2018 Second International Conference on Computing Methodologies and Communication (ICCMC)最新文献_第5页

RBF Neural Network Controller In Shunt Active Power Filter 并联有源电力滤波器中的RBF神经网络控制器

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8487574

P. S. Puhan, S. Sandeep, G. Kumar

引用次数: 1

Temperature & Humidity Control By Using Neural Network For Oyster Mushroom Cultivation 基于神经网络的平菇栽培温湿度控制

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8487839

D. Gajbhiye, Kavita Joshi, Madana Mekala

引用次数: 1

Attendance and Security Assurance using Image Processing 使用图像处理的考勤和安全保证

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8487788

Raisha Shrestha, S. Pradhan, Rahul Karn, S. Shrestha

{"title":"Attendance and Security Assurance using Image Processing","authors":"Raisha Shrestha, S. Pradhan, Rahul Karn, S. Shrestha","doi":"10.1109/ICCMC.2018.8487788","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487788","url":null,"abstract":"In Maximum number of educational institutions we can see prevailing system of attendance where attendance of students are taken manually by the professors calling out the names of the students. In some universities we can find RFID system present for attendance. The manual system of attendance is very time consuming and may not be much efficient as well. Whereas RFID based attendance is also not much reliable as we don't know if the RFID card is actually used by the student whom it belongs or not. Both existing techniques for attendance system have problems in it.So our paper has used Image Processing techniques and automated the attendance system where the attendance is taken by the system by recognizing the faces of the students. The system has dataset of known faces or students such that when any unknown face detected inside the classroom, he/she will be recognized as an intruder. This will safeguard the students from any kind of invasion or attack. In this paper we have discussed the techniques which can be used to implement image processing for automating the attendance system and assure security of the students.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"35 1","pages":"544-548"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85624140","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

Machine Learning Based Twitter Spam Account Detection: A Review 基于机器学习的Twitter垃圾邮件账户检测:综述

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8487992

Shivangi Gheewala, Rakesh Patel

{"title":"Machine Learning Based Twitter Spam Account Detection: A Review","authors":"Shivangi Gheewala, Rakesh Patel","doi":"10.1109/ICCMC.2018.8487992","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487992","url":null,"abstract":"Online social networks (OSNs) are emerging communication medium for people to establish and manage social relationships. In OSNs, regularly billions of users are involved in social interaction, content and opinion dissemination, networking, recommendations, scouting, alerting, and social campaigns. The popularization of OSNs open up a new perspectives and challenges to the study of social networks, being of interest to many fields. Social network is a place where social activities, business oriented activities, entertainment, and information are exchanged. It establish a worldwide connectivity environment where communities of people share their interests and activities, or who are interested in interests and activities of others Although social network has given immense benefits to people at the same time harming people with various mischievous activities that take place on social platforms. This causes significant economic loss to our society and even threaten the national security. All the social networks Facebook, Twitter, LinkedIn, etc. are highly susceptible to malware activities. Twitter is one of the biggest microblogging networking platform, it has more than half a billion tweets are posted every day in average by millions of users on Twitter. Such a versatility and wide spread of use, Twitter easily get intruded with malicious activities. Malicious activities includes malware intrusion, spam distribution, social attacks, etc. Spammers use social engineering attack strategy to send spam tweets, spam URLs, etc. This made twitter an ideal arena for proliferation of anomalous spam accounts. The impact stimulates researchers to develop a model that analyze, detects and recovers from defamatory actions in twitter. Twitter network is inundated with tens of millions of fake spam profiles which may jeopardize the normal user’s security and privacy. To improve real users safety and identification of spam profiles become key parts of the research.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"42 3","pages":"79-84"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91423077","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

An Overview of Primary User Emulation Attack in Cognitive Radio Networks 认知无线网络中主用户仿真攻击研究综述

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8487476

Ishu Gupta, O. P. Sahu

引用次数: 1

Identifying Provenance of Information and Anomalous Paths in Attributed Social Networks 在属性社会网络中识别信息来源和异常路径

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8488006

Hetuk Trivedi, P. Bindu, P. S. Thilagam

{"title":"Identifying Provenance of Information and Anomalous Paths in Attributed Social Networks","authors":"Hetuk Trivedi, P. Bindu, P. S. Thilagam","doi":"10.1109/ICCMC.2018.8488006","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8488006","url":null,"abstract":"Information provenance problem is an important and challenging problem in social network analysis and it deals with identifying the origin or source of information spread in a social network. In this paper, an approach for detecting the source of an information spread as well as suspicious anomalous paths in a social network is proposed. An anomalous path is a sequence of nodes that propagates an anomalous information to the given destination nodes who cause an anomalous event. The proposed approach is based on attribute-based anomalies and information cascading technique. The anomalous paths are identified in two steps. The first step assigns an anomalous score to each and every vertex in the given graph based on suspicious attributes. The second step detects the source and suspicious anomalous paths in the network using the anomaly scores. The approach is tested on datasets such as Enron and Facebook to demonstrate its effectiveness. Detecting anomalous paths is useful in several applications including identifying terrorist attacks communication path, disease spreading pattern, and match-fixing hidden path between bookie and a cricketer.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"14 1","pages":"914-919"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82302986","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

