Spam Analysis And Detection For User Generated Content In Online Social Networks
DOWNLOAD
Download Spam Analysis And Detection For User Generated Content In Online Social Networks PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Spam Analysis And Detection For User Generated Content In Online Social Networks book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Spam Analysis And Detection For User Generated Content In Online Social Networks
DOWNLOAD
Author : Enhua Tan
language : en
Publisher:
Release Date : 2013
Spam Analysis And Detection For User Generated Content In Online Social Networks written by Enhua Tan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
With the access to three large OSN user activity logs, including Yahoo! Blogs, Yahoo! Answers, and Yahoo! Del.icio.us, for a duration of up to 4.5 years, we are able to well analyze the patterns of content generation patterns of social network users in detail. Our analysis consistently shows that users' posting behavior in these networks exhibits strong daily and weekly patterns, but the user active time in these OSNs does not follow commonly assumed exponential distributions. We also show that the user posting behavior in these OSNs follows stretched exponential distributions instead of widely accepted power law distributions. Our discovery lays a foundation for user behavior analysis in social networks, and serves as a ground truth for anomaly detection and anti-spam.
Information Quality In Online Social Media And Big Data Collection
DOWNLOAD
Author : Mahdi Washha (doctorant en informatique).)
language : en
Publisher:
Release Date : 2018
Information Quality In Online Social Media And Big Data Collection written by Mahdi Washha (doctorant en informatique).) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
The popularity of OSM is mainly conditioned by the integrity and the quality of UGC as well as the protection of users' privacy. Based on the definition of information quality as fitness for use, the high usability and accessibility of OSM have exposed many information quality (IQ) problems which consequently decrease the performance of OSM dependent applications. Such problems are caused by ill-intentioned individuals who misuse OSM services to spread different kinds of noisy information, including fake information, illegal commercial content, drug sales, mal- ware downloads, and phishing links. The propagation and spreading of noisy information cause enormous drawbacks related to resources consumptions, decreasing quality of service of OSM-based applications, and spending human efforts. The majority of popular social networks (e.g., Facebook, Twitter, etc) over the Web 2.0 is daily attacked by an enormous number of ill-intentioned users. However, those popular social networks are ineffective in handling the noisy information, requiring several weeks or months to detect them. Moreover, different challenges stand in front of building a complete OSM-based noisy information filtering methods that can overcome the shortcomings of OSM information filters. These challenges are summarized in: (i) big data; (ii) privacy and security; (iii) structure heterogeneity; (iv) UGC format diversity; (v) subjectivity and objectivity; (vi) and service limitations In this thesis, we focus on increasing the quality of social UGC that are published and publicly accessible in forms of posts and profiles over OSNs through addressing in-depth the stated serious challenges. As the social spam is the most common IQ problem appearing over the OSM, we introduce a design of two generic approaches for detecting and filtering out the spam content. The first approach is for detecting the spam posts (e.g., spam tweets) in a real-time stream, while the other approach is dedicated for handling a big data collection of social profiles (e.g., Twitter accounts).
Online Social Networks Security
DOWNLOAD
Author : Brij B. Gupta
language : en
Publisher: CRC Press
Release Date : 2021-02-26
Online Social Networks Security written by Brij B. Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-26 with Computers categories.
In recent years, virtual meeting technology has become a part of the everyday lives of more and more people, often with the help of global online social networks (OSNs). These help users to build both social and professional links on a worldwide scale. The sharing of information and opinions are important features of OSNs. Users can describe recent activities and interests, share photos, videos, applications, and much more. The use of OSNs has increased at a rapid rate. Google+, Facebook, Twitter, LinkedIn, Sina Weibo, VKontakte, and Mixi are all OSNs that have become the preferred way of communication for a vast number of daily active users. Users spend substantial amounts of time updating their information, communicating with other users, and browsing one another’s accounts. OSNs obliterate geographical distance and can breach economic barrier. This popularity has made OSNs a fascinating test bed for cyberattacks comprising Cross-Site Scripting, SQL injection, DDoS, phishing, spamming, fake profile, spammer, etc. OSNs security: Principles, Algorithm, Applications, and Perspectives describe various attacks, classifying them, explaining their consequences, and offering. It also highlights some key contributions related to the current defensive approaches. Moreover, it shows how machine-learning and deep-learning methods can mitigate attacks on OSNs. Different technological solutions that have been proposed are also discussed. The topics, methodologies, and outcomes included in this book will help readers learn the importance of incentives in any technical solution to handle attacks against OSNs. The best practices and guidelines will show how to implement various attack-mitigation methodologies.
Proceedings Of The Australasian Computer Science Week Multiconference
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2020
Proceedings Of The Australasian Computer Science Week Multiconference written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Sentiment Analysis In Social Networks
DOWNLOAD
Author : Federico Alberto Pozzi
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-10-06
Sentiment Analysis In Social Networks written by Federico Alberto Pozzi and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-06 with Computers categories.
