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This research demonstrates how to monitor an Internet of Things (IoT) construct and use the data captured from the network's IoT devices to gather information about end-users in the operating environment. The purpose for this study is to expose unsophisticated capabilities that malicious entities can perform when the aggregation of the raw data created from the low-level processing operation of IoT...
The objective of this research is to associate artificial registrations of unauthorized network activity with stress knowledge representations to self-Monitor an autonomic computing system, which is a self-Managing system. Utilization of the danger theory perspective in artificial immune systems (AIS) is employed to illustrate how an AIS classification method contributes to four properties of autonomic...
In this research, a real-world simulation service uses Internet of Things (IoT) capable objects to detect behavioral-based anomalies within a simulated smart home/vicinity. In the simulation, the smart home and the surrounding world are monitored with a behavioral modeling intrusion detection system (BMIDS). The BMIDS uses immunity-inspired algorithms to distinguish whether behavioral patterns extracted...
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