2017 9th International Conference on Communication Systems and Networks (COMSNETS)最新文献_第3页

Why a socialbot is effective in Twitter? A statistical insight 为什么社交机器人在Twitter上是有效的?统计见解

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945454

Mohd Fazil, M. Abulaish

{"title":"Why a socialbot is effective in Twitter? A statistical insight","authors":"Mohd Fazil, M. Abulaish","doi":"10.1109/COMSNETS.2017.7945454","DOIUrl":"https://doi.org/10.1109/COMSNETS.2017.7945454","url":null,"abstract":"Twitter, a popular microblogging platform, facilitates users to express views and thoughts on any topic of discussion using short messaging texts limited to 140 characters. Due to its open and real-time information sharing and dissemination nature, it is abused by socialbots for political astroturfing, advertising, spamming, and other illicit activities. To this end, we injected an army of 98 socialbots associated to top six Twitter using countries to study socialbots’ infiltration behaviour. In this paper, we present a statistical insight derived through the analysis of the captured data by our socialbots. Socialbots’ profile features, such as age, gender, etc. and their behavioural impact on infiltration performance are studied and presented, wherein a user's following activity to a socialbot is considered as an infiltration. Experimental results and subsequent statistical analyses show that socialbots’ profiles belonging to India were the successful in duping highest number of users, whereas Indonesian socialbots were least infiltrative. Moreover, among various Twitter activities, following is found to be the most effective activity for infiltrating a user. Among the intruded users, trace of the presence of botnets, spammers, and other malicious users have also been observed and presented in this paper.","PeriodicalId":168357,"journal":{"name":"2017 9th International Conference on Communication Systems and Networks (COMSNETS)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124674634","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: 19

A weight-based map matching algorithm using minimum input variables for urban road networks 基于权重的城市路网最小输入变量地图匹配算法

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945429

S. Maity, Soumik Dalal, Sayan Ranu, L. Vanajakshi

{"title":"A weight-based map matching algorithm using minimum input variables for urban road networks","authors":"S. Maity, Soumik Dalal, Sayan Ranu, L. Vanajakshi","doi":"10.1109/COMSNETS.2017.7945429","DOIUrl":"https://doi.org/10.1109/COMSNETS.2017.7945429","url":null,"abstract":"Global Positioning System (GPS) has found its application in the field of Intelligent Transportation Systems (ITS) in fleet management, prediction of arrival of public transport vehicles, route identification, route navigation, and many other location based services. Map matching algorithms integrate the positioning data received from the GPS, with digital road networks on existing maps. This includes minimizing the error in locating the vehicle on a route, identifying the correct road segment and locating the vehicle's correct position on the road network. This paper presents a weight based map matching algorithm, which can be applied in real-time, for complex urban road networks. The parameters considered in the evaluation of the candidate segments are distance, direction difference and connectivity with the previously identified segment. A comparison between these parameters for the two best road segments was analyzed to identify probable cases of ambiguity in selection of the best segment and a solution to overcome wrong assignments was included in the algorithm. The most noticeable feature about this algorithm is the high accuracy of 96.55% for segment assignment using minimum input variables of latitude and longitude of the vehicles.","PeriodicalId":168357,"journal":{"name":"2017 9th International Conference on Communication Systems and Networks (COMSNETS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130266959","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

An adaptive and elastic cloud based framework for service oriented computing in Internet of Things 物联网面向服务计算的自适应、弹性云框架

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945433

Arpita Bajpai, B. Choudhury, S. Choudhury

引用次数: 2

Stability and delay analysis of delay tolerant networks with random message arrivals 随机消息到达延迟容忍网络的稳定性和延迟分析

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945399

S. Yasodharan, V. Sukumaran, C. Singh

引用次数: 0

CrowdMap: Crowdsourcing based city traffic map generation CrowdMap:基于众包的城市交通地图生成

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945459

Rohit Verma

引用次数: 3

Dynamic transmission power control in wireless sensor networks using P-I-D feedback control technique 基于P-I-D反馈控制技术的无线传感器网络动态传输功率控制

