Game theoretic analysis of multiparty access control in online social networks

Hu, Hongxin; Ahn, Gail-Joon; Zhao, Ziming; Yang, Dejun

doi:10.1145/2613087.2613097

Cited by 49 publications

(31 citation statements)

References 34 publications

(42 reference statements)

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“…In particular, researchers have analyzed conflict resolution from a game-theoretic point of view and proposed negotiation protocols based on game-theoretic concepts such as the Nash equilibrium [Hu et al 2014a;Rajtmajer et al 2016;Squicciarini et al 2010;Such and Rovatsos 2016;Xiao and Tan 2012]. For instance, Squicciarini et al [2010] use the Clarke-Tax model and game theory in the context of an auction to resolve policy conflicts by selecting the privacy policy that maximizes social utility.…”

Section: Governancementioning

confidence: 99%

Survey on Access Control for Community-Centered Collaborative Systems

2018

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The last decades have seen a growing interest and demand for community-centered collaborative systems and platforms. These systems and platforms aim to provide an environment in which users can collaboratively create, share and manage resources. While offering attractive opportunities for online collaboration and information sharing, they also open several security and privacy issues. This has attracted several research efforts towards the design and implementation of novel access control solutions that can handle the complexity introduced by collaboration. Despite these efforts, transition to practice has been hindered by the lack of maturity of the proposed solutions. The access control mechanisms typically adopted by commercial collaborative systems like online social network websites and collaborative editing platforms, are still rather rudimentary and do not provide users with a sufficient control over their resources. This survey examines the growing literature on access control for collaborative systems centered on communities, and identifies the main challenges to be addressed in order to facilitate the adoption of collaborative access control solutions in real-life settings. Based on the literature study, we delineate a roadmap for future research in the area of access control for community-centered collaborative systems.

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Section: Governancementioning

confidence: 99%

Survey on Access Control for Community-Centered Collaborative Systems

2018

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“…Authors in [24][25] highlight the risks of sharing private data and propose appropriate trade-off mechanisms where the user is informed about the usage of his data and an incentive equal to the privacy cost is offered in return. In [26] a new Multi-party Access Control (MPAC) model was proposed that uses Nash Equilibrium to obtain a unique solution for sharing data with multiple parties and identify an appropriate incentive. The difficulty with these approaches is that, they are highly influenced by the truthfulness and greediness of the user which can entice them into affecting the originality of the data.…”

Section: Related Workmentioning

confidence: 99%

Increasing user controllability on device specific privacy in the Internet of Things

Asif

Rajarajan

Lestas

2018

Computer Communications

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This is the accepted version of the paper.This version of the publication may differ from the final published version.Permanent repository link: http://openaccess.city.ac.uk/19508/ Link to published version: http://dx. AbstractWith recent advancements in information technology more and more devices are integrated in the Internet of Things. These devices gather significant amount of private information pertinent to a user and while, in some cases it helps in improving the life style of an individual, in others it raises major privacy concerns. This trade-off between utility and privacy is highly dependent upon the devices in consideration and as the utility of the generated data increases, the privacy of an individual decreases. In this paper, we formulate a utility-privacy trade-off that enables a user to make appliance specific decisions as to how much data can be shared. This is achieved by parametrizing the degree of privacy allowed for each device and enabling the user to configure the parameter of each device. We use the smart metering application as the test case scenario for the proposed approach. We evaluate its performance using simulations conducted on the ECO data set. Our results indicate that, the proposed approach is successful in identifying appliances with an accuracy of 81.8% and a precision of 70.1%. In addition, it is demonstrated that device specific changes of the configuration parameters allow the degree of privacy achieved for the particular device and the utility to be well controlled, thus demonstrating the effectiveness of the proposed approach. Moreover, it is shown that, as expected, devices with higher power consumption contribute more to the overall privacy and utility achieved. A comparative study is also conducted and the proposed approach is shown to outperform the existing ElecPrivacy approach by producing a trace that is harder to identify, as reported after testing the Weiss' and Baranski's algorithm, both of which are well known Non-Intrusive Load Monitoring algorithms. Finally, it is demonstrated that the addition of noise, which is an integral part of the propose approach, can greatly improve performance.

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“…These proposals provide an elegant analytic framework proposing negotiation protocols to study the problem and the solutions that can be obtained using well-known gametheoretic solution concepts such as the Nash equilibrium. However, as shown in [45], these proposals may not always work well in practice, as they do not capture the social idiosyncrasies considered by users in the real life when they face multi-party privacy conflicts, and users' behaviour is far from perfectly rational as assumed in these game-theoretic approaches -e.g., refer to [3], [4].…”

Section: Related Workmentioning

confidence: 99%

Resolving Multi-Party Privacy Conflicts in Social Media

Such

Criado

2016

IEEE Trans. Knowl. Data Eng.

102

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Items shared through Social Media may affect more than one user's privacy -e.g., photos that depict multiple users, comments that mention multiple users, events in which multiple users are invited, etc. The lack of multi-party privacy management support in current mainstream Social Media infrastructures makes users unable to appropriately control to whom these items are actually shared or not. Computational mechanisms that are able to merge the privacy preferences of multiple users into a single policy for an item can help solve this problem. However, merging multiple users' privacy preferences is not an easy task, because privacy preferences may conflict, so methods to resolve conflicts are needed. Moreover, these methods need to consider how users' would actually reach an agreement about a solution to the conflict in order to propose solutions that can be acceptable by all of the users affected by the item to be shared. Current approaches are either too demanding or only consider fixed ways of aggregating privacy preferences. In this paper, we propose the first computational mechanism to resolve conflicts for multi-party privacy management in Social Media that is able to adapt to different situations by modelling the concessions that users make to reach a solution to the conflicts. We also present results of a user study in which our proposed mechanism outperformed other existing approaches in terms of how many times each approach matched users' behaviour.

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Game theoretic analysis of multiparty access control in online social networks

Cited by 49 publications

References 34 publications

Survey on Access Control for Community-Centered Collaborative Systems

Survey on Access Control for Community-Centered Collaborative Systems

Increasing user controllability on device specific privacy in the Internet of Things

Resolving Multi-Party Privacy Conflicts in Social Media

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