On the value of private information
TARK '01 Proceedings of the 8th conference on Theoretical aspects of rationality and knowledge
IEEE Security and Privacy
Overcoming Online Information Privacy Concerns: An Information-Processing Theory Approach
Journal of Management Information Systems
A privacy expectations and security assurance offer system
NSPW '07 Proceedings of the 2007 Workshop on New Security Paradigms
Investment in privacy-preserving technologies under uncertainty
GameSec'11 Proceedings of the Second international conference on Decision and Game Theory for Security
Game theory meets network security and privacy
ACM Computing Surveys (CSUR)
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Privacy is a central concern in the information age. In some circumstances, customers' decisions whether to use firms' services rely on the extent of privacy that firms are able to provide, for example, the use of certain banking services, health care information technology [7]...etc. Firms thus face crucial assessment of investment on privacy-preserving technologies. Two important factors affect firms' valuation: (1) a customer's valuation of his private information and (2) a customer's profitability to the firm. The former determines the potential customer base that a firm can exploit given certain privacy protection, and the latter establishes profits that a firm can make. Both factors have some random components which can be best described by their descriptive probability distributions. We view firms' evaluation processes as a variant of Stackelberg type leader-follower game under complete information with customers taking the role of the follower. Firms integrate customers' optimal decisions into their valuation. Rational utility maximizing customers optimally decide whether to use firms' services by linking to their own decision threshold. The threshold is their own fair valuation of privacy connected to their private information. This fair privacy valuation is determined by a standardized premium over a fixed privacy rank related to values of private information common to the general population. This assertion is motivated by a recent research study [2]. We explore how the two underlying distributions and their dependence structures impact firms' investment valuation. Copulas, useful tools to study the relationship between random variables, are used to allow great flexibility on constructing bivariate distribution functions from arbitrarily univariate marginals with various dependence structures. We find that dependence structures and underlying univariate distributions have significant impacts on valuation. This suggests that, for appropriate investment decision making, firms shall be cautious on estimating underlying univariate distributions and their dependence structures. If distribution validation is not empirically possible, firms shall proceed with distributions and dependence structures which are practically justifiable for their market segments/industries. Our results identify several cases where the government intervention may be required to have firms invest in privacy-preserving technologies.