Cybersecurity for autonomous vehicles against malware attacks in smart-cities.

Autor:	Aurangzeb, Sana, Aleem, Muhammad, Khan, Muhammad Taimoor, Anwar, Haris, Siddique, Muhammad Shaoor
Předmět:	INTELLIGENT transportation systems TRAFFIC safety CYBER physical systems TRAFFIC congestion AUTONOMOUS vehicles INTERNET security WIRELESS communications MALWARE
Zdroj:	Cluster Computing; Jun2024, Vol. 27 Issue 3, p3363-3378, 16p
Abstrakt:	Smart Autonomous Vehicles (AVSs) are networks of Cyber-Physical Systems (CPSs) in which they wirelessly communicate with other CPSs sub-systems (e.g., smart -vehicles and smart-devices) to efficiently and securely plan safe travel. Due to unreliable wireless communication among them, such vehicles are an easy target of malware attacks that may compromise vehicles' autonomy, increase inter-vehicle communication latency, and drain vehicles' power. Such compromises may result in traffic congestion, threaten the safety of passengers, and can result in financial loss. Therefore, real-time detection of such attacks is key to the safe smart transportation and Intelligent Transport Systems (ITSs). Current approaches either employ static analysis or dynamic analysis techniques to detect such attacks. However, these approaches may not detect malware in real-time because of zero-day attacks and huge computational resources. Therefore, we introduce a hybrid approach that combines the strength of both analyses to efficiently detect malware for the privacy of smart-cities. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
Externí odkaz:	Zobrazit plný text záznamu Full text from SpringerLink