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2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)最新文献

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ETSecIoT 2020 Breaker Page ETSecIoT 2020断路器页面
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/etseciot50046.2020.00003
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引用次数: 0
Message from the Chairs 主席致辞
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/etseciot50046.2020.00011
{"title":"Message from the Chairs","authors":"","doi":"10.1109/etseciot50046.2020.00011","DOIUrl":"https://doi.org/10.1109/etseciot50046.2020.00011","url":null,"abstract":"","PeriodicalId":193628,"journal":{"name":"2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)","volume":" 371","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141218802","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}
引用次数: 0
Progressive Monitoring of IoT Networks Using SDN and Cost-Effective Traffic Signatures 使用SDN和经济高效的流量签名逐步监控物联网网络
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/ETSecIoT50046.2020.00005
Arman Pashamokhtari, H. Gharakheili, V. Sivaraman
{"title":"Progressive Monitoring of IoT Networks Using SDN and Cost-Effective Traffic Signatures","authors":"Arman Pashamokhtari, H. Gharakheili, V. Sivaraman","doi":"10.1109/ETSecIoT50046.2020.00005","DOIUrl":"https://doi.org/10.1109/ETSecIoT50046.2020.00005","url":null,"abstract":"IoT networks continue to expand in various domains, from smart homes and campuses to smart cities and critical infrastructures. It has been shown that IoT devices typically lack appropriate security measures embedded, and hence are increasingly becoming the target of sophisticated cyber-attacks. Also, these devices are heterogeneous in their network communications that makes it difficult for operators of smart environments to manage them at scale. Existing monitoring solutions may perform well in certain environments, however, they do not scale cost-effectively and are inflexible to changes due to their static use of models. In this paper1, we use SDN to dynamically monitor a selected portion of IoT packets or flows, and develop specialized models to learn corresponding traffic signatures. Our first contribution develops a progressive inference pipeline, comprising a number of machine-learning models each is specialized in certain features of IoT traffic. Our inference engine dynamically obtains selected telemetry, including a subset of traffic or flow counters, using SDN techniques. Our second contribution develops three supervised multi-class classifiers, two are protocol specialists trained by packet-based features and one is flow-based model trained by behavioral characteristics of ten unidirectional flows. Our third contribution evaluates the performance of our scheme by replaying real traffic traces of 26 IoT devices on to an SDN switching simulator in conjunction with three trained Random Forest models. Our system yields an overall accuracy of 99.4%. We also integrate our system with an off-the-shelf IDS (Zeek) to flag TCP flood and reflection attacks by inspecting only the suspicious device network traffic.","PeriodicalId":193628,"journal":{"name":"2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116113451","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}
引用次数: 8
An Efficient Privacy-preserving IoT System for Face Recognition 一种高效的保护隐私的物联网人脸识别系统
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/ETSecIoT50046.2020.00006
Wanli Xue, Wen Hu, Praveen Gauranvaram, A. Seneviratne, Sanjay Jha
{"title":"An Efficient Privacy-preserving IoT System for Face Recognition","authors":"Wanli Xue, Wen Hu, Praveen Gauranvaram, A. Seneviratne, Sanjay Jha","doi":"10.1109/ETSecIoT50046.2020.00006","DOIUrl":"https://doi.org/10.1109/ETSecIoT50046.2020.00006","url":null,"abstract":"Face recognition (FR) has become increasingly important in many real-world IoT applications like public safety surveillance camera system or CCTV, person re-identification system and face-based authentication system. The privacy of face images has been a growing concern, not only in the collected face dataset stored in the cloud platforms but also in its everyday use. However, most existing schemes (e.g., deep learning with differential privacy [1]) build privacy-preserving analytics models from the stored face data while ignoring the privacy concern in end devices. In this paper, we propose a novel efficient privacy-preserving face representation scheme in the Bloom filter space, which can satisfy the resource limits from IoT devices. Our solution allows analytics tasks on privacy-preserving face data representation but retains the high data utility on analytics (e.g., classification).","PeriodicalId":193628,"journal":{"name":"2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)","volume":"753 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120884733","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}
引用次数: 3
IoT Threat Detection Advances, Challenges and Future Directions 物联网威胁检测进展、挑战和未来方向
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/ETSecIoT50046.2020.00009
Nickson M. Karie, N. Sahri, Paul Haskell-Dowland