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945391

P. Priyesh, Subrat Kart Bharti

引用次数: 11

Predicting social dynamics based on network traffic analysis for CCN/ICN management 基于网络流量分析的CCN/ICN管理社会动态预测

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945460

Satadal Sengupta

{"title":"Predicting social dynamics based on network traffic analysis for CCN/ICN management","authors":"Satadal Sengupta","doi":"10.1109/COMSNETS.2017.7945460","DOIUrl":"https://doi.org/10.1109/COMSNETS.2017.7945460","url":null,"abstract":"Proliferation of online social networks (OSNs) has resulted in an unprecedented surge in the volume of multimedia content consumed by users on a daily basis. Popular OSNs such as Facebook enable users to view and share embedded videos and images on their feeds, which increases visibility, prompting repeated requests for the same piece of content. Maintaining desirable quality of service for all users becomes challenging in such a scenario, especially when low-bandwidth cellular network is being used for data download. Such problems have prompted the research community to focus heavily on the emerging paradigm of Information-or Content-Centric Networking (ICN/CCN), where in-network content management (e.g., content distribution, caching, etc.) forms the crux of an enhanced user experience. In this abstract, we argue that social dynamics among OSN users can provide concrete hints regarding future popularity of content. We propose a strategy to identify viewing and sharing patterns of Facebook users served by a cellular base station, by analyzing network traffic. We utilize these patterns to infer social dynamics among cellular users (mapped to cellphone numbers). We validate our strategy with proof-of-concept experiments on real data, and extensive simulations on a simulation framework proposed by us.","PeriodicalId":168357,"journal":{"name":"2017 9th International Conference on Communication Systems and Networks (COMSNETS)","volume":"106 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123390176","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

A novel online social network (Twitter)message (Tweet)classifier based on message diffusion in the network 一种新的基于网络中消息扩散的在线社交网络(Twitter)消息分类器

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945417

M. Giri, S. Jyothi, C. Vorugunti

引用次数: 0

Enhancing spectral efficiency in LTE-D2D networks 提高LTE-D2D网络的频谱效率

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945413

S. Kumar, V. Sathya, Sreenath Ramanath

引用次数: 2

On automatizing recognition of multiple human activities using ultrasonic sensor grid 基于超声传感器网格的人体多活动自动识别研究

2017 9th International Conference on Communication Systems and Networks (COMSNETS) Pub Date : 1900-01-01 DOI: 10.1109/COMSNETS.2017.7945440

Arindam Ghosh, Anubrata Sanyal, Amartya Chakraborty, P. K. Sharma, M. Saha, S. Nandi, Sujoy Saha

{"title":"On automatizing recognition of multiple human activities using ultrasonic sensor grid","authors":"Arindam Ghosh, Anubrata Sanyal, Amartya Chakraborty, P. K. Sharma, M. Saha, S. Nandi, Sujoy Saha","doi":"10.1109/COMSNETS.2017.7945440","DOIUrl":"https://doi.org/10.1109/COMSNETS.2017.7945440","url":null,"abstract":"Human activity recognition is an important problem in health care, ambient-assisted living, surveillance-based security, etc. and has crucial applications in smart environment. A non-invasive, automated system for monitoring human activity using array of heterogeneous ultrasonic sensors has been proposed in this work. Ultrasonic sensors are widely used for distance measurement in many applications. In the proposed system experiments have been conducted using ten volunteers in a controlled laboratory environment. The data collection unit has two kinds of setups of ultrasonic sensors: the former with five HC-SR04 sensors, and the latter with four HC-SR04 ultrasonic sensors and an LV-MaxSonar-EZ0 sensor. The proposed method is found capable of detecting standing, sitting and falling of a person, and also the movements in different directions. Based on the collected data, we have performed classification analysis using multiple machine learning algorithms. The experimental results show 81% to 90% correct detection of different activities of the volunteers.","PeriodicalId":168357,"journal":{"name":"2017 9th International Conference on Communication Systems and Networks (COMSNETS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121341133","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: 23