A Multi-Level Intrusion Detection System for Wireless Sensor Networks Based on Immune Theory

Alaparthy, Vishwa Teja; Morgera, S.D.

doi:10.1109/access.2018.2866962

Cited by 57 publications

(21 citation statements)

References 16 publications

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“…Alaparthy and Morgera [100] designed a multilevel IDS for WSN environment based on the immune system concept of human body. Factors such as battery life, messages or data size, data transfer rate were used to perform the detection.…”

Section: A Existing Intrusion Detection Protocols In Wsnmentioning

confidence: 99%

“…We compare the results of various IDS in WSN and IoT such as Wazid and Das [34], Wazid et al [27], [66], Wang et al [102], [96], [97], Salehi et al [98], Selvakumar et al [99], Alaparthy and Morgera [100], Sun et al [101], Jan et al [103], Sharma et al [104], Pajouh et al [105], Mudgerikar et al [108], and Ahmed et al [109].…”

Section: Comparative Analysis Of Existing Ids In Wsn and Iotmentioning

confidence: 99%

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Intrusion Detection Protocols in Wireless Sensor Networks Integrated to Internet of Things Deployment: Survey and Future Challenges

et al. 2020

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As we all know that the technology is projected to be next to humans very soon because of its holistic growth. Now-a-days, we see a lot of applications that are making our lives comfortable such as smart cars, smart homes, smart traffic management, smart offices, smart medical consultation, smart cities, etc. All such facilities are in the reach of a common man because of the advancement in Information and Communications Technology (ICT). Because of this advancement, new computing and communication environment such as Internet of Things (IoT) came into picture. Lot of research work is in progress in IoT domain which helps for the overall development of the society and makes the lives easy and comfortable. But in the resource constrained environment of Wireless Sensor Network (WSN) and IoT, it is almost inconceivable to establish a fully secure system. As we are moving forward very fast, technology is becoming more and more vulnerable to the security threats. In future, the number of Internet connected people will be less than the smart objects so we need to prepare a robust system for keeping the above mentioned environments safe and standardized it for the smooth conduction of communication among IoT objects. In this survey paper, we provide the details of threat model applicable for the security of WSN and IoT based communications. We also discuss the security requirements and various attacks possible in WSN and IoT based communication environments. The emerging projects of WSNs integrated to IoT are also briefed. We then provide the details of different architectures of WSN and IoT based communication environments. Next, we discuss the current issues and challenges related to WSN and IoT. We also provide a critical literature survey of recent intrusion detection protocols for IoT and WSN environments along with their comparative analysis. A taxonomy of security and privacy-preservation protocols in WSN and IoT is also highlighted. Finally, we discuss some research challenges which need to be addressed in the coming future. INDEX TERMS Wireless sensor network (WSN), Internet of Things (IoT), intrusion detection, cloud computing, fog computing, edge computing, security.

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Section: A Existing Intrusion Detection Protocols In Wsnmentioning

confidence: 99%

Section: Comparative Analysis Of Existing Ids In Wsn and Iotmentioning

confidence: 99%

Intrusion Detection Protocols in Wireless Sensor Networks Integrated to Internet of Things Deployment: Survey and Future Challenges

et al. 2020

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“…Alaparthy et al [10] used the basic principles of artificial immune technology to propose an immune theory technology called danger theory to protect wireless sensor networks (WSN). This is achieved by monitoring WSN parameters (such as energy, data volume, and data transmission frequency) and developing outputs based on their weights and concentrations.…”

Section: Related Workmentioning

confidence: 99%

SLGBM: An Intrusion Detection Mechanism for Wireless Sensor Networks in Smart Environments

Jiang

Zhao

2020

IEEE Access

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Wireless sensor network (WSN), which serves as one of the key components of the cyber physical system, is a wireless network composed of many stationary or moving sensors in a self-organizing and multi-hop manner. It cooperatively senses, collects, processes and transmits the information of the perceived objects in the geographical area covered by the network, and finally sends this information to the owner of the network. There are some typical attacks in WSN, such as Blackhole, Grayhole, Flooding and Scheduling attacks, which may cause damages to the WSN system in a short time. Moreover, intrusion detection methods for WSN suffer from the disadvantages of low detection rate, large calculation overhead, and high false alarm rate due to the limited resources of sensor nodes and a large amount of redundancy as well as high correlation of network data. In view of the above problems, we propose SLGBM, an intrusion detection method for wireless sensor networks. First, the sequence backward selection (SBS) algorithm is applied to reduce the data dimension on the feature space of the original traffic data so as to reduce the computational overhead. A LightGBM algorithm is then utilized to detect different network attacks. The experimental results based on the WSN-DS dataset show that F-measure of our proposed SLGBM are obviously superior to current typical detection methods, which are 99.8%, 99.4%, 99.1%, 96.5%, and 96.1% in Normal, Blackhole, Grayhole, Flooding, and Scheduling (TDMA) attack detections respectively.

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“…On the other hand, Wang et al (2018) [80] proposed an improved Immune algorithm for industrial cloud storage. Alaparthy et al (2018) [81] analyzed a multi-level ID system based on the Immune algorithm. Many studies address the application of ANN in ID.…”

Section: E Intrusion Detectionmentioning

confidence: 99%

Applications and Evaluations ofBio-InspiredApproaches in Cloud Security: A Review

et al. 2020

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Cloud computing gained much popularity in the recent past due to its many internet-based services related to data, application, operating system, and eliminating the need for central hardware access. Many of the challenges associated with cloud computing can be specified as network load, security intrusion, authentication, biometric identification, and information leakage. Numerous algorithms have been proposed and evaluated to solve those challenges. Among those, bio-inspired algorithms such as Evolutionary, Swarm, Immune, and Neural algorithms are the most prominent ones which are developed based on nature's ecosystems. Bio-inspired algorithms' adaptability allows many researchers and practitioners to utilize them to solve many security-related cloud computing issues. This paper aims to explore previous research, recent studies, challenges, and scope for further analysis of cloud security. Therefore, this study provides an overview of bio-inspired algorithms application and evaluations, taking into account cloud security challenges,

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A Multi-Level Intrusion Detection System for Wireless Sensor Networks Based on Immune Theory

Cited by 57 publications

References 16 publications

Intrusion Detection Protocols in Wireless Sensor Networks Integrated to Internet of Things Deployment: Survey and Future Challenges

Intrusion Detection Protocols in Wireless Sensor Networks Integrated to Internet of Things Deployment: Survey and Future Challenges

SLGBM: An Intrusion Detection Mechanism for Wireless Sensor Networks in Smart Environments

Applications and Evaluations ofBio-InspiredApproaches in Cloud Security: A Review

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