{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T22:50:08Z","timestamp":1757544608089,"version":"3.41.2"},"reference-count":37,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2021,10,15]],"date-time":"2021-10-15T00:00:00Z","timestamp":1634256000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJICC"],"published-print":{"date-parts":[[2022,2,2]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>Virtually unlimited amounts of data collection by cybersecurity systems put people at risk of having their privacy violated. Social networks like Facebook on the Internet provide an overplus of knowledge concerning their users. Although users relish exchanging data online, only some data are meant to be interpreted by those who see value in it. It is now essential for online social network (OSN) to regulate the privacy of their users on the Internet. This paper aims to propose an efficient privacy violation detection model (EPVDM) for OSN.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>In recent months, the prominent position of both industry and academia has been dominated by privateness, its breaches and strategies to dodge privacy violations. Corporations around the world have become aware of the effects of violating privacy and its effect on them and other stakeholders. Once privacy violations are detected, they must be reported to those affected and it's supposed to be mandatory to make them to take the next action. Although there are different approaches to detecting breaches of privacy, most strategies do not have a functioning tool that can show the values of its subject heading. An EPVDM for Facebook, based on a deep neural network, is proposed in this research paper.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The main aim of EPVDM is to identify and avoid potential privacy breaches on Facebook in the future. Experimental analyses in comparison with major intrusion detection system (IDS) to detect privacy violation show that the proposed methodology is robust, precise and scalable. The chances of breaches or possibilities of privacy violations can be identified very accurately.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>All the resultant is compared with well popular methodologies like adaboost (AB), decision tree (DT), linear regression (LR), random forest (RF) and support vector machine (SVM). It's been identified from the analysis that the proposed model outperformed the existing techniques in terms of accuracy (94%), precision (99.1%), recall (92.43%), f-score (95.43%) and violation detection rate (&gt;98.5%).<\/jats:p><\/jats:sec>","DOI":"10.1108\/ijicc-05-2021-0093","type":"journal-article","created":{"date-parts":[[2021,10,15]],"date-time":"2021-10-15T14:23:00Z","timestamp":1634307780000},"page":"75-91","source":"Crossref","is-referenced-by-count":2,"title":["Assuring enhanced privacy violation detection model for social networks"],"prefix":"10.1108","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1304-3723","authenticated-orcid":false,"given":"Ali","family":"Altalbe","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3226-5583","authenticated-orcid":false,"given":"Faris","family":"Kateb","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2021,10,15]]},"reference":[{"first-page":"641","article-title":"Detection of spam tipping behaviour on foursquare","year":"2013","key":"key2022020205381366900_ref001"},{"issue":"3","key":"key2022020205381366900_ref002","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/MIC.2011.66","article-title":"Security and privacy in social networks","volume":"15","year":"2011","journal-title":"IEEE Internet Computing"},{"first-page":"810","article-title":"Risks of friendships on social networks","year":"2012","key":"key2022020205381366900_ref003"},{"journal-title":"The Wall Street Journal","article-title":"Selling you on Face book","year":"2012","key":"key2022020205381366900_ref004"},{"key":"key2022020205381366900_ref005","first-page":"154","article-title":"Privacy broker for enforcing privacy policies in databases","volume-title":"Proceedings of Knowledge Based Computer Systems, KBCS 2004","year":"2004"},{"first-page":"93","article-title":"The socialbot network: when bots socialize for fame and money","year":"2011","key":"key2022020205381366900_ref006"},{"volume-title":"Security Breach Could Expose 40M to Fraud","year":"2005","key":"key2022020205381366900_ref007"},{"key":"key2022020205381366900_ref008","unstructured":"Check Point (2014), [online], available at: http:\/\/www.checkpoint.com\/ (accessed 14 January 2014)."},{"key":"key2022020205381366900_ref009","unstructured":"Constine, J. (2012), \u201cFacebook launches verified accounts and pseudonyms\u201d, available at: http:\/\/techcrunch.com\/2012\/02\/15\/facebook-verified-accounts-alternate-names\/ (accessed 14 January 2014)."},{"key":"key2022020205381366900_ref010","first-page":"62","article-title":"Using social network analysis for spam detection","volume-title":"Proceeding Advance Social Computer","year":"2010"},{"first-page":"351","article-title":"Privacy wizards for social networking sites","year":"2010","key":"key2022020205381366900_ref011"},{"year":"2013","key":"key2022020205381366900_ref012","article-title":"Friend or foe? Fake profile identification in online social networks"},{"key":"key2022020205381366900_ref013","unstructured":"Infoglide (2014), \u201cMinormonitor\u2014Facebook monitoring and parental control software\u201d, available at: http:\/\/www.minormonitor.com\/ (accessed 14 January 2014)."