Important-Data-Based DoS Attack Mechanism and Resilient H∞ Filter Design for Networked T–S Fuzzy Systems

服务拒绝攻击 网络数据包 计算机科学 模糊逻辑 模型攻击 滤波器(信号处理) 异步通信 分布式计算 互联网 计算机安全 计算机网络 人工智能 计算机视觉 万维网
作者
Xun Wang,Engang Tian,Wei Xing Zheng,Xiangpeng Xie
出处
期刊:IEEE transactions on cybernetics [Institute of Electrical and Electronics Engineers]
卷期号:54 (5): 3352-3362 被引量:53
标识
DOI:10.1109/tcyb.2023.3285526
摘要

This article is concerned with the security problems for networked Takagi-Sugeno (T-S) fuzzy systems with asynchronous premise constraints. The primary objective of this article is twofold. First, a novel important-data-based (IDB) denial-of-service (DoS) attack mechanism is proposed from the perspective of the adversary for the first time to reinforce the destructive effect of the DoS attacks. Different from most existing DoS attack models, the proposed attack mechanism can utilize the information of packets, evaluate the importance degree of packets, and only attack the most "important" ones. As such, a larger system performance degradation can be expected. Second, corresponding to the proposed IDB DoS mechanism, a resilient H fuzzy filter is designed from the defender's point of view to alleviate the negative effect of the attack. Furthermore, since the defender does not know the attack parameter, an algorithm is designed to estimate it. In a word, a unified attack-defense framework is developed in this article for networked T-S fuzzy systems with asynchronous premise constraints. With the help of the Lyapunov functional method, sufficient conditions are successfully established to compute the desired filtering gains and ensure the H performance of the filtering error system. Finally, two examples are exploited to demonstrate the destructiveness of the proposed IDB DoS attack and the usefulness of the developed resilient H filter.
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
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
森森完成签到,获得积分10
1秒前
1秒前
Ava应助温暖的颜演采纳,获得10
1秒前
Ky_Mac应助Lee采纳,获得20
2秒前
ww发布了新的文献求助10
2秒前
2秒前
3秒前
抗氧剂完成签到,获得积分20
4秒前
直率的玉米完成签到 ,获得积分10
4秒前
英俊的铭应助ZMl采纳,获得10
4秒前
4秒前
爆米花应助wh雨采纳,获得10
4秒前
丘比特应助冷水鱼采纳,获得10
4秒前
LiZH完成签到,获得积分10
5秒前
6秒前
传奇3应助ivy采纳,获得10
6秒前
6秒前
Persepolis完成签到,获得积分10
6秒前
mm完成签到,获得积分10
7秒前
量子星尘发布了新的文献求助10
7秒前
小蘑菇应助sweettt3采纳,获得10
7秒前
9秒前
花粉过敏发布了新的文献求助10
9秒前
xianglinnnn完成签到,获得积分10
9秒前
陈2026完成签到,获得积分10
9秒前
xmj发布了新的文献求助10
9秒前
9秒前
善学以致用应助脆脆鲨采纳,获得10
9秒前
跳跃完成签到,获得积分10
9秒前
Wang完成签到,获得积分0
11秒前
11秒前
sssssss发布了新的文献求助10
11秒前
扶瑶可接发布了新的文献求助10
11秒前
12秒前
罐装冰块完成签到,获得积分10
12秒前
shiizii应助激昂的吐司采纳,获得10
12秒前
12秒前
12秒前
淡淡大山完成签到,获得积分20
12秒前
kangnakangna完成签到,获得积分10
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Russian Foreign Policy: Change and Continuity 800
Real World Research, 5th Edition 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
Superabsorbent Polymers 700
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5710603
求助须知:如何正确求助?哪些是违规求助? 5199800
关于积分的说明 15261321
捐赠科研通 4863194
什么是DOI,文献DOI怎么找? 2610478
邀请新用户注册赠送积分活动 1560802
关于科研通互助平台的介绍 1518423