A survey on intrusion detection system and prerequisite demands in IoT networks

• Published in: Journal of physics. Conference series 2021-05, Vol.1916 (1), p.12179
• Main Authors: Aravamudhan, Parthiban, Kanimozhi, T
• Format: Article
• Language: English
• Subjects: cloud computing; cloud security; Consumers; deep learning; edge detection systems; Industrial development; internet of things; intrusion detection system; Intrusion detection systems; network security; Physics; Security systems
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1916/1/012179

Over the past few years the development in the mobile industry and development of internet, network for all, 4G, 5G etc. enabled the ordinary people as well as the elite people to depend upon mobile networks for regular business developments, entertainment, medical and educational needs. Almost all areas of development depend on the so called improvement of the mobile network. As the advantages and flexibility increases, the consumers entering by new registration increase widely and service requirement of existing consumers increase massively. It is mandatory to provide high level of security and dual privacy protection to the users sharing the large set of information through the cloud. The massive crowd sensing is important for any kind of network security system to ensure the detection of any miscellaneous activity entering the network grid. The study is focused on gathering various literature evidences on demand for intrusion detection system, analyzing the pitfalls in current models and creating an idea that would be helpful for us to proceed further with the research on intrusion detection system implementations and innovating a novel methodology that improvise from the present system. The future enhancement and interpretations on solutions would be discussed too.