Data Mining with Linked Data: Past, Present, and Future 关联数据的数据挖掘:过去、现在和未来

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8487861

Rohit Beniwal, Vikas Gupta, Manish Rawat, Rishabh Aggarwal

引用次数: 6

Event Based Sentiment Analysis of Twitter Data 基于事件的Twitter数据情感分析

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8487531

Mamta Patil, H. K. Chavan

{"title":"Event Based Sentiment Analysis of Twitter Data","authors":"Mamta Patil, H. K. Chavan","doi":"10.1109/ICCMC.2018.8487531","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487531","url":null,"abstract":"Everyday large volumes of data are produced. Millions of users share and dissipate most up-to-date information on twitter. Traditional text mining suffers severely from short and noisy nature of tweets. Event detection from twitter data has many new challenges when compared to event detection from traditional media. Noisy nature and limited length are the challenges imposed by twitter data. Event detection performance on twitter is negatively affected by nature of tweets. This paper proposes SegAnalysis framework to tackle these challenges. It performs tweet segmentation, event detection and sentiment analysis. Tweet segmentation is performed in a batch mode using POS (part of speech) tagger on recent online tweets fetched by the user. Segmentation of a tweet preserves the named entities and its stickiness score is calculated. Naïve Bayes classification and online clustering detect events. These events improve situational awareness and decision support. Sentiment analysis categorizes tweets as positive, negative and neutral depending on sentiment score of a tweet. SegAnalysis framework can be extended to deal with events belonging to multiple clusters.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"31 1","pages":"1050-1054"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78862843","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

Web Effort Estimation Using FP and WO: A Critical Study 基于FP和WO的Web工作量估算:一项批判性研究

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8487472

S. Saif, A. Wahid

{"title":"Web Effort Estimation Using FP and WO: A Critical Study","authors":"S. Saif, A. Wahid","doi":"10.1109/ICCMC.2018.8487472","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487472","url":null,"abstract":"Web based services are becoming more ubiquitous. The ease-in access and the availability of web applications have increased the volume of the users who routinely access web for diverse functionality. Most of the organisations have endorsed web applications over traditional applications as a medium to deliver and offer their diverse services. With the increasing demand, the complexity of web application development has increased proportionally. The most important and critical component in web project management is to develop web projects on time and within budget. Accurate budget estimates have positive and productive impact on project management. Accuracy in estimated web efforts have direct and deeper influence on development industry. It is mandatory for any development industry to ensure accuracy and effectiveness in their web effort estimation process. This helps project management to acquire and retain good customer base and reputation among the other competing companies. This paper is an attempt to study the impact and effectiveness of function points(FP) and web objects(WO) on web size and consequently on web efforts estimation. A dataset of ten industrial web projects were used and it was observed that size estimated by using WO was more than FP in most of the projects however, the effort in most of the projects calculated by using WO were significantly better in comparison to FP.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"174 1","pages":"357-361"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79578501","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

AN INTELLIGENT AND NOVEL ALGORITHM FOR SECURING VULNERABLE USERS OF ONLINE SOCIAL NETWORK 一种保护在线社交网络弱势用户的智能新算法

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI: 10.1109/ICCMC.2018.8487760

S. Revathi, M. Suriakala

{"title":"AN INTELLIGENT AND NOVEL ALGORITHM FOR SECURING VULNERABLE USERS OF ONLINE SOCIAL NETWORK","authors":"S. Revathi, M. Suriakala","doi":"10.1109/ICCMC.2018.8487760","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487760","url":null,"abstract":"The last few years have witnessed a very fast-paced growth in the user base and activities of Online Social Networks (OSN). Their growth is attributed to the trust that they have received from people. People engage in social networks to make friends, chat, upload and like photos, update their status, and post comments. The use of social networks causes users to think less about the related security and privacy concerns in terms of OSNs. Trusting social networks leads to serious privacy concerns. Users disclose their information voluntarily, not knowing who exactly is going to access or use their data. They are less concerned about how safe their private information is, as they are more interested in meeting different people from across the globe. Their desire to connect with their family, friends, and virtual friends is apparent from their use of OSNs. The widespread use of social networks has also given rise to widespread impersonation. It is difficult to find a feasible solution to help counteract the negative consequences of this problem. This paper discusses the reasons behind information leaks, particularly, the way in which OSNs contribute to the intelligence used by hackers. A number of security measures for organizations are also included in the paper, to help them combat the activities related to leakage of information with respect to OSNs. It also identifies the future direction in terms of in-depth research in the fields by establishing a culture of security and implementing behavioral change. The Description Logic Rule Generation algorithm is proposed in the paper to be able to find and analyze the nature of vulnerabilities and attackers. The algorithm identifies vulnerable users on the basis of a sharing threshold. The users are removed in case they cross the threshold values. The paper also presents the security analysis of results of the OSNs popularity among users.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"22 1","pages":"214-219"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78378740","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