Abstract

The Internet of Things (IoT) provides the ability to extend the Internet into devices and everyday objects, in a way that they are uniquely addressable. Sensors, actuators, as well as everyday devices and objects, such as cellphones, cars, and homes, are interconnected and form a network that can be accessed, monitored, and controlled remotely. Security is an important subject in the IoT networks since the devices and the networks can be used as a means of invading the users' privacy. The current work examines the issue of security agent location using indicative intrusion detection techniques for network layer attacks. We analyze the methodology, operation, as well as the complexity of each technique. Through the extensive implementation and experimentation, we are able to conclude that the local security agents have the same performance results with centralized and decentralized approaches, but with negligible overhead. As such, they are useful when internal network communication, or network augmentation with monitoring nodes, is not feasible.

Highlights

  • The trend to socially interact through the Internet has led to a new technological era in the field of network communications and services and shifted the attention towards connecting everyday objects

  • The SF notation stands for Selective Forward, FR is Forwarding Ratio, Blocking Node (BN) is Block Node, SF-BH is Selective Forward and Blackhole attack

  • The support vector machine (SVM) model has a Precision of 95% in Selective Forward - Forwarding Ratio (SF-FR) and 100% in SF-BN with the cost of creating false positives

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Summary

Introduction

The trend to socially interact through the Internet has led to a new technological era in the field of network communications and services and shifted the attention towards connecting everyday objects. This mode of connectivity has motivated people to access sensor and embedded device data via the Internet, creating the Internet of Things (IoT). Networks of this type inevitably attract people with malicious intent, who aim in disrupting their functionality by any means possible. The anomaly detection technique has the advantage of detecting novel attacks more by recognizing abnormal activity

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