Optimized Energy Efficient Secure Routing Protocol for Wireless Body Area Network

Singla, Ripty; Kaur, Navneet; Koundal, Deepika; Lashari, Saima Anwar; Bhatia, Surbhi; Rahmani, Mohammad Khalid Imam

doi:10.1109/access.2021.3105600

Cited by 36 publications

(7 citation statements)

References 52 publications

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“…The classifier C which is trained on the intrusion detection dataset provides higher accuracy and the main aim of this work is to generate an adversarial instance a adv that can track the classifier C to predict it as a normal entity that looks similar to instance a. There are two types of attack and one is a targeted one whereas another is an untargeted attack [14,15]. The classifier C used in the proposed methodology is DCGAN.…”

Section: Proposed Methodologymentioning

confidence: 99%

Optimized Generative Adversarial Networks for Adversarial Sample Generation

Alghazzawi¹,

Hasan²,

Bhatia³

2022

Computers, Materials &Amp; Continua

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Detecting the anomalous entity in real-time network traffic is a popular area of research in recent times. Very few researches have focused on creating malware that fools the intrusion detection system and this paper focuses on this topic. We are using Deep Convolutional Generative Adversarial Networks (DCGAN) to trick the malware classifier to believe it is a normal entity. In this work, a new dataset is created to fool the Artificial Intelligence (AI) based malware detectors, and it consists of different types of attacks such as Denial of Service (DoS), scan 11, scan 44, botnet, spam, User Datagram Portal (UDP) scan, and ssh scan. The discriminator used in the DCGAN discriminates two different attack classes (anomaly and synthetic) and one normal class. The model collapse, instability, and vanishing gradient issues associated with the DCGAN are overcome using the proposed hybrid Aquila optimizer-based Mine blast harmony search algorithm (AO-MBHS). This algorithm helps the generator to create realistic malware samples to be undetected by the discriminator. The performance of the proposed methodology is evaluated using different performance metrics such as training time, detection rate, F-Score, loss function, Accuracy, False alarm rate, etc. The superiority of the hybrid AO-MBHS based DCGAN model is noticed when the detection rate is changed to 0 after the retraining method to make the defensive technique hard to be noticed by the malware detection system. The support vector machines (SVM) is used as the malicious traffic detection application and its True positive rate (TPR) goes from 80% to 0% after retraining the proposed model which shows the efficiency of the proposed model in hiding the samples.

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Section: Proposed Methodologymentioning

confidence: 99%

Optimized Generative Adversarial Networks for Adversarial Sample Generation

Alghazzawi¹,

Hasan²,

Bhatia³

2022

Computers, Materials &Amp; Continua

Self Cite

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“…Application-specific data acquisition process focussing on energy efficiency and media access, through LEACH-centralized protocol that go along with self-organisation of the sensor nodes and spinning cluster head positions for efficient load handling that out performs the lifetime [ 8 ] of the Network. Reducing network congestion to improve data reliability and enhance the data transmission with security [ 9 ] using an Optimized Energy Efficient Secure Routing Protocol (OEESR). The protocol evaluates data throughput and energy consumption by 90% and 8.8% with diminished packet drop rate of 13%.…”

Section: Literature Reviewmentioning

confidence: 99%

Hierarchical energy efficient secure routing protocol for optimal route selection in wireless body area networks

Roshini

Kiran

2023

International Journal of Intelligent Networks

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“…The multipath routing transmission mechanism and data encoding and decoding transmission mechanism of mobile wireless sensor network are mainly to improve the stability and reliability of network transmission and improve the fault tolerance of network transmission [ 10 ]. This section will introduce the research progress of related research work.…”

Section: Related Workmentioning

confidence: 99%

An Energy Efficient and Reliable Multipath Transmission Strategy for Mobile Wireless Sensor Networks

Sun

Wang

et al. 2022

Computational Intelligence and Neuroscience

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Multipath data transmission is a key problem that needs to be solved urgently in wireless sensor networks. In this paper, sensor node failure, link failure, energy exhaustion, and external interference affect the stability and reliability of network data transmission. A multipath transmission strategy for wireless sensor networks based on improved shuffled frog leaping algorithm is proposed. A mathematical model of multipath transmission in wireless sensor networks is established. In the shuffled frog leaping algorithm, combined with the transition probability in the particle swarm optimization algorithm, random individuals in the subgroup are introduced to assist the search when updating the frog individual position, which improves the algorithm's ability to jump out of the local optimum and improves the quality of the optimization algorithm solution. The model is applied to multipath transmission in wireless sensor networks. Then, the shuffled frog leaping algorithm is used to update, divide, and reorganize the sensor nodes to select the optimal node to establish the optimal transmission path and improve the stability and reliability of the network. Simulation experiments show that the algorithm in this paper can ensure the reliability of data transmission, reduce the network packet loss rate and network energy consumption, and reduce the average delay of data transmission.

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Optimized Energy Efficient Secure Routing Protocol for Wireless Body Area Network

Cited by 36 publications

References 52 publications

Optimized Generative Adversarial Networks for Adversarial Sample Generation

Optimized Generative Adversarial Networks for Adversarial Sample Generation

Hierarchical energy efficient secure routing protocol for optimal route selection in wireless body area networks

An Energy Efficient and Reliable Multipath Transmission Strategy for Mobile Wireless Sensor Networks

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