{"title":"IoT Threat Detection Advances, Challenges and Future Directions","authors":"Nickson M. Karie, N. Sahri, Paul Haskell-Dowland","doi":"10.1109/ETSecIoT50046.2020.00009","DOIUrl":"https://doi.org/10.1109/ETSecIoT50046.2020.00009","url":null,"abstract":"It is predicted that, the number of connected Internet of Things (IoT) devices will rise to 38.6 billion by 2025 and an estimated 50 billion by 2030. The increased deployment of IoT devices into diverse areas of our life has provided us with significant benefits such as improved quality of life and task automation. However, each time a new IoT device is deployed, new and unique security threats emerge or are introduced into the environment under which the device must operate. Instantaneous detection and mitigation of every security threat introduced by different IoT devices deployed can be very challenging. This is because many of the IoT devices are manufactured with no consideration of their security implications. In this paper therefore, we review existing literature and present IoT threat detection research advances with a focus on the various IoT security challenges as well as the current developments towards combating cyber security threats in IoT networks. However, this paper also highlights several future research directions in the IoT domain.","PeriodicalId":193628,"journal":{"name":"2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124060728","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}
引用次数: 39
ETSecIoT 2020 Index
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/etseciot50046.2020.00010
{"title":"ETSecIoT 2020 Index","authors":"","doi":"10.1109/etseciot50046.2020.00010","DOIUrl":"https://doi.org/10.1109/etseciot50046.2020.00010","url":null,"abstract":"","PeriodicalId":193628,"journal":{"name":"2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)","volume":"468 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131252144","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}
引用次数: 0
ETSecIoT 2020 TOC
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/etseciot50046.2020.00004
{"title":"ETSecIoT 2020 TOC","authors":"","doi":"10.1109/etseciot50046.2020.00004","DOIUrl":"https://doi.org/10.1109/etseciot50046.2020.00004","url":null,"abstract":"","PeriodicalId":193628,"journal":{"name":"2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134041022","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}
引用次数: 0
ETSecIoT 2020 Commentary ETSecIoT 2020 评论
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/etseciot50046.2020.00002
ETSecIoT
{"title":"ETSecIoT 2020 Commentary","authors":"ETSecIoT","doi":"10.1109/etseciot50046.2020.00002","DOIUrl":"https://doi.org/10.1109/etseciot50046.2020.00002","url":null,"abstract":"","PeriodicalId":193628,"journal":{"name":"2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134270509","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}
引用次数: 0
Security and Forensics in the Internet of Things: Research Advances and Challenges 物联网中的安全和取证:研究进展与挑战
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/ETSecIoT50046.2020.00007
Wencheng Yang, Michael N. Johnstone, L. Sikos, Song Wang
{"title":"Security and Forensics in the Internet of Things: Research Advances and Challenges","authors":"Wencheng Yang, Michael N. Johnstone, L. Sikos, Song Wang","doi":"10.1109/ETSecIoT50046.2020.00007","DOIUrl":"https://doi.org/10.1109/ETSecIoT50046.2020.00007","url":null,"abstract":"Considering the billions of Internet of Things (IoT) devices around the world, the IoT has brought convenience to people’s lives, but also created a larger attack surface. Therefore, specific attention should be paid to IoT, especially from two aspects, namely, security and forensics. Security properties, especially authentication, ensure the integrity of large amounts of data processed in IoT networks, while forensic investigations can identify, collect, and retain evidence when abuse in IoT systems occurs. Regarding these two critical aspects, this article introduces and analyzes the latest biometric-based authentication research effort in IoT, as well as some IoT forensic investigation models/frameworks. In addition, we also investigate some unresolved challenges that IoT research still faces and provide a direction for future work.","PeriodicalId":193628,"journal":{"name":"2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117060140","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}
引用次数: 9
Assessing the Suitability of Traditional Botnet Detection against Contemporary Threats 评估传统僵尸网络检测对当代威胁的适用性
2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT) Pub Date : 2020-04-01 DOI: 10.1109/ETSecIoT50046.2020.00008
Ashley Woodiss-Field, Michael N. Johnstone
{"title":"Assessing the Suitability of Traditional Botnet Detection against Contemporary Threats","authors":"Ashley Woodiss-Field, Michael N. Johnstone","doi":"10.1109/ETSecIoT50046.2020.00008","DOIUrl":"https://doi.org/10.1109/ETSecIoT50046.2020.00008","url":null,"abstract":"Botnets are groups of compromised devices used by malicious actors to perpetrate various forms of cyber-attacks. The Internet of Things involves the use and operation of (often small, low power) devices such as household appliances, industrial sensors and actuators, and media devices. Contemporary botnets have been known to target IoT devices for use in their attacks. Traditional botnet detection techniques may not be adequate in detecting contemporary botnet threats. BotMiner is one such technique. This paper discusses the attempted recreation of BotMiner and the limitations found in the context of IoT-based Botnet detection.","PeriodicalId":193628,"journal":{"name":"2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126486185","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}
引用次数: 3
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