A flexible SDN-based framework for slow-rate DDoS attack mitigation by using deep reinforcement learning

计算机科学 服务拒绝攻击 强化学习 软件定义的网络 可扩展性 入侵检测系统 应用层DDoS攻击 前进飞机 计算机网络 特里诺 计算机安全 人工智能 操作系统 互联网 网络数据包
作者
Noe M. Yungaicela-Naula,Cesar Vargas‐Rosales,Jesús Arturo Pérez-Díaz,Diego Fernando Carrera
出处
期刊:Journal of Network and Computer Applications [Elsevier BV]
卷期号:205: 103444-103444 被引量:53
标识
DOI:10.1016/j.jnca.2022.103444
摘要

Distributed Denial-of-Service (DDoS) attacks are difficult to mitigate with existing defense tools. Fortunately, it has been demonstrated that Software-Defined Networking (SDN) with machine learning (ML) and deep learning (DL) techniques has a high potential to handle these threats effectively. However, although there are many SDN-based solutions for detecting DDoS attacks, only a few contain mitigation strategies. Additionally, most previous studies have focused on solving high-rate DDoS attacks. For the time being, recent slow-rate DDoS threats are hard to detect and mitigate. In this work, we propose a modular, flexible, and scalable SDN-based framework that integrates a DL-based intrusion detection system (IDS) and a deep reinforcement learning (DRL)-based intrusion prevention system (IPS) to address slow-rate DDoS threats. We incorporated scalability features into this framework, such as data-plane-based traffic monitoring and traffic flow sampling. Moreover, we have designed a lightweight DRL-based IPS to provide rapid mitigation responses. Furthermore, to evaluate the framework, we deployed a data center network using Mininet, Open Network Operating System (ONOS) controller, and Apache Web server. Next, we performed extensive experiments varying the number of attackers and the rate of attack connections. The proposed IDS achieved an average detection rate of 98%, with a flow sampling rate of 30%. In addition, IPS timely mitigated slow-rate DDoS with 100% of success for a few attackers. Taken together, these results show that the proposed framework provides effective responses to malicious and legitimate connections.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
jiaolulu发布了新的文献求助10
4秒前
量子星尘发布了新的文献求助10
4秒前
真的不想干活了完成签到,获得积分10
4秒前
美丽的依琴完成签到,获得积分10
5秒前
Xin完成签到,获得积分10
11秒前
Aurora.H完成签到,获得积分10
14秒前
14秒前
FashionBoy应助科研通管家采纳,获得10
15秒前
打打应助科研通管家采纳,获得10
15秒前
Jasper应助科研通管家采纳,获得10
15秒前
Ava应助科研通管家采纳,获得10
15秒前
顾矜应助科研通管家采纳,获得10
15秒前
上官若男应助科研通管家采纳,获得10
15秒前
duckspy发布了新的文献求助10
17秒前
17秒前
17秒前
xiaowan完成签到,获得积分10
18秒前
Terry完成签到,获得积分10
19秒前
张张张哈哈哈完成签到,获得积分10
19秒前
Research完成签到 ,获得积分10
19秒前
称心采枫完成签到 ,获得积分0
20秒前
20秒前
新新新新新发顶刊完成签到 ,获得积分10
21秒前
L3完成签到,获得积分10
22秒前
我是科研小能手完成签到,获得积分10
22秒前
风中的小丸子完成签到,获得积分10
23秒前
23秒前
时尚俊驰发布了新的文献求助10
24秒前
24秒前
24秒前
Grin完成签到,获得积分10
25秒前
周周完成签到,获得积分20
25秒前
26秒前
liufan完成签到 ,获得积分10
28秒前
guitarist完成签到 ,获得积分10
28秒前
饮汽水完成签到,获得积分10
28秒前
28秒前
yoyo20012623完成签到,获得积分10
29秒前
伦语发布了新的文献求助10
29秒前
韵苑完成签到,获得积分10
31秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038201
求助须知:如何正确求助?哪些是违规求助? 3575940
关于积分的说明 11373987
捐赠科研通 3305747
什么是DOI,文献DOI怎么找? 1819274
邀请新用户注册赠送积分活动 892662
科研通“疑难数据库(出版商)”最低求助积分说明 815022