Quantum Machine Learning for Intrusion Detection of Distributed Denial of Service Attacks: A Comparative Overview

机译：Quantum Machine学习用于入侵检测分布式拒绝服务攻击：比较概述

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In recent years, we have seen an increase in computer attacks through our communication networks worldwide, whether due to cybersecurity systems' vulnerability or their absence. This paper presents three quantum models to detect distributed denial of service attacks. We compare Quantum Support Vector Machines, hybrid Quantum-Classical Neural Networks, and a two-circuit ensemble model running parallel on two quantum processing units. Our work demonstrates quantum models' effectiveness in supporting current and future cybersecurity systems by obtaining performances close to 100%, being 96% the worst-case scenario. It compares our models' performance in terms of accuracy and consumption of computational resources.

机译：近年来，我们通过全球通信网络的计算机攻击增加了计算机攻击，无论是由于网络安全系统的漏洞还是缺席。本文介绍了三种量子模型，以检测分布式拒绝服务攻击。我们比较量子支持向量机，混合量子 - 经典神经网络和两个量子处理单元上并行运行的双电路集合模型。我们的工作通过获得接近100％的表演，展示量子模型对支持当前和未来的网络安全系统，是最坏情况的96％。它在计算资源的准确性和消费方面比较了我们的模型的性能。

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《Conference on Quantum Computing, Communication, and Simulation》|2021年|116990B.1-116990B.9|共9页
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E.D. Payares; J.C. Martinez-Santos;
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Quantum computing; Quantum machine learning; Quantum Processing Units; Cybersecurity; DDoS attacks; Smart Intrusion Detection Systems;

机译：量子计算;量子机学习;量子加工单位;网络安全;DDOS攻击;智能入侵检测系统;

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1. Machine Learning-Based Distributed Denial of Service Attack Detection on Intrusion Detection System Regarding to Feature Selection [J] . Arif Wirawan Muhammad, Cik Feresa Mohd Foozy, Ahmad Azhari International Journal of Artificial Intelligence Research . 2020,第1期

机译：基于机器学习的分布式拒绝服务攻击检测关于特征选择的入侵检测系统
2. Forging a deep learning neural network intrusion detection framework to curb the distributed denial of service attack [J] . Arnold Adimabua Ojugo, Rume Elizabeth Yoro International Journal of Electrical and Computer Engineering . 2021,第2期

机译：锻造深度学习神经网络入侵检测框架，以遏制分布式拒绝服务攻击
3. Machine Learning-based Distributed Denial of Service Attacks Detection Technique using New Features in Software-defined Networks [J] . Waheed G. Gadallah, Nagwa M. Omar, Hosny M. Ibrahim International Journal of Computer Network and Information Security . 2021,第3期

机译：基于机器学习的分布式拒绝服务攻击检测技术使用软件定义网络中的新功能
4. Machine Learning Based SDN-enabled Distributed Denial-of-Services Attacks Detection and Mitigation System for Internet of Things [C] . Muhammad Aslam, Dengpan Ye, Muhammad Hanif, International Conference on Machine Learning for Cyber Security . 2020

机译：基于机器学习的SDN的分布式拒绝服务攻击事物互联网的检测和缓解系统
5. Detection and Explanation of Distributed Denial of Service (DDoS) Attack Through Interpretable Machine Learning [D] . Das, Saikat. 2021

机译：通过可解释机学习的分布式拒绝服务（DDOS）攻击的检测与解释
6. FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET [O] . Malik N. Ahmed, Abdul Hanan Abdullah, Omprakash Kaiwartya -1

机译：FSM-F：MANET中基于有限状态机的拒绝服务和入侵检测框架
7. Machine Learning-Based Distributed Denial of Service Attack Detection on Intrusion Detection System Regarding to Feature Selection [O] . Ahmad Azhari, Arif Wirawan Muhammad, Cik Feresa Mohd Foozy 2020

机译：基于机器学习的分布式拒绝服务攻击检测关于特征选择的入侵检测系统

Quantum Machine Learning for Intrusion Detection of Distributed Denial of Service Attacks: A Comparative Overview

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