Online Social Networks (OSNs) allow users to create a public or private profile, encourage sharing information and interests with other users and communicating with each other. As a result, OSNs are being used by millions of people and they are now part of our everyday life. People use OSNs to keep in touch with family, friends, to share personal information, as well as for business purposes. Users of an OSN build connections with their friends, colleagues and people over time. These connections form a social graph that controls how information spreads in the social network.
Abstract:
Although the dramatic increase in Online Social Network (OSN) usage, there are still a lot of security and privacy concerns. In such a scenario, it would be very benefici...Show MoreMetadata
Abstract:
Although the dramatic increase in Online Social Network (OSN) usage, there are still a lot of security and privacy concerns. In such a scenario, it would be very beneficial to have a mechanism able to assign a risk score to each OSN user. For this reason, in this paper, we propose a risk assessment based on the idea that the more a user behavior diverges from what it can be considered as a `normal behavior', the more it should be considered risky. In doing this, we have taken into account that OSN population is really heterogeneous in observed behaviors. As such, it is not possible to define a unique standard behavioral model that fits all OSN users' behaviors. However, we expect that similar people tend to follow similar rules with the results of similar behavioral models. For this reason, we propose a risk assessment approach organized into two phases: similar users are first grouped together, then, for each identified group, we build one or more models for normal behavior. The carried out experiments on a real Facebook dataset show that the proposed model outperforms a simplified behavioral-based risk assessment where behavioral models are built over the whole OSN population, without a group identification phase.
Published in: IEEE Transactions on Dependable and Secure Computing ( Volume: 15, Issue: 2, 01 March-April 2018)
Funding Agency:
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DISTA, University of Insubria, Varese, Italy
Naeimeh Laleh is currently working toward the PhD degree in computer
science under the iSocial Marie Curie Initial Training Network project with a focus on privacy, risk analysis in
decentralized online social networks at the University of Insubria, Italy. Her research interests include risk
analysis in big data, online social network analysis, graph processing algorithms for fraud/anomaly/attack detection,
stream gra...Show More
Naeimeh Laleh is currently working toward the PhD degree in computer
science under the iSocial Marie Curie Initial Training Network project with a focus on privacy, risk analysis in
decentralized online social networks at the University of Insubria, Italy. Her research interests include risk
analysis in big data, online social network analysis, graph processing algorithms for fraud/anomaly/attack detection,
stream gra...View more

DISTA, University of Insubria, Varese, Italy
Barbara Carminati received the PhD degree in computer science from
the University of Milano, Italy. She is an associate professor of computer science at the University of Insubria,
Italy. Her main research interests include related to security and privacy for innovative applications, like XML data
sources, semantic web, secure cloud computing, web services, data streams and online social networks. She has been
involve...Show More
Barbara Carminati received the PhD degree in computer science from
the University of Milano, Italy. She is an associate professor of computer science at the University of Insubria,
Italy. Her main research interests include related to security and privacy for innovative applications, like XML data
sources, semantic web, secure cloud computing, web services, data streams and online social networks. She has been
involve...View more

DISTA, University of Insubria, Varese, Italy
Elena Ferrari received the PhD degree in computer science from the
University of Milano, Italy. She is a full professor of computer science at the University of Insubria, Italy, where
she leads the STRICT Socialab and is the scientific director of the K& SM Research Center. Her research interests
include data security, privacy, and trust. She received the IEEE Computer Society's 2009 Technical Achievement
Award for ‘o...Show More
Elena Ferrari received the PhD degree in computer science from the
University of Milano, Italy. She is a full professor of computer science at the University of Insubria, Italy, where
she leads the STRICT Socialab and is the scientific director of the K& SM Research Center. Her research interests
include data security, privacy, and trust. She received the IEEE Computer Society's 2009 Technical Achievement
Award for ‘o...View more

DISTA, University of Insubria, Varese, Italy
Naeimeh Laleh is currently working toward the PhD degree in computer
science under the iSocial Marie Curie Initial Training Network project with a focus on privacy, risk analysis in
decentralized online social networks at the University of Insubria, Italy. Her research interests include risk
analysis in big data, online social network analysis, graph processing algorithms for fraud/anomaly/attack detection,
stream graph mining, machine learning, fraud detection in banking.
Naeimeh Laleh is currently working toward the PhD degree in computer
science under the iSocial Marie Curie Initial Training Network project with a focus on privacy, risk analysis in
decentralized online social networks at the University of Insubria, Italy. Her research interests include risk
analysis in big data, online social network analysis, graph processing algorithms for fraud/anomaly/attack detection,
stream graph mining, machine learning, fraud detection in banking.View more

DISTA, University of Insubria, Varese, Italy
Barbara Carminati received the PhD degree in computer science from
the University of Milano, Italy. She is an associate professor of computer science at the University of Insubria,
Italy. Her main research interests include related to security and privacy for innovative applications, like XML data
sources, semantic web, secure cloud computing, web services, data streams and online social networks. She has been
involved in the organization of several international conferences as program committee member as well as program and
general chair.
Barbara Carminati received the PhD degree in computer science from
the University of Milano, Italy. She is an associate professor of computer science at the University of Insubria,
Italy. Her main research interests include related to security and privacy for innovative applications, like XML data
sources, semantic web, secure cloud computing, web services, data streams and online social networks. She has been
involved in the organization of several international conferences as program committee member as well as program and
general chair.View more

DISTA, University of Insubria, Varese, Italy
Elena Ferrari received the PhD degree in computer science from the
University of Milano, Italy. She is a full professor of computer science at the University of Insubria, Italy, where
she leads the STRICT Socialab and is the scientific director of the K& SM Research Center. Her research interests
include data security, privacy, and trust. She received the IEEE Computer Society's 2009 Technical Achievement
Award for ‘outstanding and innovative contributions to secure data management.’ She is an ACM
Distinguished Scientist. She is fellow of the IEEE.
Elena Ferrari received the PhD degree in computer science from the
University of Milano, Italy. She is a full professor of computer science at the University of Insubria, Italy, where
she leads the STRICT Socialab and is the scientific director of the K& SM Research Center. Her research interests
include data security, privacy, and trust. She received the IEEE Computer Society's 2009 Technical Achievement
Award for ‘outstanding and innovative contributions to secure data management.’ She is an ACM
Distinguished Scientist. She is fellow of the IEEE.View more