This paper discusses the need for new security frameworks for IoT enabled remote applications. It considers real life scenario as a case study to explicitly represent the relationship between security requirements and security goals. Security as a service is a subscription model in IoT environment that needs to be customized to meet the application specific goal. This paper provides the basic idea about how to do this.
{"title":"Poster: Exploring Security as a Service for IoT Enabled Remote Application Framework","authors":"T. Bhattasali, N. Chaki","doi":"10.1145/2938559.2948769","DOIUrl":"https://doi.org/10.1145/2938559.2948769","url":null,"abstract":"This paper discusses the need for new security frameworks for IoT enabled remote applications. It considers real life scenario as a case study to explicitly represent the relationship between security requirements and security goals. Security as a service is a subscription model in IoT environment that needs to be customized to meet the application specific goal. This paper provides the basic idea about how to do this.","PeriodicalId":298684,"journal":{"name":"MobiSys '16 Companion","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128414192","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}
A cloud based, Vehicular Data Analytics Platform (VDAP) to identify unusual driving behaviors, evaluate driving habits, monitor health status of vehicles, and track fleets of vehicles is presented. The platform is capable of ingesting data from multiple sources such as On Board Diagnostics (OBD) port, GPS, sensor units, and smart phones. Initial system consists of an OBD port to Bluetooth dongle, an app running on a smartphone, and a cloud-based backend. Based on OBD data, Complex Event Processors (CEPs) at both the smartphone and backend detect and notify unsafe and anomalous events in real time.
{"title":"Demo: Cloud-Based Vehicular Data Analytics Platform","authors":"Shashika Ranga Muramudalige, H. Bandara","doi":"10.1145/2938559.2948849","DOIUrl":"https://doi.org/10.1145/2938559.2948849","url":null,"abstract":"A cloud based, Vehicular Data Analytics Platform (VDAP) to identify unusual driving behaviors, evaluate driving habits, monitor health status of vehicles, and track fleets of vehicles is presented. The platform is capable of ingesting data from multiple sources such as On Board Diagnostics (OBD) port, GPS, sensor units, and smart phones. Initial system consists of an OBD port to Bluetooth dongle, an app running on a smartphone, and a cloud-based backend. Based on OBD data, Complex Event Processors (CEPs) at both the smartphone and backend detect and notify unsafe and anomalous events in real time.","PeriodicalId":298684,"journal":{"name":"MobiSys '16 Companion","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126973941","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}
Entering the era of remote health monitoring and wearable devices, wireless body area networks (BSNs) are growing at a fast pace. However, energy restriction of micro-battery of a bio-sensor makes BANs vulnerable to malicious attacks. In this paper, we introduce a new attack entitled textit{Power Attack} exploiting the energy constraint of bio-sensors. We propose a threat model for power attack and analyze its viability in reality using Mannasim simulator.
{"title":"Poster: Power Attack in Body Area Networks: Dream or Reality?","authors":"Novia Nurain, A. Islam","doi":"10.1145/2938559.2948815","DOIUrl":"https://doi.org/10.1145/2938559.2948815","url":null,"abstract":"Entering the era of remote health monitoring and wearable devices, wireless body area networks (BSNs) are growing at a fast pace. However, energy restriction of micro-battery of a bio-sensor makes BANs vulnerable to malicious attacks. In this paper, we introduce a new attack entitled textit{Power Attack} exploiting the energy constraint of bio-sensors. We propose a threat model for power attack and analyze its viability in reality using Mannasim simulator.","PeriodicalId":298684,"journal":{"name":"MobiSys '16 Companion","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130648993","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}
Utsav Drolia, Katherine Guo, R. Gandhi, P. Narasimhan
One of the main thrusts of mobile and pervasive computing is supporting perception-based applications [1]. Perceptionbased applications are those that help users augment their understanding of the physical world through the sensors on their mobile devices, e.g. augmented reality, visual product search, speech-to-text. Although mobile devices now have multi-core CPUs and multi-GB RAMs, these applications cannot be executed entirely on the devices. These applications need intensive computation and access to “big data” for them to be fast and accurate. They rely on offloading intensive tasks to the cloud. The devices send sensed values to the cloud, which then executes the recognition procedures using its computational resources [1] and access to big data. However, the heavy computation and the added communication latency still deter seamless interaction, which is desired for such applications. Hence, there is a need to accelerate the performance of perception-based mobile applications. In this regard, we believe approximate memoization will be a key enabling-technique.
