DroneSig: Lightweight Digital Signature Protocol for Micro Aerial Vehicles

Micro aerial vehicles a.k.a. drones, have become an integral part of a variety of civilian and military application domains, including but not limited to aerial surveying and mapping, aerial surveillance and security, aerial inspection of infrastructure, and aerial delivery. Meanwhile, the cybersecurity of drones is gaining significant attention due to both financial and strategic information and value involved in aerial applications. As a result of the lack of security features in the communication protocol, an adversary can easily interfere with on-going communications or even seize control of the drone. In this thesis, we propose a lightweight digital signature protocol, also referred to as DroneSig, to protect drones from a man-in-the-middle attack, where an adversary eavesdrops the communication between Ground Control Station (GCS) and drone, and impersonates the GCS and sends fake commands to terminate the on-going mission or even take control over the drone. The basic idea of the DroneSig is that the drone will only execute the new command after validating the received digital signature from the GCS, proving that the new command message is coming from the authenticated GCS. If the validation of the digital signature fails, the new command is rejected immediately, and the Return-to-Launch (RTL) mode is initiated and forces the drone to return to the take-off position. We conduct extensive simulation experiments for performance evaluation and comparison using OMNeT++, and simulation results show that the proposed lightweight digital signature protocol achieves better performance in terms of energy consumption and computation time compared to the standard Advanced Encryption Standard (AES) cryptographic technique

An Anti-Interference Scheme for UAV Data Links in Air–Ground Integrated Vehicular Networks

As one of the main applications of the Internet of things (IoT), the vehicular ad-hoc network (VANET) is the core of the intelligent transportation system (ITS). Air–ground integrated vehicular networks (AGIVNs) assisted by unmanned aerial vehicles (UAVs) have the advantages of wide coverage and flexible configuration, which outperform the ground-based VANET in terms of communication quality. However, the complex electromagnetic interference (EMI) severely degrades the communication performance of UAV sensors. Therefore, it is meaningful and challenging to design an efficient anti-interference scheme for UAV data links in AGIVNs. In this paper, we propose an anti-interference scheme, named as Mary-MCM, for UAV data links in AGIVNs based on multi-ary (M-ary) spread spectrum and multi-carrier modulation (MCM). Specifically, the Mary-MCM disperses the interference power by expanding the signal spectrum, such that the anti-interference ability of AGIVNs is enhanced. Besides, by using MCM and multiple-input multiple-output (MIMO) technologies, the Mary-MCM improves the spectrum utilization effectively while ensuring system performance. The simulation results verify that the Mary-MCM achieves excellent anti-interference performance under different EMI combinationsFunding: This work was supported in part by the National Natural Science Foundation of China under Grants 61571370, 61601365, 61901381, 61801388, 61901378, and 61901379; in part by the Science and Technology Research Program of Shaanxi Province under Grants 2018ZDCXL-GY-03-04, 2019ZDLGY07-10, 2019JQ-253, 2019JQ-631, and 2019JM-345; in part by the Advance Research Program on Common Information System Technologies under Grant 315075702; in part by the Postdoctoral Science Foundation of China under Grants BX20180262, BX20190287, 2018M641020, and 2018M641019; and in part by the Fundamental Research Funds for the Central Universities under Grants G2019KY05302, 31020180QD095, and 3102017OQD091.Scopu

Secure multi-path routing for Internet of Things based on trust evaluation

In the realm of the Internet of Things (IoT), ensuring the security of communication links and evaluating the safety of nodes within these links remains a significant challenge. The continuous threat of anomalous links, harboring malicious switch nodes, poses risks to data transmission between edge nodes and between edge nodes and cloud data centers. To address this critical issue, we propose a novel trust evaluation based secure multi-path routing (TESM) approach for IoT. Leveraging the software-defined networking (SDN) architecture in the data transmission process between edge nodes, TESM incorporates a controller comprising a security verification module, a multi-path routing module, and an anomaly handling module. The security verification module ensures the ongoing security validation of data packets, deriving trust scores for nodes. Subsequently, the multi-path routing module employs multi-objective reinforcement learning to dynamically generate secure multiple paths based on node trust scores. The anomaly handling module is tasked with handling malicious switch nodes and anomalous paths. Our proposed solution is validated through simulation using the Ryu controller and P4 switches in an SDN environment constructed with Mininet. The results affirm that TESM excels in achieving secure data forwarding, malicious node localization, and the secure selection and updating of transmission paths. Notably, TESM introduces a minimal 12.4% additional forwarding delay and a 5.46% throughput loss compared to traditional networks, establishing itself as a lightweight yet robust IoT security defense solution