Secure Routing Protocol To Mitigate Attacks By Using Blockchain Technology In Manet

• URL: http://arxiv.org/abs/2304.04254v1
• Date: Sun, 9 Apr 2023 15:19:51 GMT
• Title: Secure Routing Protocol To Mitigate Attacks By Using Blockchain Technology In Manet
• Authors: Nitesh Ghodichor, Raj Thaneeghavl. V, Dinesh Sahu, Gautam Borkar, Ankush Sawarkar
• Abstract summary: MANET is an infrastructure-less network with a changeable topology. Malicious network nodes are the source of network-based attacks. This article explains the many sorts of assaults, their impact on MANET, and the MANET-based defence measures that are currently in place.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: MANET is a collection of mobile nodes that communicate through wireless networks as they move from one point to another. MANET is an infrastructure-less network with a changeable topology; as a result, it is very susceptible to attacks. MANET attack prevention represents a serious difficulty. Malicious network nodes are the source of network-based attacks. In a MANET, attacks can take various forms, and each one alters the network's operation in its unique way. In general, attacks can be separated into two categories: those that target the data traffic on a network and those that target the control traffic. This article explains the many sorts of assaults, their impact on MANET, and the MANET-based defence measures that are currently in place. The suggested SRA that employs blockchain technology (SRABC) protects MANET from attacks and authenticates nodes. The secure routing algorithm (SRA) proposed by blockchain technology safeguards control and data flow against threats. This is achieved by generating a Hash Function for every transaction. We will begin by discussing the security of the MANET. This article's second section explores the role of blockchain in MANET security. In the third section, the SRA is described in connection with blockchain. In the fourth phase, PDR and Throughput are utilised to conduct an SRA review using Blockchain employing PDR and Throughput. The results suggest that the proposed technique enhances MANET security while concurrently decreasing delay. The performance of the proposed technique is analysed and compared to the routing protocols Q-AODV and DSR.

Related papers

• ETGuard: Malicious Encrypted Traffic Detection in Blockchain-based Power Grid Systems [11.476439383002829]
  We present a novel framework that is able to automatically detect malicious encrypted traffic in blockchain-based power grid systems. We mathematically derive incremental learning losses to resist the forgetting of old attack patterns. Our method achieves state-of-the-art performance on three different benchmark datasets.
  arXiv  Detail & Related papers  (2024-08-20T08:53:42Z)
• Securing Proof of Stake Blockchains: Leveraging Multi-Agent Reinforcement Learning for Detecting and Mitigating Malicious Nodes [0.2982610402087727]
  MRL-PoS+ is a novel consensus algorithm to enhance the security of PoS blockchains. We show that MRL-PoS+ significantly improves the attack resilience of PoS blockchains.
  arXiv  Detail & Related papers  (2024-07-30T17:18:03Z)
• Real-time Cyberattack Detection with Collaborative Learning for Blockchain Networks [29.481124078876032]
  We propose an efficient collaborative cyberattack detection model to protect blockchain networks. Our proposed detection model can detect attacks in the blockchain network with an accuracy of up to 97%.
  arXiv  Detail & Related papers  (2024-07-04T15:39:49Z)
• Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning [51.13534069758711]
  Decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities. Federated Learning (FL) enables participants to collaboratively train models while safeguarding data privacy. This paper investigates the synergy between blockchain's security features and FL's privacy-preserving model training capabilities.
  arXiv  Detail & Related papers  (2024-03-28T07:08:26Z)
• Generative AI-enabled Blockchain Networks: Fundamentals, Applications, and Case Study [73.87110604150315]
  Generative Artificial Intelligence (GAI) has emerged as a promising solution to address challenges of blockchain technology. In this paper, we first introduce GAI techniques, outline their applications, and discuss existing solutions for integrating GAI into blockchains.
  arXiv  Detail & Related papers  (2024-01-28T10:46:17Z)
• MRL-PoS: A Multi-agent Reinforcement Learning based Proof of Stake Consensus Algorithm for Blockchain [0.18641315013048293]
  This paper introduces MRL-PoS, a Proof-of-Stake consensus algorithm based on multi-agent reinforcement learning. It incorporates a system of rewards and penalties to eliminate malicious nodes and incentivize honest ones.
  arXiv  Detail & Related papers  (2023-12-14T16:58:18Z)
• Tikuna: An Ethereum Blockchain Network Security Monitoring System [0.0]
  This paper focuses on protecting the lowest level layer in the blockchain, particularly the P2P network that allows the nodes to communicate and share information. The P2P network layer may be vulnerable to several families of attacks, such as Distributed Denial of Service (DDoS), eclipse attacks, or Sybil attacks. We introduce Tikuna, an open-source tool for monitoring and detecting potential attacks on the blockchain P2P network, at an early stage.
  arXiv  Detail & Related papers  (2023-10-13T15:39:50Z)
• The Feasibility and Inevitability of Stealth Attacks [63.14766152741211]
  We study new adversarial perturbations that enable an attacker to gain control over decisions in generic Artificial Intelligence systems. In contrast to adversarial data modification, the attack mechanism we consider here involves alterations to the AI system itself.
  arXiv  Detail & Related papers  (2021-06-26T10:50:07Z)
• Quantum-resistance in blockchain networks [46.63333997460008]
  This paper describes the work carried out by the Inter-American Development Bank, the IDB Lab, LACChain, Quantum Computing (CQC), and Tecnologico de Monterrey to identify and eliminate quantum threats in blockchain networks. The advent of quantum computing threatens internet protocols and blockchain networks because they utilize non-quantum resistant cryptographic algorithms.
  arXiv  Detail & Related papers  (2021-06-11T23:39:25Z)
• Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing [65.32148145602865]
  deep hashing networks are vulnerable to adversarial examples. We propose a novel prototype-supervised adversarial network (ProS-GAN) To the best of our knowledge, this is the first generation-based method to attack deep hashing networks.
  arXiv  Detail & Related papers  (2021-05-17T00:31:37Z)
• Adversarial Attacks on Deep Learning Based Power Allocation in a Massive MIMO Network [62.77129284830945]
  We show that adversarial attacks can break DL-based power allocation in the downlink of a massive multiple-input-multiple-output (maMIMO) network. We benchmark the performance of these attacks and show that with a small perturbation in the input of the neural network (NN), the white-box attacks can result in infeasible solutions up to 86%.
  arXiv  Detail & Related papers  (2021-01-28T16:18:19Z)
• A Self-supervised Approach for Adversarial Robustness [105.88250594033053]
  Adversarial examples can cause catastrophic mistakes in Deep Neural Network (DNNs) based vision systems. This paper proposes a self-supervised adversarial training mechanism in the input space. It provides significant robustness against the textbfunseen adversarial attacks.
  arXiv  Detail & Related papers  (2020-06-08T20:42:39Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.