Bio-inspired machine learning based Wireless Sensor Network security

Rathore, Heena; Jha, Sushmita

doi:10.1109/nabic.2013.6617852

Cited by 31 publications

(14 citation statements)

References 10 publications

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“…Machine learning–based bio‐inspired trust and reputation model uses inspiration from the human immune system to differentiate between malicious and benign nodes on the network.…”

Section: State‐of‐the‐art Trust and Reputation Modelsmentioning

confidence: 99%

“…The classification is achieved using machine learning algorithms. During the second block, virtual antibodies are generated by the CHs using equation 9 in Rathore and Jha and transmitted to sensor nodes.

u_{j} = \frac{1}{m} true \sum_{i = 1}^{m} x_{j}^{i} .

This process goes on for some time till the gateway generates trust value ratings for the nodes within the third block.…”

Section: State‐of‐the‐art Trust and Reputation Modelsmentioning

confidence: 99%

“…The popularity of TRMs in ensuring security in WSN is due to the heavy computations associated with cryptography‐based protocols that cannot be supported by the resource constrained network . Numerous schemes have been proposed with the aim of aiding sensor nodes to better establish excellent trust and reputation among themselves . Most of the solutions for several complicated problems such as security have been attempted using engineering approaches.…”

Section: Introductionmentioning

confidence: 99%

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The adoption of socio‐ and bio‐inspired algorithms for trust models in wireless sensor networks: A survey

Nunoo‐Mensah

Boateng

Gadze

2017

Int J Communication

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The security of a wireless sensor network is greatly increased with increasing levels of trustworthiness of nodes on the network. There are a number of trust models proposed that use various trust evaluation methods. The paper categorises trust evaluation methods for wireless sensor networks into socio-inspired, bio-inspired, and analytical methods. Biologically inspired methods and socio constructs are rarely used in the design of trust schemes as opposed to analytical methods (probability, agent based, fuzzy, etc). The paper discusses existing bio-and socio-inspired-based trust schemes implemented for wireless sensor networks, viz quality-based distance vector protocol, enhanced bio-inspired trust and reputation model for wireless sensor network, bio-inspired trust routing protocol, machine learning-based bio-inspired trust and reputation model, socio-psychological trust and reputation model, and finally reputation framework for sensor network. The contributions, trust evaluation methods and limitations of recent trust models (i.e. analytical based, biological and socio-inspired models) are discussed in this paper. The pros and cons of analytical, socio, and biologically inspired algorithms for computing are outlined to easily ascertain the relevance of adopting either biological or socio-inspired approaches for solving trust-related problems in wireless sensor networks. KEYWORDSbio-inspired algorithms, socio-inspired algorithms, trust models, wireless sensor network Int J Commun Syst. 2018;31:e3444.wileyonlinelibrary.com/journal/dac

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“…Machine learning–based bio‐inspired trust and reputation model uses inspiration from the human immune system to differentiate between malicious and benign nodes on the network.…”

Section: State‐of‐the‐art Trust and Reputation Modelsmentioning

confidence: 99%

u_{j} = \frac{1}{m} true \sum_{i = 1}^{m} x_{j}^{i} .

This process goes on for some time till the gateway generates trust value ratings for the nodes within the third block.…”

Section: State‐of‐the‐art Trust and Reputation Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The adoption of socio‐ and bio‐inspired algorithms for trust models in wireless sensor networks: A survey

Nunoo‐Mensah

Boateng

Gadze

2017

Int J Communication

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“…The authors in [26] apply the biological knowledge about the human immune system to propose a new network security mechanism to disable the fraudulent nodes in a WSN. Bioinspired algorithms provide dynamic, adaptive, and real-time methods of intrusion detection.…”

Section: Related Workmentioning

confidence: 99%

Web Spider Defense Technique in Wireless Sensor Networks

Cánovas

Lloret

Macías

et al. 2014

International Journal of Distributed Sensor Networks

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Wireless sensor networks (WSNs) are currently widely used in many environments. Some of them gather many critical data, which should be protected from intruders. Generally, when an intruder is detected in the WSN, its connection is immediately stopped. But this way does not let the network administrator gather information about the attacker and/or its purposes. In this paper, we present a bioinspired system that uses the procedure taken by the web spider when it wants to catch its prey. We will explain how all steps performed by the web spider are included in our system and we will detail the algorithm and protocol procedure. A real test bench has been implemented in order to validate our system. It shows the performance for different response times, the CPU and RAM consumption, and the average and maximum values for ping and tracert time responses using constant delay and exponential jitter.

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“…The rate constants Q and R are necessarily not same. The rate of antibody production at time t is supposed to be proportional to the rate of small B cell stimulation at time t -T. That is, there is a delay T between stimulation of a small B-cell and the subsequent production of plasma cells from it [26]. When simulations were carried out using the Runge Kutta(variable) method for solving the differential equations, following results were seen as shown in Figure 11.…”

Section: Mathematical Modelmentioning

confidence: 99%