2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)最新文献_第5页

Vision Powered Conversational AI for Easy Human Dialogue Systems 用于简单的人类对话系统的视觉驱动会话AI

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00088

Bipendra Basnyat, Neha Singh, Nirmalya Roy, A. Gangopadhyay

引用次数: 2

A WiFi-based Home Security System 基于wifi的家庭安全系统

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00026

Shaohu Zhang, Raghav H. Venkatnarayan, Muhammad Shahzad

引用次数: 5

Role of Blockchain in Forestalling Pandemics 区块链在预防流行病中的作用

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00014

Keshav Kaushik, Susheela Dahiya, Rajani Singh, A. Dwivedi

引用次数: 11

UAVs-Based Mobile Radars for Real-Time Highways Surveillance 基于无人机的高速公路实时监控移动雷达

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00020

Fatima Zahra Rabahi, S. Boudjit, C. Bemmoussat, M. Benaissa

{"title":"UAVs-Based Mobile Radars for Real-Time Highways Surveillance","authors":"Fatima Zahra Rabahi, S. Boudjit, C. Bemmoussat, M. Benaissa","doi":"10.1109/MASS50613.2020.00020","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00020","url":null,"abstract":"Recently, drones also known as UAVs for Unmanned Aerial Vehicles have had a great place in the civil and industrial field. They can be deployed in an ad hoc manner and operate collaboratively within a fleet known as Flying AdHoc Network (FANET). This kind of deployment can be found in some real-time applications where it is difficult to intervene, as it is the case in natural disasters. In our paper, we proposed a new application using drones to help police officers to verbalize drivers on real-time. The idea is to use radar drones to monitor highways against traffic violations and then transmit the captured images to a ground police patrol or to the police data centre. If the UAV fleet is close to the ground Base Station (BS), drones broadcast the captured images directly to the BS. However, if the fleet is far away, the UAVs are forced to go back and forth to the BS while the major issue for UAVs is the limited lifetime of their batteries. To solve this problem and ensure real-time transmission during highways surveillance, we introduced vehicles on the ground as an alternative solution that meets the requirements of our network. This mechanism is called vehicles-assisted UAVs Network. For the validation of our proposed model, some simulations have been made using NS-3 simulator. The results of our simulation show that our model is very promising in terms of delay, packet delivery ratio, and energy consumption.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134174407","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: 2

A TORA-based Wireless Protocol for MANET with Low Routing Overhead at Link Layer 基于tora的低链路层路由开销的MANET无线协议

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00043

Biao Han, Li Ding, Yusheng Ji, Xiaoyan Wang, Baosheng Wang

{"title":"A TORA-based Wireless Protocol for MANET with Low Routing Overhead at Link Layer","authors":"Biao Han, Li Ding, Yusheng Ji, Xiaoyan Wang, Baosheng Wang","doi":"10.1109/MASS50613.2020.00043","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00043","url":null,"abstract":"Mobile Ad hoc Network (MANET) is an emerging technology that allows users to transmit data without any physical infrastructure. Among those MANET protocols, Temporally Ordered Routing Algorithm (TORA) is an on-demand MANET routing protocol that attempts to find routes according to the directed acyclic graph (DAG). However, the TORA protocol requires strict synchronization. The routing overhead of TORA will increase linearly with the packet transmission rate. Motivated by Apple Wireless Direct Link (AWDL), we propose an ad hoc link-layer protocol called TORA-based Wireless Protocol (TWP) in this article. TWP can be deployed on embedded devices with Linux-kernel systems. Besides, it has unique frame structures and mechanisms. Also, it can implement synchronization and a TORA-like routing function at the link layer. We analyze the performance of TWP via experiments on Raspberry Pis. The results show that TWP can perform routing and data transmission successfully. It performs well in synchronization and can effectively reduce the routing overhead during the process of network routing.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115782942","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: 1

Deep Learning Based Prediction Towards Designing A Smart Building Assistant System 基于深度学习预测的智能楼宇辅助系统设计

