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An efficacious neural network and DNA cryptography-based algorithm for preventing black hole attacks in MANET

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Abstract

Today, more than ever, the necessity for remote availability, independent of a client’s location, is driving the popularity of remote systems. WiFi, Bluetooth, and GPRS are just a few of the wireless technologies that have facilitated the widespread availability of the internet on mobile phones, PDAs, laptops, and other portable electronic devices, and the ease with which users may exchange and sync data between them. MANET, or mobile ad hoc network, is one of the newer ways for nodes to connect because of its decentralized structure and self-configuring nature. Many different protocols control the MANET, and because of its dynamic topology, new problems have emerged in recent years. The black hole attacks put ad hoc networks at risk of data loss. These attacks trick the source into thinking it is sending data through the shortest path possible when, in reality, it is not. It’s a cosmic black hole metaphor where everything vanishes. This research aims to investigate the implications of the Blackhole attack on the On-Demand Multicast Routing Protocol in a MANET and propose solutions to counteract it. MATLAB is used to test the efficacy of our strategy. In addition, the suggested method is evaluated using standard performance measures like packet delivery ratio, throughput, packet loss, etc.

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Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code Availability

The code of the current study are not publicly available due to the ongoing research as a part of future work of this version but are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Department of ITCA, Madan Mohan Malaviya University of Technology, Gorakhpur, UP, 273010, India

    Rahul Chakravorty & Jay Prakash

  2. Department of Computer Engineering and Applications, GLA University, Mathura, UP, 281406, India

    Ashish Srivastava

Authors
  1. Rahul Chakravorty
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  2. Jay Prakash
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  3. Ashish Srivastava
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Correspondence to Rahul Chakravorty or Ashish Srivastava.

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Chakravorty, R., Prakash, J. & Srivastava, A. An efficacious neural network and DNA cryptography-based algorithm for preventing black hole attacks in MANET. Soft Comput 28, 4667–4679 (2024). https://doi.org/10.1007/s00500-023-09386-0

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