TY - GEN
T1 - An Information-Flow Control Model for Online Social Networks Based on User-Attribute Credibility and Connection-Strength Factors
AU - Gudes, Ehud
AU - Voloch, Nadav
N1 - Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - During the last couple of years there have been many researches on Online Social Networks (OSN). The common manner of representing an OSN is by a user-based graph, where the vertices are different OSN users, and the edges are different interactions between these users, such as friendships, information-sharing instances, and other connection types. The question of whether a certain user is willing to share its information to other users, known and less known, is a question that occupies several researches in aspects of information security, sharing habits and information-flow models for OSN. While many approaches take into consideration the OSN graph edges as sharing-probability factors, here we present a novel approach, that also combines the vertices as well-defined attributed entities, that contain several properties, in which we seek a certain level of credibility based on the user’s attributes, such as number of total friends, age of user account, etc. The edges in our model represent the connection-strength of two users, by taking into consideration the attributes that represent their connection, such as number of mutual friend, friendship duration, etc. and the model also recognizes resemblance factors, meaning the number of similar user attributes. This approach optimizes the evaluation of users’ information-sharing willingness by deriving it from these attributes, thus creating an accurate flow-control graph that prevents information leakage from users to unwanted entities, such as adversaries or spammers. The novelty of the model is mainly its choice of integrated factors for user credibility and connection credibility, making it very useful for different OSN flow-control decisions and security permissions.
AB - During the last couple of years there have been many researches on Online Social Networks (OSN). The common manner of representing an OSN is by a user-based graph, where the vertices are different OSN users, and the edges are different interactions between these users, such as friendships, information-sharing instances, and other connection types. The question of whether a certain user is willing to share its information to other users, known and less known, is a question that occupies several researches in aspects of information security, sharing habits and information-flow models for OSN. While many approaches take into consideration the OSN graph edges as sharing-probability factors, here we present a novel approach, that also combines the vertices as well-defined attributed entities, that contain several properties, in which we seek a certain level of credibility based on the user’s attributes, such as number of total friends, age of user account, etc. The edges in our model represent the connection-strength of two users, by taking into consideration the attributes that represent their connection, such as number of mutual friend, friendship duration, etc. and the model also recognizes resemblance factors, meaning the number of similar user attributes. This approach optimizes the evaluation of users’ information-sharing willingness by deriving it from these attributes, thus creating an accurate flow-control graph that prevents information leakage from users to unwanted entities, such as adversaries or spammers. The novelty of the model is mainly its choice of integrated factors for user credibility and connection credibility, making it very useful for different OSN flow-control decisions and security permissions.
KW - Information-flow networks control
KW - Online Social Networks security
KW - Trust-based security models
UR - http://www.scopus.com/inward/record.url?scp=85049002372&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-94147-9_5
DO - 10.1007/978-3-319-94147-9_5
M3 - Conference contribution
AN - SCOPUS:85049002372
SN - 9783319941462
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 55
EP - 67
BT - Cyber Security Cryptography and Machine Learning - Second International Symposium, CSCML 2018, Proceedings
A2 - Dinur, Itai
A2 - Dolev, Shlomi
A2 - Lodha, Sachin
PB - Springer Verlag
T2 - 2nd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2018
Y2 - 21 June 2018 through 22 June 2018
ER -