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00034

Ankur Sarker, Fan Yao, Haiying Shen, Huiying Zhao, Haoran Zhu, H. Lone, Laura E. Barnes, Brad Campbell, Mitchel Rosen

{"title":"Deep Learning Based Prediction Towards Designing A Smart Building Assistant System","authors":"Ankur Sarker, Fan Yao, Haiying Shen, Huiying Zhao, Haoran Zhu, H. Lone, Laura E. Barnes, Brad Campbell, Mitchel Rosen","doi":"10.1109/MASS50613.2020.00034","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00034","url":null,"abstract":"Nowadays, smart building infrastructures are equipped with hundreds of sensors to monitor building environments and provide smart solutions for occupant comfortability and energy efficiency. Ideally, an automated system can predict and adjust the physical features (e.g., lighting, air quality, temperature, and so on) in a person’s office based on his/her personalized preferences and activities. However, since the data is from one person, there may not be sufficient data for machine learning model training, and the data’s quality may be low (e.g., with noises). Then, it is a challenge to conduct accurate predictions to provide personalized environment adjustment. To handle this problem, in this paper, we propose a smart building assistance system consisting of different sensor data analysis approaches and a deep neural network (DNN)-based prediction model to make a more accurate prediction despite low-quality sensor data. First, we collected a year-long smart building dataset from four different data sources (i.e., sensors, calendar, weather, and survey). Second, we perform different feature engineering approaches (i.e., concretization, one-hot encoding, and multiple feature combination) on the data as inputs for the prediction models. Third, we identify a support vector regression-based prediction model and propose a hybrid DNN model consisting of several recurrent neural network blocks and a feed-forward DNN block to predict different preferred physical features considering different activities of a person (e.g., meeting, lunch, research activities). Finally, we conduct experimental studies to evaluate the performance of the proposed prediction models compared to other existing machine learning models in terms of accuracy. Our predicted preferred physical features match the occupant’s preferred ranges of different physical features during a specific activity. We also open-sourced our code on GitHub.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122970881","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: 1

Tracing the Source of Fake News using a Scalable Blockchain Distributed Network 使用可扩展的区块链分布式网络追踪假新闻的来源

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00015

A. Dwivedi, Rajani Singh, Sakshi Dhall, Gautam Srivastava, S. Pal

{"title":"Tracing the Source of Fake News using a Scalable Blockchain Distributed Network","authors":"A. Dwivedi, Rajani Singh, Sakshi Dhall, Gautam Srivastava, S. Pal","doi":"10.1109/MASS50613.2020.00015","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00015","url":null,"abstract":"In the news industry, as well as in social media, fake news detection and identification of news sources has become a central topic of discussion. In the era of digitization, anyone can easily generate or manipulate digital content and publish them on social media websites. On the one hand, these social networking platforms provide ample ease in modern-day communication but on the other hand, using such platforms has posed new challenges to real-world implementation like viral spreading of false/fake information with malicious intentions. In this paper, a naive blockchain and watermarking based social media framework is proposed to control the fake news propagation. We postulate a new blockchain model to mitigate existing challenges in this field. Moreover, the novel solution can help in reducing the spread of fake news by tracing the root or origin of the fake news on social media. Through our experimental results, we show that our blockchain-based solution is able to immediately stream data through a bloXroute server that can propagate data up to 100 times faster than conventional solutions.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126000659","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: 21

Distributed and Privacy Preserving Routing of Connected Vehicles to Minimize Congestion 基于分布式和隐私保护的车联网路径设计

