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Sharing-Habits Based Privacy Control in Social Networks [chapter]

Silvie Levy, Ehud Gudes, Nurit Gal-Oz
2016 Lecture Notes in Computer Science  
We study users behavior in online social networks (OSN) as a means to preserve privacy. People widely use OSN for a variety of objectives and fields. Each OSN has different characteristics, requirements, and vulnerabilities of the private data shared. Sharing-habits refers to users' patterns of sharing information. These sharing-habits implied by the communication between users and their peers hides a lot of additional private information. Most users are not aware that the sensitive private
more » ... rmation they share might leak to unauthorized users. We use several different well-known strategies from graph flows, and the sharing-habits of information flow among OSN users to define efficient and easy to implement algorithms for ensuring privacy preservation with a predefined privacy level.
doi:10.1007/978-3-319-41483-6_16 fatcat:urbb2piepffvfgxkjb4x7z7qnm

Sharing Reputation Across Virtual Communities

Nurit Gal-Oz, Tal Grinshpoun, Ehud Gudes
2010 Journal of Theoretical and Applied Electronic Commerce Research  
Trust and reputation systems for virtual communities are gaining increasing research attention. These systems track members' activities and obtain their reputation to improve the quality of member interactions and reduce the effect of fraudulent members. As virtual communities become a central playground for internet users, the reputation a member gains within a community may be viewed as a social credential. These credentials can serve the user as a means for promoting her status in new
more » ... ties on one hand, and on the other hand assist virtual communities to broaden their knowledge about users with relatively low activity volume. The Cross-Community Reputation (CCR) model was designed for sharing reputation knowledge across communities. The model identifies the fundamental terms that are required for a meaningful sharing of reputation information between communities and proposes methods to make that information sharing feasible within the boundaries of users' and communities' policies. This paper presents the CR model and draws the architecture guidelines for designing an infrastructure to support it. The proposed model is evaluated by using a sample of real-world users' ratings as well as by conducting a dedicated experiment with real users. The results of the experimental evaluation demonstrate the effectiveness of the CCR model in various aspects. A number of papers on Trust and Reputation discuss aspects important for cross-community reputation. The problem of uncertainty and confidence in computing reputation is discussed in [12] , [20] . The Beta reputation model [12] presents a formal framework for computing the uncertainty in a single community case. The problem of providing privacy while transferring reputation from one community to another was investigated in [17] . Lee and Yu [16] introduce the idea of a composite model of trust that allows the composition of both reputation data (horizontal trust) and credentials (vertical trust). Their paper suggests a new policy language that allows such compositions. However, it does not deal with the computation of the aggregated trust. Some commercial products provide a very simple notion of cross-community reputation, e.g. iKarma (Site 2) and TrustPlus (Site 3), which do not exhibit the complexities of the concept as presented here. The present paper introduces a model for computing CCR (see also [8] ). A community that wishes to receive CCR data regarding one of its users sends a request to relevant communities either directly or through a trusted third party. Communities that have reputation data of the user and are willing to share the information reply with the relevant reputation data. The received data is assembled into an object containing the CCR data of the user in the context of the requesting community. Figure 2: Request for CCR scenario The storage issue also effects user privacy and control. Any form of centralized storage (which is a must when using the push model) prevents any possibility for distributed and private CCR computation. Moreover, an untrustworthy CCRP using a centralized storage substantially compromises the privacy of the users. On the other hand, using the pull model with no centralized storage enables the development of distributed methods for private CCR computation. Such methods are out of the scope of this paper (see [9] ). Trigger -this aspect reflects the events that trigger data updates. We consider two strategies: • On-demand -in this reactive strategy the data updates are initiated only when needed • Periodic -in this proactive strategy the data updates are initiated periodically in a predefined frequency The tradeoffs between these strategies are in data-validity, availability, latency and network load. Choosing to update data on-demand ensures that the data (if available) is valid in the sense that it is up-to-date. When combined with the pull model, the on-demand strategy implies a low network load, but may suffer from availability and latency issues. When the on-demand strategy is combined with the push model, there are naturally no availability problems. However, the network load is considerably higher, since a community initiates an update following every change (or threshold breach, depending on the sensitivity used) in the local reputation of one of its users. Another option is to use periodic updates that follow a predefined frequency. The choice of the update frequency leads to a clear tradeoff between data-validity and network load. Sensitivity -this aspect reflects the amount of change in local reputation that yields a data update: • Any change -any change in the local reputation yields a data update • Threshold -only a change in the local reputation that surpasses a predefined threshold yields a data update The tradeoff of sensitivity is between accuracy and network load. There are actually not two options here, but rather a continuous function of the threshold value that reflects the sensitivity of update initiations. This is because the any change option can be considered as a threshold of ε > 0. The use of a low threshold value results in accurate data, but with the price of a heavy network load. On the other hand, using increasingly higher threshold values lowers the network load at the price of impaired accuracy. Note the difference between accuracy and data-validity. Non-valid data means that the reputation value may no longer be relevant due to extreme changes in local reputation data that the CCRP is not yet informed of. On the other hand, the level of accuracy bounds the possible error in the reputation data. Thus, there is more control over inaccurate data than over non-valid data. Each of the discussed aspects implies a tradeoff between system performance (i.e., network load) and some measure of quality (e.g., data-validity, accuracy). There might also be storage and privacy implications. We next present several combinations of these aspects that suit different needs. Push-OnDemand-AnyChange -this combination may be used when the main requirement is the quality of the CCR reputation, i.e. availability, data-validity, and accuracy. The cost is clearly in the system performance as well as in reduced user privacy. Any change in local reputation is immediately pushed by the community. Consequently, the CCRP always holds available, up-to-date, and completely accurate reputation information. However, any change in any community is immediately sent to the CCRP causing an extremely heavy network load. Moreover, the CCRP has to store all the data centrally, causing reduced user privacy. Pull-OnDemand -this combination may be used when the main requirement is maximizing user privacy. Naturally with such a requirement at hand, no caching of reputation data may be performed by the CCRP. This solution may lead to availability problems. If CCR quarries are very frequent this solution also implies a heavy network load. In the general case there should be some balance between performance, quality, and privacy needs. We therefore propose the following hybrid alternative. Pull-PushNotify-Cache -each community notifies the CCRP when one of its members' reputation has significantly changed (surpassed a threshold). The CCRP collects these notifications (as well as their respective change ratios). When needed, a community requests CCR data on-demand, and the CCRP pulls only the data it needs based on the notifications it got. The CCRP may also cache recent reputation values, so some redundant pulls may be saved. This alternative does require some storage, but it is much smaller than the storage required for complete storage of reputations.
doi:10.4067/s0718-18762010000200002 fatcat:hdaukbmtunhj3fuopqpkbqxdb4

