This paper investigates the system security problem of cyber-physical systems (CPSs), which is not only more practical but also more significant to deal with than the detecting faults problem. The purpose of this paper is to find an optimal attack strategy that maximizes the output error of the attacked system with low energy consumption. Based on a general model of linear time-invariant systems and a key technical lemma, a new optimal attack strategy for the meticulously designed false data injection attack is constructed. It is worth mentioning that compared with the existing model-based attack strategies, the designed one is more general and the corresponding attack strategy is more easily implemented when system states and external input are inaccessible. Key to overcoming the inaccessible information, a dynamic observer in the form of Luenberger is constructed. Finally, a networked magnetic levitation steel ball movement system is applied to illustrate the effectiveness of the proposed scheme.
{"title":"Optimal injection attack strategy for cyber-physical systems: a dynamic feedback approach","authors":"Sheng Gao, Hao Zhang, Zhuping Wang, Chao Huang","doi":"10.1051/sands/2022005","DOIUrl":"https://doi.org/10.1051/sands/2022005","url":null,"abstract":"This paper investigates the system security problem of cyber-physical systems (CPSs), which is not only more practical but also more significant to deal with than the detecting faults problem. The purpose of this paper is to find an optimal attack strategy that maximizes the output error of the attacked system with low energy consumption. Based on a general model of linear time-invariant systems and a key technical lemma, a new optimal attack strategy for the meticulously designed false data injection attack is constructed. It is worth mentioning that compared with the existing model-based attack strategies, the designed one is more general and the corresponding attack strategy is more easily implemented when system states and external input are inaccessible. Key to overcoming the inaccessible information, a dynamic observer in the form of Luenberger is constructed. Finally, a networked magnetic levitation steel ball movement system is applied to illustrate the effectiveness of the proposed scheme.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"129 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89201503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, large numbers of smart sensors (e.g., road-side cameras) which communicate with nearby base stations could launch distributed denial of services (DDoS) attack storms in intelligent transportation systems. DDoS attacks disable the services provided by base stations. Thus in this paper, considering the uneven communication traffic flows and privacy preserving, we give a hidden Markov model-based prediction model by utilizing the multi-step characteristic of DDoS with a federated learning framework to predict whether DDoS attacks will happen on base stations in the future. However, in the federated learning, we need to consider the problem of poisoning attacks due to malicious participants. The poisoning attacks will lead to the intelligent transportation systems paralysis without security protection. Traditional poisoning attacks mainly apply to the classification model with labeled data. In this paper, we propose a reinforcement learning-based poisoning method specifically for poisoning the prediction model with unlabeled data. Besides, previous related defense strategies rely on validation datasets with labeled data in the server. However, it is unrealistic since the local training datasets are not uploaded to the server due to privacy preserving, and our datasets are also unlabeled. Furthermore, we give a validation dataset-free defense strategy based on Dempster–Shafer (D–S) evidence theory avoiding anomaly aggregation to obtain a robust global model for precise DDoS prediction. In our experiments, we simulate 3000 points in combination with DARPA2000 dataset to carry out evaluations. The results indicate that our poisoning method can successfully poison the global prediction model with unlabeled data in a short time. Meanwhile, we compare our proposed defense algorithm with three popularly used defense algorithms. The results show that our defense method has a high accuracy rate of excluding poisoners and can obtain a high attack prediction probability.
