody vulnerabilities and legal governing limitations.^[3][6]

Existing forensic approaches towards UAVs (drones) are lacking in many ways such as the absence of material-level identification (physical markers), a weak chain of custody for physical components and insufficient anti-counterfeiting measures. These limitations significantly weaken attribution and evidentiary robustness in drone-related investigations.

By embedding forensic identity directly into drone components, nano-tagging addresses long-standing challenges related to attribution, chain of custody, and evidence integrity that remain unresolved in existing UAV forensic framework^[1][2]. As drones have digital markers that may crash after any incident, nano-tagging will help in embedding the physical identifiers (nanotags) in UAVs. It also assists in developing the device-level assumption to the component-level attribution. Besides that, nano-tagging aids in resistance to anti-forensic attacks, component manipulation and digital data integrity. Nanotags have physically unclonable features (impossible to duplicate)^[5]. Nanotags act as covert evidence in forensics^[1].

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Niharika Puri
AU  - Padigela Srinivas Reddy
PY  - 2026
DA  - 2026/05/05
TI  - A Nano-Tagging–Based Framework for Secure Drone Evidence Handling
BT  - Proceedings of the First International Conference on Advances in Forensics and Cyber Technologies (ICFACT 2025)
PB  - Atlantis Press
SP  - 418
EP  - 426
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-610-4_36
DO  - 10.2991/978-94-6239-610-4_36
ID  - Puri2026
ER  -