Singapore Institute of Technology
Browse

File(s) stored somewhere else

Please note: Linked content is NOT stored on Singapore Institute of Technology and we can't guarantee its availability, quality, security or accept any liability.

PIC: Preserving Data Integrity in UAV Assisted Communication

conference contribution
posted on 2023-10-03, 09:13 authored by Venkata Abhishek NalamVenkata Abhishek Nalam, Muhammad Naveed Aman, Teng Joon Lim, Biplab Sikdar

The use of unmanned aerial vehicles (UAVs) for diverse activities has increased rapidly in recent years. Nonetheless, if operational cyber security is not handled effectively, these technologies offer a significant hazard which can cause catas-trophic harm. Therefore it is important to identify the potential attacks that can be implemented by an adversary. Traditional methods for data integrity designed for the Internet are not suitable for UAV assisted vehicular or wireless sensor networks due to the high communication overhead and latency required. This paper proposes a lightweight data integrity technique called PIC to address this problem. Every device, at regular intervals, generates an authentication parameter that depends on the packets transmitted. The authentication parameters are only delivered to a central server or the destination device where the integrity of the packets is verified. The proposed algorithm, i.e., PIC, does not include computationally expensive cryptographic algorithms. Therefore, the overhead introduced by embedding message authentication code (MAC) to every transmitted packet is significantly reduced. A formal security proof is presented in this paper to demonstrate the robustness of PIC, i.e., the PIC can identify malicious UAVs effectively. A performance analysis using NS-3 is also presented to show that PIC detects malicious UAVs with minimum communication overhead and latency.

History

Journal/Conference/Book title

IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 02-05 May 2022

Publication date

2022-05-02

Usage metrics

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC