Detection and Analysis of P2P Malware Detection in IoT Smart Home Applications

The Internet of Things is a trending technology with the objective of connecting billions of devices to the Internet and offering automation like never. The devices can make their own decisions based on the input data. With all the advantages and features of the IoT platform, the only challenge that seems to be complicated is security. IoT security is a vast topic because of the numerous layers in architecture and the complexity involved in the data processing operations. The research study considered statistical analysis using Python programming language for analyzing the importance of security framework and how the security frameworks can excel against P2P botnet type of malware. A public data set was part of the solution design on the Google Colab platform. The data set consisted of many entries and variables, which revealed the data packets in P2P attacks. This attack is relevant to the discussion of the security framework because all the layers of the architecture are affected by a malware attack. The peer-to-peer communication between two or more IoT devices requires support by the controller layer of the architecture. The details of botnet traffic and attack are self-explanatory. The objective is to detect the network packets with malicious codes include using the proposed method. Detecting SYN flood attacks, ICMP flood attacks, HTTP attacks, and DNS amplification attacks are part of the solution.