Chenguan Xu, Wenqing Li, Yao Rao, Bei Qi, Bin Yang, Zhongdong Wang
{"title":"Coordinative energy efficiency improvement of buildings based on deep reinforcement learning","authors":"Chenguan Xu, Wenqing Li, Yao Rao, Bei Qi, Bin Yang, Zhongdong Wang","doi":"10.1080/23335777.2022.2066181","DOIUrl":"https://doi.org/10.1080/23335777.2022.2066181","url":null,"abstract":"ABSTRACT Due to the uncertainty of user’s behaviour and other conditions, the design of energy efficiency improvement methods in buildings is challenging. In this paper, a building energy management method based on deep reinforcement learning is proposed, which solves the energy scheduling problem of buildings with renewable sources and energy storage system and minimises electricity costs while maintaining the user’s comfort. Different from model-based methods, the proposed DRL agent makes decisions only by observing the measurable information without considering the dynamic of the building environment. Simulations based on real data verify the effectiveness of the proposed method.","PeriodicalId":37058,"journal":{"name":"Cyber-Physical Systems","volume":"9 1","pages":"260 - 272"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90242220","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":"Confidentiality attacks against encrypted control systems","authors":"A. Naseri, Walter Lucia, Amr Youssef","doi":"10.1080/23335777.2022.2051209","DOIUrl":"https://doi.org/10.1080/23335777.2022.2051209","url":null,"abstract":"ABSTRACT Encrypted control systems were introduced to enhance the security of cyber-physical systems, which outsource control action computations to a third-party platform. To protect the confidentiality of the transmitted data, homomorphic encryption schemes are particularly appealing for their capability of allowing computations on encrypted data. By considering the popular ElGamal and Paillier encryption schemes, this paper shows that encrypted control systems are vulnerable to attackers leveraging the inherently small domains of the plaintext data in control systems and the randomisation process required to make the utilised ciphers semantically secure. Finally, we present some countermeasures to defend against these attacks.","PeriodicalId":37058,"journal":{"name":"Cyber-Physical Systems","volume":"14 1","pages":"224 - 243"},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81140912","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}
Hengshuo Liang, Lauren Burgess, Weixian Liao, Erik Blasch, Wei Yu
{"title":"Deep Learning Assist IoT Search Engine for Disaster Damage Assessment","authors":"Hengshuo Liang, Lauren Burgess, Weixian Liao, Erik Blasch, Wei Yu","doi":"10.1080/23335777.2022.2051210","DOIUrl":"https://doi.org/10.1080/23335777.2022.2051210","url":null,"abstract":"ABSTRACT In this paper, we address the issue of disaster damage assessments using deep learning (DL) techniques. Specifically, we propose integrating DL techniques into the Internet of Things Search Engine (IoTSE) system to carry out disaster damage assessment. Our approach is to design two scenarios, Single and Complex Event Settings, to complete performance validation using four Convolutional Neural Network (CNN) models. These two scenarios are designed with three possible network services. Our experimental results confirm that all four CNN models can learn each label during the single event setting well. Whereas, with complex event settings, the CNN models have learning difficulty because multiple events have closely related labels.","PeriodicalId":37058,"journal":{"name":"Cyber-Physical Systems","volume":"19 1","pages":"313 - 337"},"PeriodicalIF":0.0,"publicationDate":"2022-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82968909","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":"Towards an intrusion detection system for detecting web attacks based on an ensemble of filter feature selection techniques","authors":"D. Kshirsagar, Sandeep Kumar","doi":"10.1080/23335777.2021.2023651","DOIUrl":"https://doi.org/10.1080/23335777.2021.2023651","url":null,"abstract":"ABSTRACT The use of machine learning models in intrusion detection systems (IDSs) takes more time to build the model with many features and degrade the performance. The present paper proposes an ensemble of filter feature selection techniques (EFFST) to obtain a significant feature subset for web attack detection by selecting one-fourth split of the ranked features. The experimentation on the CICIDS 2017 dataset shows that the proposed EFFST method provides a detection rate of 99.9909%, with J48 using 24 features. The system’s performance is compared to the original features and traditional relevant feature selection methods employed in IDSs..","PeriodicalId":37058,"journal":{"name":"Cyber-Physical Systems","volume":"36 1","pages":"244 - 259"},"PeriodicalIF":0.0,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83141566","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":"Fixed-point iterative approach for solving linear Diophantine systems with bounds on the variables","authors":"Haocheng Yu, Luyao Yang, Jinyu Dai, Baoping Jiang, Zhengtian Wu, Shuxian Zhu","doi":"10.1080/23335777.2021.2022765","DOIUrl":"https://doi.org/10.1080/23335777.2021.2022765","url":null,"abstract":"ABSTRACT Systems of linear Diophantine equations arise from several applications. Scholars have given attention to such systems and come up with several effective solutions. A new approach, called the fixed-point iterative method, was proposed to solve linear Diophantine equations with lower and upper bounds on the variables. Two steps are involved in solving this problem. First, the problem is transformed into a polytope judgment problem . Then, the approach is used to judge the existence of an integer point in the polytope. Compared with the branch-and-bound method, results show that the approach is feasible and effective for solving linear Diophantine systems.","PeriodicalId":37058,"journal":{"name":"Cyber-Physical Systems","volume":"5 1","pages":"376 - 389"},"PeriodicalIF":0.0,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82749540","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":"Evolving uncertainty in healthcare service interactions during COVID-19: Artificial Intelligence - a threat or support to value cocreation?","authors":"S. Saxena, Amritesh","doi":"10.1016/B978-0-12-824557-6.00014-5","DOIUrl":"https://doi.org/10.1016/B978-0-12-824557-6.00014-5","url":null,"abstract":"","PeriodicalId":37058,"journal":{"name":"Cyber-Physical Systems","volume":"40 1","pages":"93 - 116"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81391165","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}
Basant Agarwal, Vaishnavi Sharma, P. Harjule, Vinita Tiwari, Ashish Sharma
{"title":"The COVID-19 outbreak: social media sentiment analysis of public reactions with a multidimensional perspective","authors":"Basant Agarwal, Vaishnavi Sharma, P. Harjule, Vinita Tiwari, Ashish Sharma","doi":"10.1016/B978-0-12-824557-6.00013-3","DOIUrl":"https://doi.org/10.1016/B978-0-12-824557-6.00013-3","url":null,"abstract":"","PeriodicalId":37058,"journal":{"name":"Cyber-Physical Systems","volume":"52 1","pages":"117 - 138"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78625436","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}
Hrishikesh Shenai, Jay Gala, Kaustubh Y. Kekre, P. Chitale, R. Karani
{"title":"Combating COVID-19 using object detection techniques for next-generation autonomous systems","authors":"Hrishikesh Shenai, Jay Gala, Kaustubh Y. Kekre, P. Chitale, R. Karani","doi":"10.1016/B978-0-12-824557-6.00007-8","DOIUrl":"https://doi.org/10.1016/B978-0-12-824557-6.00007-8","url":null,"abstract":"","PeriodicalId":37058,"journal":{"name":"Cyber-Physical Systems","volume":"35 1","pages":"55 - 73"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72720792","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":"Rapid medical guideline systems for COVID-19 using database-centric modeling and validation of cyber-physical systems","authors":"Mani Padmanabhan","doi":"10.1016/B978-0-12-824557-6.00012-1","DOIUrl":"https://doi.org/10.1016/B978-0-12-824557-6.00012-1","url":null,"abstract":"","PeriodicalId":37058,"journal":{"name":"Cyber-Physical Systems","volume":"37 1","pages":"161 - 170"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86862625","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}