The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network analysis Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network mining Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics
Online Social Networks Security
DOWNLOAD
Author : Brij B. Gupta
language : en
Publisher: CRC Press
Release Date : 2021-02-26
Online Social Networks Security written by Brij B. Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-26 with Computers categories.
In recent years, virtual meeting technology has become a part of the everyday lives of more and more people, often with the help of global online social networks (OSNs). These help users to build both social and professional links on a worldwide scale. The sharing of information and opinions are important features of OSNs. Users can describe recent activities and interests, share photos, videos, applications, and much more. The use of OSNs has increased at a rapid rate. Google+, Facebook, Twitter, LinkedIn, Sina Weibo, VKontakte, and Mixi are all OSNs that have become the preferred way of communication for a vast number of daily active users. Users spend substantial amounts of time updating their information, communicating with other users, and browsing one another’s accounts. OSNs obliterate geographical distance and can breach economic barrier. This popularity has made OSNs a fascinating test bed for cyberattacks comprising Cross-Site Scripting, SQL injection, DDoS, phishing, spamming, fake profile, spammer, etc. OSNs security: Principles, Algorithm, Applications, and Perspectives describe various attacks, classifying them, explaining their consequences, and offering. It also highlights some key contributions related to the current defensive approaches. Moreover, it shows how machine-learning and deep-learning methods can mitigate attacks on OSNs. Different technological solutions that have been proposed are also discussed. The topics, methodologies, and outcomes included in this book will help readers learn the importance of incentives in any technical solution to handle attacks against OSNs. The best practices and guidelines will show how to implement various attack-mitigation methodologies.
Changing Dynamics Of National Security
DOWNLOAD
Author : Dr. Hemant Kumar Pandey
language : en
Publisher: OrangeBooks Publication
Release Date : 2021-12-31
Changing Dynamics Of National Security written by Dr. Hemant Kumar Pandey and has been published by OrangeBooks Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-31 with Political Science categories.
The contemporary geopolitical affairs anywhere around the globe, directly influence the national security of a state. Growing conventional, as well as non-conventional threats, are influencing the policies of the nation, both at the national and international levels. The book throws light on how the different dimensions of national security are constantly changing in this globalized and modernized world. This book focuses on how the 21st century is witnessing the new unconventional menaces like Cyber terrorism, Proxy wars, Elite capture, etc. the book also discusses how new threats for Indian interests have emerged in and across physical borders and how these threats are going to be countered.
Analyzing And Detecting Social Spammers With Robust Features
DOWNLOAD
Author : Jianan Yue
language : en
Publisher:
Release Date : 2017
Analyzing And Detecting Social Spammers With Robust Features written by Jianan Yue and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
"The rapid growth of online social networks has attracted an increasing number of social spammers. Spammers gain profits by posting various content such as rumors and malwares. These behaviors greatly compromise social networks' privacy and security, and endanger the whole network community. In the last few years, researchers have proposed a number of spam detection strategies. However, spammers become harder to be detected as they constantly evolve to evade detection by emulating legitimate users and hiding spam patterns. Many detection methods become ineffective. In this thesis, we aim to design spam detection methods using features that are resilient to evolving spammers. To achieve this goal, we first conduct an in-depth analysis on different properties of user accounts. We study the Twitter accounts and extract four kinds of features: profile-based, content-based, community-based and time-based features. By analyzing evasion techniques used by current spammers, we find that the commonly-used profile and content-based features are not effective enough to uncover cunning spammers. This is because these features can be easily emulated by spammers. To tackle this issue, we investigate the structural properties of Twitter network topologies and propose community-based features. These community-based features are more robust than profile-based and content-based features due to the fact that community structure is determined by multiple accounts collectively. Compared to a normal user, a spammer is more likely to connect with other spammers. Moreover, we find that spammers often need to fulfill a task in a short period of time to reduce costs. Based on this phenomenon, we design new time-based features to capture spam outbreaks. In addition to effectiveness, we also consider efficiency as another important factor. We select computation-efficient features as potential candidates by comparing the time of feature construction. Our data-driven evaluation demonstrates that our advanced features largely improve the performance of the spam detection system. While achieving an even lower false positive rate, the detection rate increases by 16% and f1 score increases by over 10% when applying our feature set. " --
Botnets
DOWNLOAD
Author : Georgios Kambourakis
language : en
Publisher: CRC Press
Release Date : 2019-09-26
Botnets written by Georgios Kambourakis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-26 with Computers categories.
This book provides solid, state-of-the-art contributions from both scientists and practitioners working on botnet detection and analysis, including botnet economics. It presents original theoretical and empirical chapters dealing with both offensive and defensive aspects in this field. Chapters address fundamental theory, current trends and techniques for evading detection, as well as practical experiences concerning detection and defensive strategies for the botnet ecosystem, and include surveys, simulations, practical results, and case studies.
Social Big Data Analytics
DOWNLOAD
Author : Bilal Abu-Salih
language : en
Publisher: Springer Nature
Release Date : 2021-03-10
Social Big Data Analytics written by Bilal Abu-Salih and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-10 with Business & Economics categories.
This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.