Online social network information forensics: A survey on use of various tools and determining how cautious facebook users are?

Umair, A; Nanda, P; He, X

Online social network information forensics: A survey on use of various tools and determining how cautious facebook users are?

Umair, A Nanda, P

He, X

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 16th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 11th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Conference on Embedded Software and Systems, Trustcom/BigDataSE/ICESS 2017, 2017, pp. 1139 - 1144
Issue Date:: 2017-09-07

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	Filename	Description	Size
	Trustcom2017_OSN_Information_Amber (1).pdf	Accepted Manuscript	810.9 kB	Adobe PDF	View/Open

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Field	Value	Language
dc.contributor.author	Umair, A	en_US
dc.contributor.author	Nanda, P https://orcid.org/0000-0002-5748-155X	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.date.issued	2017-09-07	en_US
dc.identifier.citation	Proceedings - 16th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 11th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Conference on Embedded Software and Systems, Trustcom/BigDataSE/ICESS 2017, 2017, pp. 1139 - 1144	en_US
dc.identifier.isbn	9781509049059	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120428
dc.description.abstract	© 2017 IEEE. Online Social Networks (OSN) such as Facebook, Twitter, LinkedIn, and Instagram are heavily used to socialize, entertain or gain insights on people behavior and their activities. Everyday terabytes of data is generated over these networks, which is then used by the businesses to generate revenue or misused by the wrongdoers to exploit vulnerabilities of these social network platforms. Specifically social network information helps in extracting various important features such as; user association, access pattern, location information etc. Recent research shows, many such features could be used to develop novel attack models and investigate further into defending the users from exposing their information to outsiders. This paper analyzes some of the available tools to extract OSN information and discusses research work on similar type of unstructured data. Recent research works, which focus on gathering bits and pieces of information to extract meaningful results for digital forensics, has been discussed. An online survey is conducted to gauge the cautiousness of users in social media usage in terms of personal information dissemination.	en_US
dc.relation.ispartof	Proceedings - 16th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 11th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Conference on Embedded Software and Systems, Trustcom/BigDataSE/ICESS 2017	en_US
dc.relation.isbasedon	10.1109/Trustcom/BigDataSE/ICESS.2017.364	en_US
dc.relation.isreplacedby	10453/126846
dc.relation.isreplacedby	http://hdl.handle.net/10453/126846
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Online social network information forensics: A survey on use of various tools and determining how cautious facebook users are?	en_US
dc.type	Conference Proceeding
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access	*
pubs.declined	2017-11-21T16:18:14.101+1100
pubs.merge-to	10453/126846
pubs.merge-to	http://hdl.handle.net/10453/126846
pubs.deleted	2017-11-21T16:18:14.101+1100
pubs.publication-status	Published	en_US

Abstract:

© 2017 IEEE. Online Social Networks (OSN) such as Facebook, Twitter, LinkedIn, and Instagram are heavily used to socialize, entertain or gain insights on people behavior and their activities. Everyday terabytes of data is generated over these networks, which is then used by the businesses to generate revenue or misused by the wrongdoers to exploit vulnerabilities of these social network platforms. Specifically social network information helps in extracting various important features such as; user association, access pattern, location information etc. Recent research shows, many such features could be used to develop novel attack models and investigate further into defending the users from exposing their information to outsiders. This paper analyzes some of the available tools to extract OSN information and discusses research work on similar type of unstructured data. Recent research works, which focus on gathering bits and pieces of information to extract meaningful results for digital forensics, has been discussed. An online survey is conducted to gauge the cautiousness of users in social media usage in terms of personal information dissemination.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/120428