The key characteristic of smart cities (ie, connectivity and intelligence) has enabled connected vehicles to work together to accomplish complex jobs that they are unable to perform individually. Connectivity not only being an inevitable blessing but also poses growing cybersecurity challenges for connected vehicles. The overall risk of connected vehicles is wide as the cybercriminals are nowadays applying versatile approaches (botnets, phishing, zero-days, rootkits, etc) to disrupt their communication. The botnet, capable of launching distributed denial of service attack, is a potential threat for any connected ecosystem due to its excessive capabilities of using maximum compromised devices. Hence, the detection of botnet attacks has become a pinnacle point for cybersecurity analysts. Existing studies lack in detecting botnet at the earliest and accurately. This article presents an approach to detect the botnet attacks at an early stage and accurately utilizing typical network traffic and temporal features. The proposed approach use machine learning algorithms for the detection of botnet attack(s) and present a detailed comparison of the decision tree, probabilistic neural network, sequential minimal optimization, and Adaboost classifiers, as well as comparison of the proposed approach with existing studies in this domain, is also done. Furthermore, it investigates the role of temporal features for botnet detection. The proposed approach accomplishes the promising true positive rate of 99.7%. Results show that our methodology is efficient compared with the existing studies.
INTRODUCTIONThe concept of a smart city is primarily composed of information and communication technologies (ICT), to advance the quality of services such as connectivity, energy, transportation, and others. Especially in transportation the continuous vehicle to infrastructure (V2I), vehicle-to-sensors (V2S), vehicle-to-pedestrians, vehicle-to-vehicle (V2V) and the vehicle-to-cloud (V2C) services in smart cities are becoming essential for safety and nonsafety applications. Smart cities provide a channel to the driver, vehicle, infrastructure, and cloud to connect. 1,2 Smart cities produce a huge amount of data collected through IoT devices for further analysis that brings security issues with regard to communicating entities. [3][4][5][6][7] IoT devices (ie, smartphones, smartwatches, smart TV) have become a need of our daily lives. People around the globe are connected using personal smart devices and use them to perform many routine tasks daily. [8][9][10] Security in this current era of the connected world is most important as a single cyberattack can result in loss of important Abdul Rehman Javed and Zunera Jalil contributed equally to this study.
