TY - GEN
T1 - Trust Based Resolving of Conflicts for Collaborative Data Sharing in Online Social Networks
AU - Shetty, Nisha P.
AU - Muniyal, Balachandra
AU - Prakhar, Pratyay
AU - Singh, Angad
AU - Batra, Gunveen
AU - Puri, Akshita
AU - Manjunath, Divya Bhanu
AU - Jain, Vidit Vinay
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - Twenty-first century, the era of Internet, social networking platforms like Facebook and Twitter play a predominant role in everybody’s life. Ever increasing adoption of gadgets such as mobile phones and tablets have made social media available all times. This recent surge in online interaction has made it imperative to have ample protection against privacy breaches to ensure a fine grained and a personalized data publishing online. Privacy concerns over communal data shared amongst multiple users are not properly addressed in most of the social media. The proposed work deals with effectively suggesting whether or not to grant access to the data which is co-owned by multiple users. Conflicts in such scenario are resolved by taking into consideration the privacy risk and confidentiality loss observed if the data is shared. For secure sharing of data, a trust framework based on the user’s interest and interaction parameters is put forth. The proposed work can be extended to any data sharing multiuser platform.
AB - Twenty-first century, the era of Internet, social networking platforms like Facebook and Twitter play a predominant role in everybody’s life. Ever increasing adoption of gadgets such as mobile phones and tablets have made social media available all times. This recent surge in online interaction has made it imperative to have ample protection against privacy breaches to ensure a fine grained and a personalized data publishing online. Privacy concerns over communal data shared amongst multiple users are not properly addressed in most of the social media. The proposed work deals with effectively suggesting whether or not to grant access to the data which is co-owned by multiple users. Conflicts in such scenario are resolved by taking into consideration the privacy risk and confidentiality loss observed if the data is shared. For secure sharing of data, a trust framework based on the user’s interest and interaction parameters is put forth. The proposed work can be extended to any data sharing multiuser platform.
UR - http://www.scopus.com/inward/record.url?scp=85138832812&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85138832812&partnerID=8YFLogxK
U2 - 10.1007/978-981-19-4052-1_5
DO - 10.1007/978-981-19-4052-1_5
M3 - Conference contribution
AN - SCOPUS:85138832812
SN - 9789811940514
T3 - Lecture Notes in Networks and Systems
SP - 35
EP - 48
BT - Emerging Technologies in Data Mining and Information Security - Proceedings of IEMIS 2022
A2 - Dutta, Paramartha
A2 - Chakrabarti, Satyajit
A2 - Bhattacharya, Abhishek
A2 - Dutta, Soumi
A2 - Shahnaz, Celia
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2022
Y2 - 23 February 2022 through 25 February 2022
ER -