海报:愿蜂群与你同在:传感器欺骗攻击无人机蜂群

Yingao Yao, Pritam Dash, K. Pattabiraman
{"title":"海报:愿蜂群与你同在:传感器欺骗攻击无人机蜂群","authors":"Yingao Yao, Pritam Dash, K. Pattabiraman","doi":"10.1145/3548606.3563535","DOIUrl":null,"url":null,"abstract":"Swarm robotics, particularly drone swarms, are used in various safety-critical tasks. While a lot of attention has been paid to improving swarm control algorithms for improved intelligence, the security implications of various design choices in swarm control algorithms have not been studied. We highlight how an attacker can exploit the vulnerabilities in swarm control algorithms to disrupt drone swarms. Specifically, we show that the attacker can target one swarm member (target drone) through sensor spoofing attacks, and indirectly cause other swarm members (victim drones) to veer off from their course, and potentially resulting in a crash. Our attack cannot be prevented by traditional software security techniques, and it is stealthy in nature as it causes seemingly benign deviations in drone swarms. Our initial results show that spoofing the position of a target drone by 5m is sufficient to cause other drones to crash into a front obstacle. Overall, our attack achieves 76.67% and 93.33% success rate with 5m and 10m spoofing deviation respectively.","PeriodicalId":435197,"journal":{"name":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Poster: May the Swarm Be With You: Sensor Spoofing Attacks Against Drone Swarms\",\"authors\":\"Yingao Yao, Pritam Dash, K. Pattabiraman\",\"doi\":\"10.1145/3548606.3563535\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Swarm robotics, particularly drone swarms, are used in various safety-critical tasks. While a lot of attention has been paid to improving swarm control algorithms for improved intelligence, the security implications of various design choices in swarm control algorithms have not been studied. We highlight how an attacker can exploit the vulnerabilities in swarm control algorithms to disrupt drone swarms. Specifically, we show that the attacker can target one swarm member (target drone) through sensor spoofing attacks, and indirectly cause other swarm members (victim drones) to veer off from their course, and potentially resulting in a crash. Our attack cannot be prevented by traditional software security techniques, and it is stealthy in nature as it causes seemingly benign deviations in drone swarms. Our initial results show that spoofing the position of a target drone by 5m is sufficient to cause other drones to crash into a front obstacle. Overall, our attack achieves 76.67% and 93.33% success rate with 5m and 10m spoofing deviation respectively.\",\"PeriodicalId\":435197,\"journal\":{\"name\":\"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3548606.3563535\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3548606.3563535","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

蜂群机器人,尤其是无人机蜂群,被用于各种安全关键任务。虽然人们对改进群控制算法以提高智能已经给予了很多关注,但对群控制算法中各种设计选择的安全影响尚未进行研究。我们强调了攻击者如何利用群控制算法中的漏洞来破坏无人机群。具体来说,我们表明攻击者可以通过传感器欺骗攻击瞄准一个群体成员(目标无人机),并间接导致其他群体成员(受害者无人机)偏离他们的路线,并可能导致坠机。我们的攻击无法被传统的软件安全技术所阻止,它本质上是隐形的,因为它会在无人机群中引起看似良性的偏差。我们的初步结果表明,将目标无人机的位置欺骗5米足以导致其他无人机撞向前方的障碍物。总体而言,我们的攻击成功率分别为76.67%和93.33%,欺骗偏差分别为5m和10m。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Poster: May the Swarm Be With You: Sensor Spoofing Attacks Against Drone Swarms
Swarm robotics, particularly drone swarms, are used in various safety-critical tasks. While a lot of attention has been paid to improving swarm control algorithms for improved intelligence, the security implications of various design choices in swarm control algorithms have not been studied. We highlight how an attacker can exploit the vulnerabilities in swarm control algorithms to disrupt drone swarms. Specifically, we show that the attacker can target one swarm member (target drone) through sensor spoofing attacks, and indirectly cause other swarm members (victim drones) to veer off from their course, and potentially resulting in a crash. Our attack cannot be prevented by traditional software security techniques, and it is stealthy in nature as it causes seemingly benign deviations in drone swarms. Our initial results show that spoofing the position of a target drone by 5m is sufficient to cause other drones to crash into a front obstacle. Overall, our attack achieves 76.67% and 93.33% success rate with 5m and 10m spoofing deviation respectively.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信