An Efficient Iot Network Intrusion Detection And Prevention System JARVIS – Just A Rather Very Intelligent System.
Keywords:
Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Intrusion Detection And Prevention System (IDPS), Intrusion Detection System (IDS), Intrusion Prevention System (IPS).Abstract
Given the race to find the best technique that suits and protects all Internet of Things (IoT) wireless devices, all around the world are in a quest to develop Intrusion Detection And Prevention Systems (IDPS). This has been led by a huge change from the traditional world shifting to the smart and intelligent world empowered and made possible by IoT devices and Artificial Intelligence and Machine Learning techniques (ML). The scope of security is much a relevant need but is challenged and limited by the computation memory and processing hardware which are typically small or micro in most heterogeneous IoT devices. Hence Machine Learning (ML) algorithms come into play while constructing an effective IDPS that treats every threat by detecting and preventing it from attacking the IoT devices and their network. In the proposed paper we show how the Intrusion Detection System (IDS) can be developed from both supervised and unsupervised machine learning techniques which addresses both static and dynamic intrusion attacks by using the KDD-CUP dataset and prevent them using the different cryptographic techniques that can perform well in small processing environments. Afterward in the results, it has been shown that among the algorithms of ML Support Vector Machine (SVM), Random Forest (RF), Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), RF gives the best values for the F1 score, recall, accuracy, and other evaluation metrics. Then using the Java Springs framework work we have built the IDPS which is integrated with the smart IDS thus forming an IDPS that safeguards the network and devices from the generic attacks which are known and unknown intrusions assuming the intruder is based on the server.
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