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00036

Surabhi Boob, Shakir Mahmood, Muhammad Shahzad

{"title":"Distributed and Privacy Preserving Routing of Connected Vehicles to Minimize Congestion","authors":"Surabhi Boob, Shakir Mahmood, Muhammad Shahzad","doi":"10.1109/MASS50613.2020.00036","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00036","url":null,"abstract":"With a large number of connected vehicles on the roads, there is an opportunity to leverage their connectivity to minimize congestion on roads by calculating fast routes for vehicles in a way that each vehicle contributes as little to the congestion as possible. The existing commercial and research based approaches of calculating routes for vehicles suffer from one or more of the following two limitations: 1) they are not privacy preserving in the sense that they receive destination addresses from users and may either store and use them for other commercial purposes or are at a risk of getting hacked and exposing these addresses to hackers; and 2) they require expensive infrastructure such as road side units (RSUs). To address these limitations, we propose a distributed and privacy preserving routing protocol, namely DPR, which the connected vehicles collaboratively and repeatedly execute to calculate fast routes to their destinations such that the overall congestion on the road network is significantly reduced and at the same time the privacy of the vehicles is preserved. The DPR protocol relies on direct vehicle to vehicle communication and does not need any new infrastructure such as RSUs. We have implemented and evaluated our DPR protocol through simulations on a real road network under several traffic conditions. Our results show that DPR reduces the average travel time of vehicles that travel a distance of 1000, 2500, and over 4000 meters by 15%, 32%, and 42%, respectively. This reduction in travel time is significant considering that this improvement results purely from software manipulations and without requiring any new infrastructure.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124682320","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: 1

Voice Liveness Detection for Voice Assistants using Ear Canal Pressure 基于耳道压力的语音助手语音活跃度检测

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00089

Jiacheng Shang, Jie Wu

{"title":"Voice Liveness Detection for Voice Assistants using Ear Canal Pressure","authors":"Jiacheng Shang, Jie Wu","doi":"10.1109/MASS50613.2020.00089","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00089","url":null,"abstract":"With the success of voice recognition techniques, users can easily control any device in smart home environments by simply saying a voice command. Based on this idea, a new group of smart devices are designed and released, which are called voice assistant. However, the voice itself is not secure and can be attacked in many ways. To defend against various types of voice replay attacks, we present a new voice liveness detection system. The basic insight of our system is that mouth opening movements will change the space size in the ear canal, which further changes the air pressure in ear canals. In this paper, we propose solutions to detect mouth opening movements using the noisy air pressure data and match them with the voices to validate the liveness of the voice source. To evaluate the effectiveness of our system, we develop a prototype on Raspberry Pi and conduct comprehensive evaluations. Experiments with ten volunteers show that our system can accurately accept voice commands from legitimate users with an accuracy of 91.72%. Moreover, our system can effectively defend current voice assistant devices from replay attacks with an accuracy of 97.2%.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"376 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124701127","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

DRE2: Achieving Data Resilience in Wireless Sensor Networks: A Quadratic Programming Approach DRE2:实现无线传感器网络的数据弹性:一个二次规划方法

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00019

Shang-Chih Hsu, Yuning Yu, Bin Tang

{"title":"DRE2: Achieving Data Resilience in Wireless Sensor Networks: A Quadratic Programming Approach","authors":"Shang-Chih Hsu, Yuning Yu, Bin Tang","doi":"10.1109/MASS50613.2020.00019","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00019","url":null,"abstract":"We focus on sensor networks that are deployed in challenging environments, wherein sensors do not always have connected paths to a base station, and propose a new data resilience problem. We refer to it as DRE2: data -resiliency in $underline{e}$xtreme $underline{e}$nvironments. As there are no connected paths between sensors and the base station, the goal of $mathrm{D}mathrm{R}mathrm{E}^{2}$ is to maximize data resilience by preserving the overflow data inside the network for maximum amount of time, considering that sensor nodes have limited storage capacity and unreplenishable battery power. We propose a quadratic programming-based algorithm to solve $mathrm{D}mathrm{R}mathrm{E}^{2}$ optimally. As quadratic programming is NP-hard thus not scalable, we design two time efficient heuristics based on different network metrics. We show via extensive experiments that all algorithms can achieve high data resiliences, while a minimum cost flow-based is most energy-efficient. Our algorithms tolerate node failures and network partitions caused by energy depletion of sensor nodes. Underlying our algorithms are flow networks that generalize the edge capacity constraint well-accepted in traditional network flow theory.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117038857","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: 5