},{"issue":"6-7","key":"key2022020205381366900_ref014","first-page":"2126","article-title":"Application of rough set theory in data mining market analysis using rough sets data explorer","volume":"15","year":"2018","journal-title":"Journal of Computational and Theoretical Nanoscience"},{"volume-title":"Facebook's Security Check Asks Users to Identify Photos of Friends' Dogs","year":"2010","key":"key2022020205381366900_ref015"},{"issue":"1","key":"key2022020205381366900_ref016","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s10619-013-7124-8","article-title":"Detecting and predicting privacy violations in online social networks","volume":"32","year":"2014","journal-title":"Distributed and Parallel Databases"},{"key":"key2022020205381366900_ref017","doi-asserted-by":"publisher","first-page":"237","DOI":"10.4018\/978-1-7998-3591-2.ch015","article-title":"Neuro-fuzzy-based smart irrigation system and multimodal image analysis in static-clustered wireless sensor network for marigold crops","year":"2020","journal-title":"Advances in Bioinformatics and Biomedical Engineering"},{"issue":"5","key":"key2022020205381366900_ref018","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1080\/00051144.2019.1643963","article-title":"Fuzzy-based fault-tolerant and instant synchronization routing technique in wireless sensor network for rapid transit system","volume":"60","year":"2019","journal-title":"Automatika"},{"issue":"2","key":"key2022020205381366900_ref019","doi-asserted-by":"crossref","first-page":"41","DOI":"10.4018\/IJWP.2019070103","article-title":"Personalized content extraction and text classification using effective Web scraping techniques","volume":"11","year":"2019","journal-title":"International Journal of Web Portals"},{"key":"key2022020205381366900_ref020","first-page":"2:1","article-title":"Strategies for privacy negotiation in online social networks","volume-title":"Proceedings of the 1st International Workshop on AI for Privacy and Security (PrAISe)","year":"2016"},{"first-page":"1361","article-title":"Argumentation for resolving privacy disputes in online social networks: (extended abstract)","year":"2016","key":"key2022020205381366900_ref021"},{"issue":"1","key":"key2022020205381366900_ref022","first-page":"6:1","article-title":"A framework for computing the privacy scores of users in online social networks","volume":"5","year":"2010","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"first-page":"61","article-title":"Analyzing Face book privacy settings: user expectations vs reality","year":"2011","key":"key2022020205381366900_ref023"},{"key":"key2022020205381366900_ref024","first-page":"809","article-title":"Poster Preliminary analysis of Google+'s privacy","volume-title":"Proceedings 18th ACM Conference\u00a0on\u00a0Computer\u00a0and\u00a0Communications Security","year":"2011"},{"key":"key2022020205381366900_ref025","first-page":"112","article-title":"Negotiating privacy constraints in online social networks","volume-title":"Advances in Social Computing and Multiagent Systems, Communications in Computer and Information Science","year":"2015"},{"key":"key2022020205381366900_ref026","doi-asserted-by":"crossref","unstructured":"O'Leary, J. (2013), \u201cGetting started with login verification\u201d, available at: https:\/\/blog.twitter.com\/2013\/getting-started-login-verification (accessed 14 January 2014).","DOI":"10.1007\/978-1-4302-5867-4_1"},{"first-page":"64","article-title":"A semantic context-aware privacy model for faceblock","year":"2014","key":"key2022020205381366900_ref027"},{"key":"key2022020205381366900_ref028","unstructured":"Savage, J. (2016), \u201cTop 5 facebook video statistics for 2016 [infographic]\u201d, available at: http:\/\/www.socialmediatoday.com\/marketing\/top-5-facebook-video-statistics-2016-infographic (accessed 4 April 2017)."},{"key":"key2022020205381366900_ref029","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.chb.2014.10.059","article-title":"Information disclosure on social networking sites: an intrinsic extrinsic motivation perspective","volume":"44","year":"2015","journal-title":"Computers in Human Behavior"},{"key":"key2022020205381366900_ref030","unstructured":"Song (2011), \u201cIntroducing login approvals\u201d, available at: https:\/\/www.facebook.com\/note.php?note_id=10150172618258920 (accessed 14 January 2014)."},{"key":"key2022020205381366900_ref031","unstructured":"Sophos (2011), \u201cSecurity threat report\u201d, available at: https:\/\/tavaana.org\/sites\/default\/files\/sophos-security- threat- report- 2011.pdf (accessed 04 April 2017)."},{"issue":"3","key":"key2022020205381366900_ref032","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1002\/asi.21473","article-title":"Cope: enabling collaborative privacy management in online social networks","volume":"62","year":"2011","journal-title":"Journal of the American Society for Information Science and Technology"},{"key":"key2022020205381366900_ref033","unstructured":"Statista (2010), \u201cNumber of social media users worldwide from 2010 to 2020 (in billions)\u201d, available at: https:\/\/www.statista.com\/statistics\/278414\/number- of- worldwide- social- network- users\/ (accessed 3 April 2017)."},{"issue":"5","key":"key2022020205381366900_ref034","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.clsr.2010.07.006","article-title":"Privacy and social networks","volume":"26","year":"2010","journal-title":"Computer Law and Security Review"},{"issue":"4","key":"key2022020205381366900_ref035","doi-asserted-by":"crossref","first-page":"6079","DOI":"10.1007\/s11042-016-3555-3","article-title":"A multi-feature approach to detect Stegobot: a covert multimedia social network botnet","volume":"76","year":"2017","journal-title":"Multimedia Tools\u00a0and Applications"},{"key":"key2022020205381366900_ref036","unstructured":"Websense (2014), [online], available at: http:\/\/www.websense.com\/ (accessed 14 January 2014)."},{"key":"key2022020205381366900_ref037","unstructured":"Zephoria Digital Marketing (2016), \u201cThe top 20 valuable Facebook statistics \u2013updated\u201d, available at: https:\/\/zephoria.com\/top-15-valuable- facebook- statistics\/ (accessed 04 April 2017)."}],"container-title":["International Journal of Intelligent Computing and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJICC-05-2021-0093\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJICC-05-2021-0093\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T22:54:19Z","timestamp":1753397659000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/ijicc\/article\/15\/1\/75-91\/122139"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,15]]},"references-count":37,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,10,15]]},"published-print":{"date-parts":[[2022,2,2]]}},"alternative-id":["10.1108\/IJICC-05-2021-0093"],"URL":"https:\/\/doi.org\/10.1108\/ijicc-05-2021-0093","relation":{},"ISSN":["1756-378X"],"issn-type":[{"type":"print","value":"1756-378X"}],"subject":[],"published":{"date-parts":[[2021,10,15]]}}}