Identifying Knots of Trust in Virtual Communities [chapter]

Nurit Gal-Oz, Ran Yahalom, Ehud Gudes
2011 IFIP Advances in Information and Communication Technology  
Knots of trust are groups of community members having overall "strong" trust relations between them. In previous work we introduced the knot aware trust based reputation model. According to this model, in order to provide a member with reputation information relative to her viewpoint, the system must identify the knot to which that member belongs and interpret its reputation data correctly. In the current paper we present the problem of identifying knots which is modeled as a graph clustering
more » ... oblem, where vertices correspond to individuals and edges describe trust relationships between them. We propose a new perspective for clustering that reflects the subjective idea of trust and the nature of the community. A class of weight functions is suggested for assigning edge weights and their impact on the stability and strength of knots is demonstrated. Finally we show the efficiency of knots of high quality for providing their members with relevant reputation information.
doi:10.1007/978-3-642-22200-9_8 fatcat:62scwci63nct3n7blyus2wgkgi

Schemes for Privately Computing Trust and Reputation [chapter]

Nurit Gal-Oz, Niv Gilboa, Ehud Gudes
2010 IFIP Advances in Information and Communication Technology  
Trust and Reputation systems in distributed environments attain widespread interest as online communities are becoming an inherent part of the daily routine of Internet users. Several models for Trust and Reputation have been suggested recently, among them the Knots model [8] . The Knots model provides a member of a community with a method to compute the reputation of other community members. Reputation in this model is subjective and tailored to the taste and choices of the computing member
more » ... those members that have similar views, i.e. the computing member's Trust-Set. A discussion on privately computing trust in the Knots model appears in [16] . The present paper extends and improves [16] by presenting three efficient and private protocols to compute trust in trust based reputation systems that use any trust-sets based model. The protocols in the paper are rigorously proved to be private against a semi-honest adversary given standard assumptions on the existence of an homomorphic, semantically secure, public key encryption system. The protocols are analyzed and compared in terms of their privacy characteristics and communication complexity.
doi:10.1007/978-3-642-13446-3_1 fatcat:3lzrhz652redxcgngib2vzcb6u

A Topology Based Flow Model for Computing Domain Reputation [chapter]

Igor Mishsky, Nurit Gal-Oz, Ehud Gudes
2015 Lecture Notes in Computer Science  
A Topology based Flow Model for Computing Domain Reputation Igor Mishsky 1 , Nurit Gal-Oz 2 and Ehud Gudes 1 1 Ben-Gurion University, Beer-Sheva, 84105, Israel,,  ... 
doi:10.1007/978-3-319-20810-7_20 fatcat:cbj5qvkk65dg5m4fdu6f5nnjjm

