Proactive Memory Efficient DDOS Attack Detection at IoT Gateways through Microneural Networks with Jellyfish Optimizer

Manjula L; G T Raju; Pallavi N

Author(s)

Manjula L Department of Artificial intelligence and Machine Learning, BMS College of Engineering, Visvesvaraya Technological University, Belagavi, India

G T Raju Department of Computer science and Engineering, SJC Institute of Technology, Visvesvaraya Technological University, Belagavi, India

Pallavi N Department of Computer science and Engineering, Ramaiah Institute of Technology, Visvesvaraya Technological University Belagavi, India

Abstract

In fact, the modernization of IoT technology has led to the emergence of cyber hazards with DDoS attacks as particularly risky for IoT service availability. This occurs by overwhelming the targeted services with traffic from multiple sources hence disrupting it. In the context of IoT and DDoS attack detection, Identifying and mitigating these attacks across connecting nodes is essential to ensure the smooth functioning of IoT services. IoT network is a collection of diverse elements namely 6LOWPAN, LoRAWAN etc. Effective mitigation techniques should be designed which is applicable to diverse sets of connecting IoT nodes including gateways, fully connected nodes, and edge devices for early detection of attacks. These nodes are of both categories namely constrained and nonconstrained. So, mitigation policies designed must be with low memory consumption and inference time. This study presents a fresh DDoS attack detection model, a Jellyfish (JF) Jaro optimizer for feature selection with Light weight Micro Neural Network with string interning (MNNSI) on the IoT platform. The main goal of the MNNSI-JF approach is in the efficient & automated detection of DDoS attacks with minimal memory usage. The assessment of the simulation value of the MNNSIJF methodology was evaluated on the benchmark dataset and based on the result it shows that the improvements over other prior models were evaluated in terms of distinct measures such as memory consumption & inference time.

Publication Details

Page(s) 1-16

DOI DOI not available

Published Journal: International Journal of Communication Networks and Information Security, Volume: 16, Issue: 3, Year: 2024

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Keywords

bio inspired algorithms, DDOS Attack Detection, Proactive Memory Efficient, Jellyfish Optimizer, Internet of Things Gateways

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