Hybridized bio-inspired intrusion detection system for Internet of Things

Abstract

The Internet of Things (IoT) consists of several smart devices equipped with computing, sensing, and network capabilities, which enable them to collect and exchange heterogeneous data wirelessly. The increasing usage of IoT devices in daily activities increases the security needs of IoT systems. These IoT devices are an easy target for intruders to perform malicious activities and make the underlying network corrupt. Hence, this paper proposes a hybridized bio-inspired-based intrusion detection system (IDS) for the IoT framework. The hybridized sine-cosine algorithm (SCA) and salp swarm algorithm (SSA) determines the essential features of the network traffic. Selected features are passed to a machine learning (ML) classifier for the detection and classification of intrusive traffic. The IoT network intrusion dataset determines the performance of the proposed system in a python environment. The proposed hybridized system achieves maximum accuracy of 84.75% with minimum selected features i.e., 8 and takes minimum time of 96.42 s in detecting intrusion for the IoT network. The proposed system's effectiveness is shown by comparing it with other similar approaches for performing multiclass classification.

Bio-Inspired Internet of Things: Current Status, Benefits, Challenges, and Future Directions

“…They can handle a large number of devices and data without compromising efficiency [ 23 , 24 , 25 ]. In this regard, bio-inspired IoT algorithms, such as swarm intelligence [ 9 , 20 ], enable efficient scalability in IoT systems by leveraging collective intelligence and self-organization, allowing devices to interact and cooperate locally. On the other hand, this scalability feature enables bio-inspired IoT systems to handle a growing number of devices, interactions, and data, without lacking efficiency and performance.…”

“…By mimicking biological learning processes, they can adapt and improve their performance over time. With the involvement of AI, bio-inspired IoT systems can learn from data, adjust their parameters, and make intelligent decisions, enhancing their autonomy and ability to handle complex tasks [ 9 , 16 ].…”

“…Progressively, this ICT has given birth to many advanced technologies, of which IoT can be considered as one such major technology [ 2 , 3 , 4 , 5 ]. Over the years, this IoT has been affiliated with many of the domains that are deemed important for human survival, such as agriculture, manufacturing, transportation, and healthcare [ 6 , 7 , 8 , 9 ]. Undoubtedly, as of now, this IoT can be considered a major technology that is an essential part of our daily lives.…”

“…These ever-growing IoT solutions are employed in a variety of domains and offer convenient facilities to the stakeholders engaged in these domains. According to the latest statistics, it is predicted that there will be over 100 billion IoT devices by 2025 [ 5 , 6 , 7 , 8 , 9 , 10 ]. It is also evident that the IoT market size is expected to reach over USD 140 billion by 2030 from USD 12 billion in 2020 [ 5 , 6 , 7 , 8 , 9 , 10 ].…”

“…According to the latest statistics, it is predicted that there will be over 100 billion IoT devices by 2025 [ 5 , 6 , 7 , 8 , 9 , 10 ]. It is also evident that the IoT market size is expected to reach over USD 140 billion by 2030 from USD 12 billion in 2020 [ 5 , 6 , 7 , 8 , 9 , 10 ]. Overall, the IoT is transforming industries and revolutionizing the way we live and work.…”