Methods for Computing Trust and Reputation While Preserving Privacy [chapter]

Ehud Gudes, Nurit Gal-Oz, Alon Grubshtein
2009 Lecture Notes in Computer Science  
Trust and Reputation systems in distributed environments attain widespread interest as online communities are becoming an inherent part of the daily routine of Internet users. Trust-based models enable safer operation within communities to which information exchange and peer to peer interaction are centric. Several models for trust based reputation have been suggested recently, among them the Knots model [5] . In these models, the subjective reputation of a member is computed using information
more » ... rovided by a set of members trusted by the latter. The present paper discusses the computation of reputation in such models, while preserving members' private information. Three different schemes for the private computation of reputation are presented, and the advantages and disadvantages in terms of privacy and communication overhead are analyzed.
doi:10.1007/978-3-642-03007-9_20 fatcat:dcnjb6b4dbds3hv5l6qdhimbia

Knots Maintenance for Optimal Management of Trust Relations [chapter]

Libi Gur, Nurit Gal-Oz, Ehud Gudes
2014 IFIP Advances in Information and Communication Technology  
Gal-Oz et al. [3] ] discussed the problem of partitioning the members of the community into knots and introduced a knots clustering algorithm.  ...  The knot-aware trust-based reputation model for virtual communities introduced by Gal-Oz et al. [2] refers to a community as a collection of knots (sub-communities).  ... 
doi:10.1007/978-3-662-43813-8_13 fatcat:yljuic7pbfh3fkxllewcuz5lxm

Trust and reputation in and across virtual communities

Nurit Gal-Oz, Ehud Gudes
2013 Proceedings of the 16th International Conference on Extending Database Technology - EDBT '13  
Trust and Reputation systems have become key enablers of positive interaction experiences on the Web. These systems accumulate information regarding activities of people or peers in general, to infer their reputation in some context or within a virtual community. Reputation information improves the quality of interactions between peers and reduces the effect of fraudulent members. In this tutorial we motivate the use of trust and reputation systems and survey some of the important models
more » ... ced in the past decade. Among these models, we present our work on the knot model, which deals with communities of strangers. Special attention is given to the way existing models tackle attempts to attack reputation systems. In a dynamic world, a person or a service may be a member of multiple communities and valuable information can be gained by sharing reputation of members among communities. In the second part of the tutorial, we present the CCR model for sharing reputation across virtual communities and address major privacy concerns related to it. In the third part of our talk, we discuss the use of reputation systems in other contexts, such as domain reputation for fighting malware, and outline our research directions on this subject.
doi:10.1145/2452376.2452477 dblp:conf/edbt/Gal-OzG13 fatcat:trwmxr2d3veqbj3sdvpsnzcqay

Privacy issues with sharing reputation across virtual communities

Nurit Gal-Oz, Tal Grinshpoun, Ehud Gudes
2011 Proceedings of the 4th International Workshop on Privacy and Anonymity in the Information Society - PAIS '11  
Online communities are the new-age platform for sharing information and experiences with groups of people. Members of a community are dealing with the daily conflict of having to decide what information they are willing to disclose in order to increase their reputation. Fear of possible privacy loss may lead a member to avoid sharing information with others, even when acting anonymously. Privacy concerns are amplified when users are members of multiple communities and their overall reputation
more » ... obtained from their reputation in each community. Disclosing a piece of reputation-related information in one community may cause privacy loss in another community and vice versa. This paper outlines the privacy concerns in the Cross-Community Reputation (CCR) model for sharing reputation knowledge across communities. These privacy concerns are discussed and modeled, and a policy-based approach that copes with them is presented.
doi:10.1145/1971690.1971693 dblp:conf/edbt/Gal-OzGG11 fatcat:6eh5um7t6fbb7jh6mqvowfrwiy

Security Issues in NoSQL Databases

Lior Okman, Nurit Gal-Oz, Yaron Gonen, Ehud Gudes, Jenny Abramov
2011 2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications  
The recent advance in cloud computing and distributed web applications has created the need to store large amount of data in distributed databases that provide high availability and scalability. In recent years, a growing number of companies have adopted various types of non-relational databases, commonly referred to as NoSQL databases, and as the applications they serve emerge, they gain extensive market interest. These new database systems are not relational by definition and therefore they
more » ... not support full SQL functionality. Moreover, as opposed to relational databases they trade consistency and security for performance and scalability. As increasingly sensitive data is being stored in NoSQL databases, security issues become growing concerns. This paper reviews two of the most popular NoSQL databases (Cassandra and MongoDB) and outlines their main security features and problems. International Joint Conference of IEEE TrustCom-11/IEEE ICESS-11/FCST-11 978-0-7695-4600-1/11 $26.00
doi:10.1109/trustcom.2011.70 dblp:conf/trustcom/OkmanGGGA11 fatcat:7cnrna3drfczfehjymdp25uzbi

