Online Social Networks: Threats and Solutions

Fire, Michael; Goldschmidt, Roy; Elovici, Yuval

doi:10.1109/comst.2014.2321628

Cited by 278 publications

(148 citation statements)

References 66 publications

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“…For the spam detection, the spam word dataset, URL blocking, keyword blocking is applied on rendered message. Then, the data mining or text classification algorithm is used to detect the overall spam [3] . [4] In this paper the techniques available for detection of spammers in Twitter have been presented along with their analysis and comparison.…”

Section: Spam Detection and Filtration Using Data Mining For Sociamentioning

confidence: 99%

An Improved Method for Spam Detection in Social Media

2016

IJAERD

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Section: Spam Detection and Filtration Using Data Mining For Sociamentioning

confidence: 99%

An Improved Method for Spam Detection in Social Media

2016

IJAERD

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“…In 2014, Michael Fire et.al, [10] presented an overview of existing solutions that provide better protection, security and privacy for users. It offers simple-to-implement platforms for users.…”

Section: Related Workmentioning

confidence: 99%

A Survey on Data Security in Social Networking Sites

Pradhan¹,

Misra²,

Koirala³

2016

IJCA

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The popular communication Social Networking Sites (SNS) like Facebook, Twitter, LinkedIn etc have become in style and well-liked during the past few years and are utilized by billions of individuals irrespective of their age groups for communicating either with old friends, relatives from far places or total strangers. As they allow users to both articulate their eccentricity and meet people with similar interests. Risks posed by SNS are becoming harder to conquer due to publication of social network data by user which may contain personal or confidential information. There is a high possibility of this information to be misused by people with harmful motives like stalking, identity theft, online victimization etc. Therefore there arises an urgent need to safeguard users from attacks occurring in SNS, as users are still unaware of these threats. Moreover, a user does not have control about what others reveal about them. The attackers of SNS mainly use social engineering attack to victimize the user through malicious URL links, applications, Spam messages etc. URL has an important role in detecting phishing websites. So, this focuses on the detection and prevention of malicious URLs as they are used to mount various attacks like spamming, phishing, malware etc.

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“…Privacy breaches may result from the service provider, other users, or third party applications. Fire, Goldschmidt, & Elovici (2014) categorize threats into classic, modern, combined, and childrenoriented threats. Classic threats include malware, phishing attacks, spammers, crosssite scripting (XSS), and internet fraud.…”

Section: Related Work On Categorization Of Attacksmentioning

confidence: 99%

A Survey of Social Network Forensics

Karabiyik¹,

Canbaz²,

Aksoy³

et al. 2016

JDFSL

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Social networks in any form, specifically online social networks (OSNs), are becoming a part of our everyday life in this new millennium especially with the advanced and simple communication technologies through easily accessible devices such as smartphones and tablets. The data generated through the use of these technologies need to be analyzed for forensic purposes when criminal and terrorist activities are involved. In order to deal with the forensic implications of social networks, current research on both digital forensics and social networks need to be incorporated and understood. This will help digital forensics investigators to predict, detect and even prevent any criminal activities in different forms. It will also help researchers to develop new models/techniques in the future. This paper provides literature review of the social network forensics methods, models, and techniques in order to provide an overview to the researchers for their future works as well as the law enforcement investigators for their investigations when crimes are committed in the cyber space. It also provides awareness and defense methods for OSN users in order to protect them against to social attacks.

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Online Social Networks: Threats and Solutions

Cited by 278 publications

References 66 publications

An Improved Method for Spam Detection in Social Media

An Improved Method for Spam Detection in Social Media

A Survey on Data Security in Social Networking Sites

A Survey of Social Network Forensics

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