Abstract

Botnets, groups of malware-infected hosts controlled by malicious actors, have gained prominence in an era of pervasive computing and the Internet of Things. Botnets have shown a capacity to perform substantial damage through distributed denial-of-service attacks, information theft, spam and malware propagation. In this paper, a systematic literature review on botnets is presented to the reader in order to obtain an understanding of the incentives, evolution, detection, mitigation and current trends within the field of botnet research in pervasive computing. The literature review focuses particularly on the topic of botnet detection and the proposed solutions to mitigate the threat of botnets in system security. Botnet detection and mitigation mechanisms are categorised and briefly described to allow for an easy overview of the many proposed solutions. The paper also summarises the findings to identify current challenges and trends within research to help identify improvements for further botnet mitigation research.

Highlights

  • The analysis shows that in the 5.5 million Domain Name System (DNS) TXT record queries obtained from their campus network, around

  • This paper sought out to produce a novel systematic literature review detailing different subjects related to botnets, a growing subgroup of malware-enabled attacks

  • Botnets are widely used by malicious actors with various motivations and intentions, from simple denial-of-service attacks to advanced cyber espionage

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Summary

A Survey on Botnets

Survey on Botnets: Incentives, Abstract: Botnets, groups of malware-infected hosts controlled by malicious actors, have gained prominence in an era of pervasive computing and the Internet of Things. A systematic literature review on botnets is presented to the reader in order to obtain an understanding of the incentives, evolution, detection, mitigation and current trends within the field of botnet research in pervasive computing. The literature review focuses on the topic of botnet detection and the proposed solutions to mitigate the threat of botnets in system security. Botnet detection and mitigation mechanisms are categorised and briefly described to allow for an easy overview of the many proposed solutions. The paper summarises the findings to identify current challenges and trends within research to help identify improvements for further botnet mitigation research.

Introduction
Contribution and Research Questions
Outline
Related Work
Methodology
Search Strategy
Initial Exclusion
Title and Abstract Review
Full Text Review
Backwards Snowball Sampling
Incentives
Motivation
Malevolent Botnets
Designated Targets
Reasons for Attack
Benevolent Botnets
Evolution of Botnets
Disguises and Subterfuge
P2P-Based Botnets and Their Intricacies
Extension and Browser Based Botnets
Smartphone-Based Botnets
Vehicular Botnets and Its Effect on Modern Traffic
Blockchain-Based Botnets
IoT-Based Botnets
Atypical New Botnet Variants
Detection and Mitigation
Neural Network Detection Mechanisms
Machine Learning and Network-Based Detection Mechanisms
Detection Mechanisms—Pervasive Computing Paradigms
IoT and P2P Botnets
Mobile Botnets
Vehicle Networks
Social Network Botnets
Mitigation Mechanisms
Best Practices for End-Users and Organisations
Network-Level Blocking and Packet Analysis
Honeypots and Botnet Isolation
Attacking P2P Botnets
Mitigation against IoT Attacks and Botnets
Community Driven Tools against Botnets
Botnet Mitigation with Potential Ethical Issues
Current Trends and Challenges
Increasing Complexity of Botnets
Social Botnets
Machine Learning and Neural Networks for Botnet Detection
Proactive Botnet Mitigation
Cloud-Based Botnets
Findings
Conclusions

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