Background
Motivation towards cooperative privacy
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To keep the information society growing on over a period of time, preservation of privacy is necessary It is just like trying to solve the global issues (e.g. international terrorism, global warming etc.) to sustain the physical world. Now, information society gives importance to preservation of privacy as they understand its significance but are scared of using these services. The people are forced towards privacy preservation in information society, just like the importance given to Go-Green and No Plastic by the environmentalists in society.
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As far as possible, privacy should be maintained by the rational cooperation of others, in absence of which the entire information system may be inconsistent It is similar to the traffic rules. If a person doesn’t follow the traffic rules, it causes a trouble to others and some times it may lead to deadlock. Even though the government has scaffold privacy of users as human rights, they still remain quite unrealistic. Just the setting of rules by the government is not enough to achieve privacy preservation, effort should be put by the technology people to enforce the users to maintain privacy world. At the same time there should be a rational cooperation among the users for societal usefulness.
Related work
Preliminaries
k-anonymity
Job | Sex | Age | Disease |
---|---|---|---|
Professional | Person | [25–30] | Cancer |
Professional | Person | [25–30] | HIV |
Professional | Person | [25–30] | Asthma |
Artist | Female | [30–35] | HIV |
Artist | Female | [30–35] | Hepatitis |
Artist | Female | [30–35] | Flu |
Job | Sex | Age | Disease |
---|---|---|---|
Lawyer | Male | 28 | Cancer |
Engineer | Male | 25 | HIV |
Doctor | Female | 30 | Asthma |
Writer | Female | 34 | HIV |
Singer | Female | 32 | Hepatitis |
Dancer | Female | 35 | Flu |
Cooperative game
Convex cooperative game
The core
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Individual rationality: \(\forall i \in \mathbf N , \,x_{i}\ge \nu (\{i\})\)
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Collective rationality: \(\sum\limits_{i\in \mathbf N }{x_{i}}=\nu (\mathbf N )\)
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Coalitional rationality: \(\forall S \subseteq \mathbf N , \,\sum\limits_{i\in \mathbf N }{x_{i}}\ge \nu (S)\)
Shapley value
Cooperative Privacy Game Model
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Each tuple is a player and \(\mathbf N =\mathcal {D}_{QID}\), so \(|\mathbf N |= n\).
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Every player interacts with other players and tries to maximize their CoV as it depends on the ‘average increase in their worth’ across all valid subsets.
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The characteristic function \(\nu\) is defined as follows for all coalitions \(S\subseteq \mathbf N\)
Convexity of CoPG
Complexity of calculating cooperative value
Achieving cooperative privacy
Calculating values of cooperation
Evaluation of CoV
Process of seclusion
Anonymization
Experimentation and empirical analysis
Number of coalitions vs \(\beta\) and \(\gamma\)
Number of outliers vs \(\beta\) and \(\gamma\)
Information loss vs \(\beta\) and \(\gamma\)
Information loss vs size of data set
Representation of information loss, \(\beta\) and \(\gamma\)
Conclusions and future work
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Expanding this approach to incorporate the security functionalities which are obtained from the players involved in the game.
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Expanding the theory to design a game model with mixed strategies rather than pure strategies for Cooperative privacy because the user in the game may act differently with other players.
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In experimentation process outliers were obtained. To decrease the possible outliers appropriate mechanisms are to be incorporated to the model.
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Extensive study of theory is necessary for the choice of \(\beta\) and \(\gamma\).