2019/06/27 by Omar M. Alhawi, Alhawi, Omar M., Mustafa Mustafa +3
Computer Science · #Advanced Malware Detection Techniques #Adversarial Robustness in Machine Learning #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Software Testing and Debugging Techniques
paper · pdf · doi:10.48550/arxiv.1906.11488
openalex publication_date 2019/06/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The proliferation of Unmanned Aerial Vehicles (UAVs) embedded with vulnerable\nmonolithic software has recently raised serious concerns about their security\ndue to concurrency aspects and fragile communication links. However, verifying\nsecurity in UAV software based on traditional testing remains an open challenge\nmainly due to scalability and deployment issues. Here we investigate software\nverification techniques to detect security vulnerabilities in typical UAVs. In\nparticular, we investigate existing software analyzers and verifiers, which\nimplement fuzzing and bounded model checking (BMC) techniques, to detect memory\nsafety and concurrency errors. We also investigate fragility aspects related to\nthe UAV communication link. All UAV components (e.g., position, velocity, and\nattitude control) heavily depend on the communication link. Our preliminary\nresults show that fuzzing and BMC techniques can detect various software\nvulnerabilities, which are of particular interest to ensure security in UAVs.\nWe were able to perform successful cyber-attacks via penetration testing\nagainst the UAV both connection and software system. As a result, we\ndemonstrate real cyber-threats with the possibility of exploiting further\nsecurity vulnerabilities in real-world UAV software in the foreseeable future.\n