{"title":"Efficient poisoning attacks and defenses for unlabeled data in DDoS prediction of intelligent transportation systems","authors":"Zhong Li, Xianke Wu, Changjun Jiang","doi":"10.1051/sands/2022003","DOIUrl":"https://doi.org/10.1051/sands/2022003","url":null,"abstract":"Nowadays, large numbers of smart sensors (e.g., road-side cameras) which communicate with nearby base stations could launch distributed denial of services (DDoS) attack storms in intelligent transportation systems. DDoS attacks disable the services provided by base stations. Thus in this paper, considering the uneven communication traffic flows and privacy preserving, we give a hidden Markov model-based prediction model by utilizing the multi-step characteristic of DDoS with a federated learning framework to predict whether DDoS attacks will happen on base stations in the future. However, in the federated learning, we need to consider the problem of poisoning attacks due to malicious participants. The poisoning attacks will lead to the intelligent transportation systems paralysis without security protection. Traditional poisoning attacks mainly apply to the classification model with labeled data. In this paper, we propose a reinforcement learning-based poisoning method specifically for poisoning the prediction model with unlabeled data. Besides, previous related defense strategies rely on validation datasets with labeled data in the server. However, it is unrealistic since the local training datasets are not uploaded to the server due to privacy preserving, and our datasets are also unlabeled. Furthermore, we give a validation dataset-free defense strategy based on Dempster–Shafer (D–S) evidence theory avoiding anomaly aggregation to obtain a robust global model for precise DDoS prediction. In our experiments, we simulate 3000 points in combination with DARPA2000 dataset to carry out evaluations. The results indicate that our poisoning method can successfully poison the global prediction model with unlabeled data in a short time. Meanwhile, we compare our proposed defense algorithm with three popularly used defense algorithms. The results show that our defense method has a high accuracy rate of excluding poisoners and can obtain a high attack prediction probability.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90351526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Drug Testing In The Workplace: An Update","authors":"Patricia S. Wall","doi":"10.19030/JABR.V8I2.6175","DOIUrl":"https://doi.org/10.19030/JABR.V8I2.6175","url":null,"abstract":"","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"8 1","pages":"127-132"},"PeriodicalIF":0.0,"publicationDate":"2011-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68231577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-01-01DOI: 10.3745/KIPSTC.2004.11C.3.293
Kyoung-Ja Kim, Tae-Mu Chang
Ad hoc networks are groups of mobile hosts without any fixed infrastructure. Frequent changes in network topology owing to node mobility make these networks very difficult to manage. Therefore, enhancing the reliability of routing paths in ad hoc networks gets more important. In this paper, we propose a ZRP(Zone Routing Protocol)-based route discovery scheme that can not only reduce the total hops of routing path, but Improve security through authentications between two nodes. And to solve the problem in maintenance of routing paths owing to frequent changes of the network topology, we adopt a query control mechanism. The effectiveness of our scheme is shown by simulation methods.
{"title":"A ZRP Based Reliable Route Discovery Scheme in Ad-Hoc Networks","authors":"Kyoung-Ja Kim, Tae-Mu Chang","doi":"10.3745/KIPSTC.2004.11C.3.293","DOIUrl":"https://doi.org/10.3745/KIPSTC.2004.11C.3.293","url":null,"abstract":"Ad hoc networks are groups of mobile hosts without any fixed infrastructure. Frequent changes in network topology owing to node mobility make these networks very difficult to manage. Therefore, enhancing the reliability of routing paths in ad hoc networks gets more important. In this paper, we propose a ZRP(Zone Routing Protocol)-based route discovery scheme that can not only reduce the total hops of routing path, but Improve security through authentications between two nodes. And to solve the problem in maintenance of routing paths owing to frequent changes of the network topology, we adopt a query control mechanism. The effectiveness of our scheme is shown by simulation methods.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"12 1","pages":"325-331"},"PeriodicalIF":0.0,"publicationDate":"2004-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89871976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Staff training helps hospital deal with two negative incidents.","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"21 8","pages":"13-4"},"PeriodicalIF":0.0,"publicationDate":"2000-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21966698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Among the numerous products and systems available from security product manufacturers, two have been involved for years with day-to-day activities that, if properly carried out, can result in a more secure hospital environment for individuals and greater protection from product loss or liability--guard tour reporting and key control. This report gives details on recent advances in such systems, the costs involved, and how individual hospitals are using them.
{"title":"New developments in guard tour reporting and employee key control.","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Among the numerous products and systems available from security product manufacturers, two have been involved for years with day-to-day activities that, if properly carried out, can result in a more secure hospital environment for individuals and greater protection from product loss or liability--guard tour reporting and key control. This report gives details on recent advances in such systems, the costs involved, and how individual hospitals are using them.</p>","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"21 8","pages":"5-8"},"PeriodicalIF":0.0,"publicationDate":"2000-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21966699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Training seen key to limiting gang activity in your hospital.","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"21 8","pages":"8-9"},"PeriodicalIF":0.0,"publicationDate":"2000-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21966700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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