A privacy preserving association rule mining algorithm was introducedThis algorithm preserved privacy of individual values by computing scalar productMeanwhile the algorithm of computing scalar product was given and the security was analyzed

Privacy preserving association rule mining in vertically partitioned data

A secure and privacy-preserving protocol for holding double auctions in smart grid

Internet of things(IoT) development tends to reduce the reliance on centralized servers. The zero-trust distributed system combined with blockchain technology has become a hot topic in IoT research. However, distribution data storage services and different blockchain protocols make network interoperability and cross-platform more complex. Relay chain is a promising cross-chain technology that solves the complexity and compatibility issues associated with blockchain cross-chain transactions by utilizing relay blockchains as cross-chain connectors. Yet, relay chain cross-chain transactions need to collect asset information and implement asset transactions via two-way peg. Due to the release of user transaction information, there is the issue of privacy leakage. In this paper, we propose a cross-chain privacy protection protocol based on the Groth16 zero-knowledge proof algorithm and coin-mixing technology, which changes the authentication mechanism and uses a combination of generating functions to map virtual external addresses in transactions. It allows fast cross-chain anonymous transactions while hiding the genuine user’s address. The experiment shows that, in a zero-trust IoT context, our scheme can effectively protect user privacy information, accomplish controlled transaction traceability operations, and guarantee cross-chain transaction security.

/pdf/an-anonymous-and-supervisory-cross-chain-privacy-protection-3rhn9v3y.pdf

An Anonymous and Supervisory Cross-Chain Privacy Protection Protocol for Zero-Trust IoT Application

vMixing coins strategy can realize the anonymity of user information, thereby protecting the user's privacy. Ideally, the blacklist is public information and all bad coins are recorded in it. However, due to the failure of some bad coins to be registered in the blacklist in time, users can only obtain part of the blacklist information, which allows illegal criminals to take advantage of it. How to prevent illegal activities under the partial information blacklist and how to design coins' quality updating rule rationally have become open issues in mixing coins. The updating rule of coins' quality in mixing is addressed since illegal criminals may carry out illegal activities, for example, money laundering. ImpSuic, an improved suicide strategy, is proposed as a new quality updating rule. The intuition is: all coins of the one who has the highest bad coins according to the blacklist, are recorded as bad coins. On the other hand, the coins' quality of others remain unchanged. Besides, linear programming is introduced into ImpSuic strategy to predict the maximum utility after mixing coins, which facilitates users to make reasonable decisions before mixing coins. Simulation results show that the quality updating rule in ImpSuic strategy can preserve users' privacy and antimoney launder.

ImpSuic: A quality updating rule in mixing coins with maximum utilities

Winner determination in current auctions is often performed separately by two groups: the technical expert group and the business expert group. In general, there is a strong negative correlation between technical and business attributes, and it will cause antagonistic feelings and noncooperative behaviors between the two groups under the premise of bounded rationality. First, this paper constructs a game model between the management department and experts and analyzes the conditions for achieving stable equilibrium solutions. Then, we analyze the evolutionary paths and the influencing factors of relevant behaviors based on evolutionary game theory, which reveals the influence from the individual to groups. Finally, to systematically and quantitatively study bid evaluation behaviors, a simulation system based on MATLAB GUI shows the influences on the evolutionary results as the initial conditions and decision parameters change. The study makes positive contributions to the management of bidding evaluations to improve the fairness of the bid evaluation mechanism.

/pdf/an-evolutionary-game-study-of-the-behavioral-management-of-cshobwaop6.pdf

An Evolutionary Game Study of the Behavioral Management of Bid Evaluations in Reserve Auctions

As Bitcoin users grow, the protection of the Bitcoin privacy protection becomes an important issue. Bitcoin mixing technology can cut off the connection between buyers and sellers. Now, a more effective method is used to carry out a coin mixing operation. The existing flat structure and two-layer structure have their own deficiencies. Therefore, anonymous Bitcoin mixing scheme is proposed. In order to increase the anonymity of coin mixing, group blind signature technology is used to expand the anonymous set of users. Moreover, a Supervisor for supervising Mixes is introduced to ensure the security of the system and the threshold signature is also used to ensure the security of the Mix’s Bitcoin to prevent the Supervisor from stealing Bitcoin. Finally, the security analysis and experiment are given to conclude that our scheme is secure and efficient.

Anonymous Bitcoin Mixing Scheme Based on Semi-Trusted Supervisor

One of the recent focus within the auction field has been multi-attribute auctions where buyer is not restricted to selecting the best option only by price but also other attributes. Due to the increase in the awareness of securing private information, in this paper, we design a secure reverse multi-attribute first-price auction scheme, in which the auction is processed on the bidders' encrypted bids by multiple auctioneer servers. As a result, auctioneer servers can determine the winner without knowing the real value of bids, which let bidder's privacy would not be revealed. At last, an analysis on the privacy of bids is conducted.

A Secure Reverse Multi-Attribute First-Price E-Auction Mechanism Using Multiple Auctioneer Servers Work in Progress

Recently, traditional power grid cannot satisfy the today's fast development trend of the market, and a more intelligent power system named smart grid is developed acting a significant power infrastructure. How to achieve the energy sellers and buyers' interact efficiently is a challenging problem for smart grid. The auction requires energy buyers to provide their private bid information to the energy auction servers. However, energy buyers usually do not expect the real information of the bid get leaked out, especially known by other competitors. That means the energy sellers need to inquire suitable bids while preserving the privacy of the energy buyers. In this paper, we propose a novel privacy-preserving degree-matching (PPDM) multi-attribute auction scheme which the winner is generated by comparing sorted all of matching degree between sale solution supplied by energy sellers and biddings submitted by energy buyers. Also, the quantitative and qualitative attributes are classified as quantitative assessment finally in energy sellers and buyers' bid. Security analysis demonstrates that our scheme based on the difficulty of integer factorization assumption can secure auction privacy, multi-attribute matching, personalized search, and ranked search. Furthermore, performance evaluation shows that the PPDM can significantly reduce computation overhead and it also has moderate communication overhead.

A privacy-preserving degree-matching multi-attribute auction scheme in smart grid auction market

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Papers

Anonymous Bitcoin Mixing Scheme Based on Semi-Trusted Supervisor

A Secure Reverse Multi-Attribute First-Price E-Auction Mechanism Using Multiple Auctioneer Servers Work in Progress

A privacy-preserving degree-matching multi-attribute auction scheme in smart grid auction market