{"title":"Poster: Approximate Memoization for Perception-based Mobile Applications","authors":"Utsav Drolia, Katherine Guo, R. Gandhi, P. Narasimhan","doi":"10.1145/2938559.2938594","DOIUrl":"https://doi.org/10.1145/2938559.2938594","url":null,"abstract":"One of the main thrusts of mobile and pervasive computing is supporting perception-based applications [1]. Perceptionbased applications are those that help users augment their understanding of the physical world through the sensors on their mobile devices, e.g. augmented reality, visual product search, speech-to-text. Although mobile devices now have multi-core CPUs and multi-GB RAMs, these applications cannot be executed entirely on the devices. These applications need intensive computation and access to “big data” for them to be fast and accurate. They rely on offloading intensive tasks to the cloud. The devices send sensed values to the cloud, which then executes the recognition procedures using its computational resources [1] and access to big data. However, the heavy computation and the added communication latency still deter seamless interaction, which is desired for such applications. Hence, there is a need to accelerate the performance of perception-based mobile applications. In this regard, we believe approximate memoization will be a key enabling-technique.","PeriodicalId":298684,"journal":{"name":"MobiSys '16 Companion","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132053478","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}
Road accidents cause an estimated 1.3 million fatalities each year worldwide. We believe that mobile devices can play a positive role by detecting various driving related events like red light cutting, rash driving and many more. We focus on a specific problem that is responsible for many accidents in India: the stopping behaviour of buses especially in the vicinity of bus stops. We propose a smartphone-based system that specifically seeks to detect and report the following scenarios. 1. Has the bus come to a complete stop(instead of a rolling stop)? 2. Has the bus stopped in the left lane? 3. Has the bus stopped exactly at the bus stop? thus prevent from derailment of trains
{"title":"Poster: Improving Road Safety Through Smart-Sensing","authors":"Ravi Bhandari, B. Raman, V. Padmanabhan","doi":"10.1145/2938559.2948797","DOIUrl":"https://doi.org/10.1145/2938559.2948797","url":null,"abstract":"Road accidents cause an estimated 1.3 million fatalities each year worldwide. We believe that mobile devices can play a positive role by detecting various driving related events like red light cutting, rash driving and many more. We focus on a specific problem that is responsible for many accidents in India: the stopping behaviour of buses especially in the vicinity of bus stops. We propose a smartphone-based system that specifically seeks to detect and report the following scenarios. 1. Has the bus come to a complete stop(instead of a rolling stop)? 2. Has the bus stopped in the left lane? 3. Has the bus stopped exactly at the bus stop? thus prevent from derailment of trains","PeriodicalId":298684,"journal":{"name":"MobiSys '16 Companion","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127635281","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}
Mateusz Mikusz, Oliver Bates, S. Clinch, N. Davies, A. Friday, A. Noulas
The increasing reach of the Internet of Things (IoT) is leading to a world rich in sensors [3] that can be used to support physical analytics -- analogous to web analytics but targeted at user interactions with physical devices in the real-world (e.g. [2]). In contrast to web analytics, physical analytics systems typically only provide data relating to sensors and objects without consideration of individual users. This is mainly a consequence of an inability to track individual mobile user interactions across multiple physical objects (or across sessions of interaction with a single object) using, for example, an analogue of a web cookie. Indeed, such a "physical analytics cookie" could raise significant privacy concerns. However, in many cases a more "human-centric" approach to analytics would enable us to provide new and interesting insights into interactions between mobile users and the physical world [1]. In our work we endeavour to leverage synthetic user traces of human mobility, and data from real IoT systems, to provide such insights.
