ABSTRACT
Cybercrime refers to a malicious disruption of normal traffic of a server, service, or network by an overpowering encompassing foundation with an overflow web traffic. Particularly, DDoS achieves adequacy using different computer systems as a traffic attack. To ensure security in Internet of Things (IoT) systems, all the interconnected devices should be considered as the first sector concern. Thereupon interfacing gadgets to the internet, emerging security misuse weaknesses broaden. The insecure gadgets enable cybercrime, permitting vindictive individuals to reinvent IoT gadgets, causing malfunction. Imperfect gadgets open information to hackers leaving information insufficiently secured. Thus, malfunctioning or failing devices creates security weaknesses. The chapter focuses on the IoT gadgets capabilities to withstand cybercrimes on their own, which means that they must be programmed using machine learning (ML) algorithms that can enable IoT devices to block undesirable communication with accuracy. For instance, ML algorithms have enabled Google to block undesirable communication with 99% accuracy.