CCR: A Model for Sharing Reputation Knowledge Across Virtual Communities

Tal Grinshpoun, Nurit Gal-Oz, Amnon Meisels, Ehud Gudes
2009 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology  
Information sharing is a key objective in the age of Internet and virtual communities. Reputation information is an important part of a user's identity and is both a sensitive and desired data for communities to share. At the same time, a reputation that a user has gained at some point in time can leverage her state in new communities. Communities use various trust and reputation models to compute the internal reputation of their members and each model may represent and quantify reputation in
more » ... fferent manners. This paper introduces the Cross-Community Reputation (CCR) model that enables to bridge the gap between communities. The CCR model identifies the fundamental terms required for a meaningful sharing of reputation information among communities and proposes means to make them feasible. The model describes the actions taken in response to a request for CCR in three major stages -evaluation of preconditions, conversion of reputation values, and the matching of reputation attributes. The CCR model inherently supports policies specified by both communities and users.
doi:10.1109/wi-iat.2009.13 dblp:conf/webi/GrinshpounGMG09 fatcat:keq7a4cusbg75bvbepsmz6zutm

A Robust and Knot-Aware Trust-Based Reputation Model [chapter]

Nurit Gal-Oz, Ehud Gudes, Danny Hendler
IFIP – The International Federation for Information Processing  
Virtual communities become more and more heterogeneous as their scale increases. This implies that, rather than being a single, homogeneous community, they become a collection of knots (or sub-communities) of users. For the computation of a member's reputation to be useful, the system must therefore identify the community knot to which this member belongs and to interpret its reputation data correctly. Unfortunately, to the best of our knowledge existing trust-based reputation models treat a
more » ... munity as a single entity and do not explicitly address this issue. In this paper, we introduce the knot-aware trust-based reputation model for large-scale virtual communities. We define a knot as a group of community members having overall "strong" trust relations between them. Different knots typically represent different view points and preferences. It is therefore plausible that the reputation of the same member in different knots assign may differ significantly. Using our knot-aware approach, we can deal with heterogeneous communities where a member's reputation may be distributed in a multi modal manner. As we show, an interesting and beneficial feature of our knot-aware model is that it naturally prevents malicious attempts to bias community members' reputation.
doi:10.1007/978-0-387-09428-1_11 dblp:conf/ifiptm/Gal-OzGH08 fatcat:eqbfj7fzgrdrraos55x33utkom

Guest Editors' Introduction Trust and Trust Management

Audun Jøsang, Glenn Bewsell
2010 Journal of Theoretical and Applied Electronic Commerce Research  
The first paper entitled "Sharing Reputation Across Virtual Communities" co-authored by Nurit Gal-Oz, Tal Grinshpoun and Ehud Gudes evaluates a Cross-Community Reputation (CCR) model with the ability to  ...  The first paper entitled "Sharing Reputation Across Virtual Communities" co-authored by Nurit Gal-Oz, Tal Grinshpoun and Ehud Gudes evaluates a Cross-Community Reputation (CCR) model with the ability to  ... 
doi:10.4067/s0718-18762010000200001 fatcat:cdfe74eu5fccdjxjdbvftzo2pq

Guest Editorial: Advances in Trust Management

Kangbin Yim
2010 Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications  
The next paper [2], "Privacy Issues with Sharing and Computing Reputation across Communities" by Nurit Gal-Oz, Tal Grinshpoun and Ehud Gudes, sketches the privacy issues in the Cross-Community Reputation  ... 
doi:10.22667/jowua.2010.12.31.001 dblp:journals/jowua/Yim10 fatcat:gfbz4vajmbbmbn2cfop54l6voi

On Memory and I/O Efficient Duplication Detection for Multiple Self-clean Data Sources [chapter]

Ji Zhang, Yanfeng Shu, Hua Wang
2010 Lecture Notes in Computer Science  
Krishna Reddy (International Institute of Information Technology-Hyderabad, India) • CAMLS: A Constraint-based Apriori Algorithm for Mining Long Sequences Yaron Gonen, Nurit Gal-Oz, Ran Yahalom, Ehud Gudes  ... 
doi:10.1007/978-3-642-14589-6_14 fatcat:utkcwnmy6fbj5jt7ryvrk2pu3y
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