IoTDI 2017 : 2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation : proceedings : 18-20 April 2017, Pittsburgh, Pennsylvania, USA. IoTDI (Conference) (2nd : 2017 : Pittsburgh, Pa.)最新文献
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Pub Date : 2018-04-17DOI: 10.1109/IoTDI.2018.00036
Adeilson Marques da Silva Cardoso, R. Lopes, A. Teles, F. B. V. Magalhaes
With the Internet of Things expansion, there has been an increase in the development of services and applications that use context-aware devices incorporated into smart environments. Those devices produce large quantities of data and demand faster and more precise defense mechanisms. Complex Event Processing (CEP) is an emerging and promising technology that allows real-time analysis of continuous data-steams. In this work, we proposed and developed a DDoS (Distributed Denial of Service) detection system and evaluated its performance running on a Raspberry Pi. The results show that the system can be executed on devices with reduced computational power and that CEP is a viable solution to improve the real-time performance on the detection of DDoS attacks on IoT environments.
{"title":"Poster Abstract: Real-Time DDoS Detection Based on Complex Event Processing for IoT","authors":"Adeilson Marques da Silva Cardoso, R. Lopes, A. Teles, F. B. V. Magalhaes","doi":"10.1109/IoTDI.2018.00036","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00036","url":null,"abstract":"With the Internet of Things expansion, there has been an increase in the development of services and applications that use context-aware devices incorporated into smart environments. Those devices produce large quantities of data and demand faster and more precise defense mechanisms. Complex Event Processing (CEP) is an emerging and promising technology that allows real-time analysis of continuous data-steams. In this work, we proposed and developed a DDoS (Distributed Denial of Service) detection system and evaluated its performance running on a Raspberry Pi. The results show that the system can be executed on devices with reduced computational power and that CEP is a viable solution to improve the real-time performance on the detection of DDoS attacks on IoT environments.","PeriodicalId":92227,"journal":{"name":"IoTDI 2017 : 2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation : proceedings : 18-20 April 2017, Pittsburgh, Pennsylvania, USA. IoTDI (Conference) (2nd : 2017 : Pittsburgh, Pa.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88060735","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}
Amr Alanwar, Moustafa Alzantot, Bo-Jhang Ho, Paul Martin, Mani Srivastava
Although different interaction modalities have been proposed in the field of human-computer interface (HCI), only a few of these techniques could reach the end users because of scalability and usability issues. Given the popularity and the growing number of IoT devices, selecting one out of many devices becomes a hurdle in a typical smarthome environment. Therefore, an easy-to-learn, scalable, and non-intrusive interaction modality has to be explored. In this paper, we propose a pointing approach to interact with devices, as pointing is arguably a natural way for device selection. We introduce SeleCon for device selection and control which uses an ultra-wideband (UWB) equipped smartwatch. To interact with a device in our system, people can point to the device to select it then draw a hand gesture in the air to specify a control action. To this end, SeleCon employs inertial sensors for pointing gesture detection and a UWB transceiver for identifying the selected device from ranging measurements. Furthermore, SeleCon supports an alphabet of gestures that can be used for controlling the selected devices. We performed our experiment in a 9m-by-10m lab space with eight deployed devices. The results demonstrate that SeleCon can achieve 84.5% accuracy for device selection and 97% accuracy for hand gesture recognition. We also show that SeleCon is power efficient to sustain daily use by turning off the UWB transceiver, when a user's wrist is stationary.
{"title":"SeleCon: Scalable IoT Device Selection and Control Using Hand Gestures.","authors":"Amr Alanwar, Moustafa Alzantot, Bo-Jhang Ho, Paul Martin, Mani Srivastava","doi":"10.1145/3054977.3054981","DOIUrl":"https://doi.org/10.1145/3054977.3054981","url":null,"abstract":"<p><p>Although different interaction modalities have been proposed in the field of human-computer interface (HCI), only a few of these techniques could reach the end users because of scalability and usability issues. Given the popularity and the growing number of IoT devices, selecting one out of many devices becomes a hurdle in a typical smarthome environment. Therefore, an easy-to-learn, scalable, and non-intrusive interaction modality has to be explored. In this paper, we propose a <i>pointing</i> approach to interact with devices, as pointing is arguably a natural way for device selection. We introduce SeleCon for device selection and control which uses an ultra-wideband (UWB) equipped smartwatch. To interact with a device in our system, people can point to the device to select it then draw a hand gesture in the air to specify a control action. To this end, SeleCon employs inertial sensors for pointing gesture detection and a UWB transceiver for identifying the selected device from ranging measurements. Furthermore, SeleCon supports an alphabet of gestures that can be used for controlling the selected devices. We performed our experiment in a 9<i>m</i>-by-10<i>m</i> lab space with eight deployed devices. The results demonstrate that SeleCon can achieve 84.5% accuracy for device selection and 97% accuracy for hand gesture recognition. We also show that SeleCon is power efficient to sustain daily use by turning off the UWB transceiver, when a user's wrist is stationary.</p>","PeriodicalId":92227,"journal":{"name":"IoTDI 2017 : 2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation : proceedings : 18-20 April 2017, Pittsburgh, Pennsylvania, USA. IoTDI (Conference) (2nd : 2017 : Pittsburgh, Pa.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3054977.3054981","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36032216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IoTDI 2017 : 2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation : proceedings : 18-20 April 2017, Pittsburgh, Pennsylvania, USA. IoTDI (Conference) (2nd : 2017 : Pittsburgh, Pa.)
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