A Security Model for Intrusion Detection and Prevention over Wireless Network

Yadav, Anurag; Gupta, Himanshu; Khatri, Sunil Kumar

doi:10.1109/iscon47742.2019.9036288

Cited by 3 publications

(4 citation statements)

References 10 publications

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“…Figure 5, demonstrates the detection of various network attacks and compares them with state-of-the-art methods. Figure 5, describes the proposed model obtains higher results than IDS based methods such as (3,5,11) (5) in large WSNs. https://www.indjst.org/ According to Figure 5 and Figure 6, the proposed lightweight key generation method required minimum time and energy for data encryption and decryption.…”

Section: Resultsmentioning

confidence: 97%

“…Standard and Rivest Shamir Adleman algorithm: (10) 1 to 10 23 64 Tropea M. (12) 1 to 12 25 and 46 64 and 128 Anurag Yadav (11) 1 to 8 21 and 39 64 and 128 Zhou L. (9) 1 to 5 9 and 17 32 and 64 Lightweight (proposed) 1 to 5, 10 8, 13 and 34 32,64 and 128…”

Section: Resultsmentioning

confidence: 99%

“…This table demonstrates proposed system required minimum time for key generation using all 32-, 64-and 128-bit encryption methods. It also requires minimum time compare to other key generation techniques such as (9)(10)(11)(12)(13)(14)(15)(16)(17)(18) .…”

Section: Resultsmentioning

confidence: 99%

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Lightweight Cryptography Using Pairwise Key Generation and Malicious Node Detection in Large Wireless Sensor Network

Sall,

Bansode

2023

IJST

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Objectives: To design and develop pairwise key generation techniques for malicious node detection in wireless sensor network. Method: The lightweight key generation method has been used for data encryption with the collaboration of the sender node, entry node and destination. The unique identity of the destination server has utilized for data encryption and decryption as a master key. The proposed method generates a concise key length that reduces encryption and decryption time. It also helps to detect the misbehaviour of internal nodes when it takes higher time for data decryption and transmission. Findings: The proposed system reduces end to end delay around 10%, the packet delivery ratio improves by 3.30%, throughput by 9.87, and energy consumption by 20.50% than Advanced Encryption Standard and Rivest Shamir Adleman algorithm. The proposed encryption algorithm compresses the cypher data, reducing the network overhead, and detecting malicious nodes, providing higher security from internal and external intruders. This simulation obtains better results than existing systems that enhance around 7-9% throughput with all QoS parameters. Novelty: The proposed system eliminates network overhead of key transmission to the destination. Using this approach, the sender node generates a lightweight key for data encryption using the destination node, which means only the destination node can decrypt the data using the generation of similar keys. When any random node tries to generate such keys, it violates time-bound, and system detects as a malicious node.

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Section: Resultsmentioning

confidence: 97%

Section: Resultsmentioning

confidence: 99%

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Lightweight Cryptography Using Pairwise Key Generation and Malicious Node Detection in Large Wireless Sensor Network

Sall,

Bansode

2023

IJST

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“…Any action endeavoring to weak these parameters or to sidestep the security schemes of a network can be viewed as a network intrusion. An IDS is a sort of security management framework that is used to identify intrusion in the network and is a basic section of network security frameworks these days [1][2][3]. An IDS ordinarily checks all incoming as well as outgoing data of a specific network to decide if every packet has indications of an intrusion.…”

Section: Introductionmentioning

confidence: 99%

Wireless Intrusion Detection Based on Optimized LSTM with Stacked Auto Encoder Network

Karthic¹,

Kumar²

2022

Intelligent Automation &Amp; Soft Computing

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In recent years, due to the rapid progress of various technologies, wireless computer networks have developed. However, the activities of the security threats and attackers affect the data communication of these technologies. So, to protect the network against these security threats, an efficient IDS (Intrusion Detection System) is presented in this paper. Namely, optimized long short-term memory (OLSTM) network with a stacked auto-encoder (SAE) network is proposed as an IDS system. Using SAE, significant features are extracted from the databases such as input NSL-KDD database and the UNSW-NB15 database. Then extracted features are given as input to the optimized LSTM which is used as an intrusion identification system. To enhance the effectiveness of the LSTM, we present the pigeon optimization algorithm (POA). Using this algorithm, weight parameters of the LSTM are chosen optimally. Finally, the proposed IDS model decides whether the input packets are intruded or not. The results confirm that the proposed IDS model surpasses the previous machine learning-based IDS models in terms of correctness, F1-score and G mean.

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TL-IDPS: Two Level Intrusion Detection and Prevention System using Probabilistic Optimal Feature Set Estimation

Ntizikira

Wang

et al. 2020

2020 16th International Conference on Mobility, Sensing and Networking (MSN)

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A Security Model for Intrusion Detection and Prevention over Wireless Network

Cited by 3 publications

References 10 publications

Lightweight Cryptography Using Pairwise Key Generation and Malicious Node Detection in Large Wireless Sensor Network

Lightweight Cryptography Using Pairwise Key Generation and Malicious Node Detection in Large Wireless Sensor Network

Wireless Intrusion Detection Based on Optimized LSTM with Stacked Auto Encoder Network

TL-IDPS: Two Level Intrusion Detection and Prevention System using Probabilistic Optimal Feature Set Estimation

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