在早期系统设计中评估复杂网络物理系统中网络和物理恶意攻击的后果

B. O’Halloran, N. Papakonstantinou, Douglas L. Van Bossuyt
{"title":"在早期系统设计中评估复杂网络物理系统中网络和物理恶意攻击的后果","authors":"B. O’Halloran, N. Papakonstantinou, Douglas L. Van Bossuyt","doi":"10.1109/INDIN.2018.8471937","DOIUrl":null,"url":null,"abstract":"This research contributes to the lifecycle assessment of complex cyber-physical systems (CCPSs) to better understand and mitigate risks of malicious attacks through design. This assessment capability is proposed during the early phase of engineering design where significant decision-making flexibility exists. This is done by assessing potential malicious attacks carried out by humans interacting with the system across all phases of the system’s lifecycle. We propose a novel quantification of an attacker-centric risk, then optimize the large set of attacks using a genetic algorithm. This research is motivated by the increased vulnerability of CCPSs due to their increasingly complex interconnected and digitally connected nature. A specific area of interest for CCPSs has been the increasing degree of connectedness. For example, several recent federal reports indicate that significant risk exists in the design of commercial aircraft where the entertainment system is connected to the avionics through a central network. The result is an increased ability to attack a specific subsystem or component to produce system failure. These findings, as well as others, have led to a significant concern with malicious attacks to target critical components of the CCPS. While assessments can be performed on a CCPS during the later phases of engineering design, techniques are currently not available during the early phase. We propose an assessment technique which is useful to practitioners during conceptual design. In this research, we assess a nuclear power plant as an example CCPS. The resulting methodology provides useful insight to the risks of malicious attacks throughout the system’s lifecycle.","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"238 1","pages":"733-740"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Assessing the Consequence of Cyber and Physical Malicious Attacks in Complex, Cyber-Physical Systems During Early System Design\",\"authors\":\"B. O’Halloran, N. Papakonstantinou, Douglas L. Van Bossuyt\",\"doi\":\"10.1109/INDIN.2018.8471937\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research contributes to the lifecycle assessment of complex cyber-physical systems (CCPSs) to better understand and mitigate risks of malicious attacks through design. This assessment capability is proposed during the early phase of engineering design where significant decision-making flexibility exists. This is done by assessing potential malicious attacks carried out by humans interacting with the system across all phases of the system’s lifecycle. We propose a novel quantification of an attacker-centric risk, then optimize the large set of attacks using a genetic algorithm. This research is motivated by the increased vulnerability of CCPSs due to their increasingly complex interconnected and digitally connected nature. A specific area of interest for CCPSs has been the increasing degree of connectedness. For example, several recent federal reports indicate that significant risk exists in the design of commercial aircraft where the entertainment system is connected to the avionics through a central network. The result is an increased ability to attack a specific subsystem or component to produce system failure. These findings, as well as others, have led to a significant concern with malicious attacks to target critical components of the CCPS. While assessments can be performed on a CCPS during the later phases of engineering design, techniques are currently not available during the early phase. We propose an assessment technique which is useful to practitioners during conceptual design. In this research, we assess a nuclear power plant as an example CCPS. The resulting methodology provides useful insight to the risks of malicious attacks throughout the system’s lifecycle.\",\"PeriodicalId\":6467,\"journal\":{\"name\":\"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)\",\"volume\":\"238 1\",\"pages\":\"733-740\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDIN.2018.8471937\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN.2018.8471937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

本研究有助于复杂网络物理系统(ccps)的生命周期评估,以便通过设计更好地理解和减轻恶意攻击的风险。这种评估能力是在工程设计的早期阶段提出的,在这个阶段存在很大的决策灵活性。这是通过评估在系统生命周期的所有阶段与系统交互的人员执行的潜在恶意攻击来完成的。我们提出了一种新的以攻击者为中心的风险量化方法,然后使用遗传算法优化大型攻击集。由于ccps日益复杂的互联和数字连接性质,它们的脆弱性日益增加,这促使了本研究的开展。ccps感兴趣的一个特定领域是不断增加的连通性。例如,最近的几份联邦报告表明,在娱乐系统通过中央网络连接到航空电子设备的商用飞机的设计中存在重大风险。其结果是攻击特定子系统或组件以产生系统故障的能力增加。这些发现,以及其他发现,引起了对针对CCPS关键组件的恶意攻击的极大关注。虽然在工程设计的后期阶段可以对CCPS进行评估,但目前在早期阶段还没有可用的技术。我们提出了一种评估技术,在概念设计中对实践者有用。本研究以某核电厂为例,对CCPS进行评估。由此产生的方法对整个系统生命周期中的恶意攻击风险提供了有用的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Assessing the Consequence of Cyber and Physical Malicious Attacks in Complex, Cyber-Physical Systems During Early System Design
This research contributes to the lifecycle assessment of complex cyber-physical systems (CCPSs) to better understand and mitigate risks of malicious attacks through design. This assessment capability is proposed during the early phase of engineering design where significant decision-making flexibility exists. This is done by assessing potential malicious attacks carried out by humans interacting with the system across all phases of the system’s lifecycle. We propose a novel quantification of an attacker-centric risk, then optimize the large set of attacks using a genetic algorithm. This research is motivated by the increased vulnerability of CCPSs due to their increasingly complex interconnected and digitally connected nature. A specific area of interest for CCPSs has been the increasing degree of connectedness. For example, several recent federal reports indicate that significant risk exists in the design of commercial aircraft where the entertainment system is connected to the avionics through a central network. The result is an increased ability to attack a specific subsystem or component to produce system failure. These findings, as well as others, have led to a significant concern with malicious attacks to target critical components of the CCPS. While assessments can be performed on a CCPS during the later phases of engineering design, techniques are currently not available during the early phase. We propose an assessment technique which is useful to practitioners during conceptual design. In this research, we assess a nuclear power plant as an example CCPS. The resulting methodology provides useful insight to the risks of malicious attacks throughout the system’s lifecycle.
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
期刊最新文献
ADAPT - A decision-model-based Approach for Modeling Collaborative Assembly and Manufacturing Tasks Grey-box Model Identification and Fault Detection of Wind Turbines Using Artificial Neural Networks An Algorithmic Method for Tampering-Proof and Privacy-Preserving Smart Metering Digital Transformation as the Subject of Discursive Analysis Condition monitoring of wind-power units using the Derivative-free nonlinear Kalman Filter
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1