{"title":"Poster: Understanding Mobile User Interactions with the IoT","authors":"Mateusz Mikusz, Oliver Bates, S. Clinch, N. Davies, A. Friday, A. Noulas","doi":"10.1145/2938559.2938607","DOIUrl":"https://doi.org/10.1145/2938559.2938607","url":null,"abstract":"The increasing reach of the Internet of Things (IoT) is leading to a world rich in sensors [3] that can be used to support physical analytics -- analogous to web analytics but targeted at user interactions with physical devices in the real-world (e.g. [2]). In contrast to web analytics, physical analytics systems typically only provide data relating to sensors and objects without consideration of individual users. This is mainly a consequence of an inability to track individual mobile user interactions across multiple physical objects (or across sessions of interaction with a single object) using, for example, an analogue of a web cookie. Indeed, such a \"physical analytics cookie\" could raise significant privacy concerns.\u0000 However, in many cases a more \"human-centric\" approach to analytics would enable us to provide new and interesting insights into interactions between mobile users and the physical world [1]. In our work we endeavour to leverage synthetic user traces of human mobility, and data from real IoT systems, to provide such insights.","PeriodicalId":298684,"journal":{"name":"MobiSys '16 Companion","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127958731","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}
Several duty-cycling and energy-efficient communication protocols have been presented to solve power constraints of sensor nodes. The battery power of sensor nodes can be also supplied by surrounding energy resources using energy harvesting techniques. However, communication protocols only offer limited power for sensor nodes and energy harvesting may encounter a challenge that sensor nodes are unable to draw power from surrounding energy resources in certain environments. Thus, an emerging technology, wireless rechargeable sensor networks (WRSNs), is proposed to enhance the proposed communication protocols and energy harvesting techniques [1]. With a WRSN, a mobile vehicle is used to supply power to sensor nodes by wireless energy transfer. One of the most significant issue in WRSNs is path planning of the mobile vehicle. The mobile vehicle based on its movement trajectory visits each sensor nodes to recharge them so that the sensor nodes can obtain sufficient energy to execute continuous missions. However, all of the existing mobile vehicles charging methods [2, 3] for WRSNs require the locations of the sensor nodes based on the assumption that the location of each sensor node is known in advance by one of the sensor network localization mechanisms. Therefore, the proposed system integrates both the localization and wireless charging mechanisms for WRSNs to decrease the system initialization time and cost.
{"title":"Poster: A Localization and Wireless Charging System for Wireless Rechargeable Sensor Networks Using Mobile Vehicles","authors":"Chia-Ho Ou, Chong-Min Gao, Yu-jung Chang","doi":"10.1145/2938559.2938596","DOIUrl":"https://doi.org/10.1145/2938559.2938596","url":null,"abstract":"Several duty-cycling and energy-efficient communication protocols have been presented to solve power constraints of sensor nodes. The battery power of sensor nodes can be also supplied by surrounding energy resources using energy harvesting techniques. However, communication protocols only offer limited power for sensor nodes and energy harvesting may encounter a challenge that sensor nodes are unable to draw power from surrounding energy resources in certain environments. Thus, an emerging technology, wireless rechargeable sensor networks (WRSNs), is proposed to enhance the proposed communication protocols and energy harvesting techniques [1]. With a WRSN, a mobile vehicle is used to supply power to sensor nodes by wireless energy transfer. One of the most significant issue in WRSNs is path planning of the mobile vehicle. The mobile vehicle based on its movement trajectory visits each sensor nodes to recharge them so that the sensor nodes can obtain sufficient energy to execute continuous missions. However, all of the existing mobile vehicles charging methods [2, 3] for WRSNs require the locations of the sensor nodes based on the assumption that the location of each sensor node is known in advance by one of the sensor network localization mechanisms. Therefore, the proposed system integrates both the localization and wireless charging mechanisms for WRSNs to decrease the system initialization time and cost.","PeriodicalId":298684,"journal":{"name":"MobiSys '16 Companion","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131728321","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":"Demo: Magnetic Positioning Sphere - A Single-Source 3D Positioning System using Rotating Magnetic Fields","authors":"Wei-Tung Chen, Ling-Jyh Chen","doi":"10.1145/2938559.2938567","DOIUrl":"https://doi.org/10.1145/2938559.2938567","url":null,"abstract":"","PeriodicalId":298684,"journal":{"name":"MobiSys '16 Companion","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122282931","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}
Yan Liu, Bin Guo, Wenle Wu, Zhiwen Yu, Yang Wang, Daqing Zhang
{"title":"Poster: Towards a Multitask Worker Recruitment Framework for Mobile Crowdsensing","authors":"Yan Liu, Bin Guo, Wenle Wu, Zhiwen Yu, Yang Wang, Daqing Zhang","doi":"10.1145/2938559.2948857","DOIUrl":"https://doi.org/10.1145/2938559.2948857","url":null,"abstract":"","PeriodicalId":298684,"journal":{"name":"MobiSys '16 Companion","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131824687","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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