A Security Framework for IoT Botnet Attack Detection and Mitigation

Abstract

In every aspect of human life, the Internet of Things (IoT) has become an integral requirement. According to a report generated by the International Data Corporation (IDC), the number of IoT devices may increase exponentially by up to two trillion in the near future. Although, IoT applications are extensively adopted in smart devices to equip human life. The plethora of IoT devices and their interconnected cyberspace has gained the attention of hackers because of their inherent vulnerabilities to various possible serious cyberattacks. Thus, the security of IoT systems becomes the prime concern for consumers and businesses as the deployment of IoT technologies grows. newlineAs per the above discussion, many attacks on the IoT network, one such latest attack on the IoT network is the Botnet attack. IoT botnet is one of the most vulnerable attacks in which the devices are compromised and they are used to execute the flood attack on the server. It increased significantly after the release of Mirai in 2016. In 2018, 78% of the malware was generated due to botnet activities. After 2020, it gained a lot of popularity as several variants of the Mirai botnet were released due to availability of the code. Therefore, to enhance the reliability of IoT security systems, a better and real-time method is required. The identification, detection, analysis, and mitigation of IoT botnet is the critical requirement to deal with the attack vectors. newlineFor this purpose, a security framework has been proposed that is divided into four distinct modules, first module is to explore the vulnerable ports and attack vectors of IoT applications. After detecting the vulnerability of the IoT ports, we have executed the DoS attack and collect the data from the sensors. The second module is to detect the IoT botnet in a network by analyzing the IoT traffic. This is achieved by using INFR algorithm integrated with CNN algorithm.