TY - GEN
T1 - Implementing GDPR in Social Networks Using Trust and Context
AU - Voloch, Nadav
AU - Gudes, Ehud
AU - Gal-Oz, Nurit
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - The GDPR (General Data Protection Regulation) is a regulation for data protection and privacy for citizens of the EU. It also addresses the export of personal data outside the EU, thus creating a regulation the affects most, as all, of the commercial companies, government institutions, and other sectors that maintain personal information of their customers or audiences. Social Networks are, of course, major interested parties both for the GDPR since their core definitions involve both private user’s information, and data ownership issues. Thus, there is an urgent need for a sustainable and reliable privacy model for these networks, that does not currently exist. In our previous research we have devised a comprehensive Trust-based model for security in Social Networks, that uses Trust, Access Control and Flow Control. In this paper we use this model, and add an element of context to it, for creating an implementation in Social Networks, that will better enforce the GDPR and rights management regulations.
AB - The GDPR (General Data Protection Regulation) is a regulation for data protection and privacy for citizens of the EU. It also addresses the export of personal data outside the EU, thus creating a regulation the affects most, as all, of the commercial companies, government institutions, and other sectors that maintain personal information of their customers or audiences. Social Networks are, of course, major interested parties both for the GDPR since their core definitions involve both private user’s information, and data ownership issues. Thus, there is an urgent need for a sustainable and reliable privacy model for these networks, that does not currently exist. In our previous research we have devised a comprehensive Trust-based model for security in Social Networks, that uses Trust, Access Control and Flow Control. In this paper we use this model, and add an element of context to it, for creating an implementation in Social Networks, that will better enforce the GDPR and rights management regulations.
KW - Access control
KW - Flow control
KW - GDPR
KW - Social networks security
KW - Trust
UR - http://www.scopus.com/inward/record.url?scp=85111970516&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-78086-9_36
DO - 10.1007/978-3-030-78086-9_36
M3 - Conference contribution
AN - SCOPUS:85111970516
SN - 9783030780852
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 497
EP - 503
BT - Cyber Security Cryptography and Machine Learning - 5th International Symposium, CSCML 2021, Proceedings
A2 - Dolev, Shlomi
A2 - Margalit, Oded
A2 - Pinkas, Benny
A2 - Schwarzmann, Alexander
PB - Springer Science and Business Media Deutschland GmbH
T2 - 5th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2021
Y2 - 8 July 2021 through 9 July 2021
ER -
