This paper proposes a new proactive weighted threshold signature scheme based on Iflene＇s general secret sharing, the generalized Chinese remainder theorem, and the RSA threshold signature, which is itself based on t...This paper proposes a new proactive weighted threshold signature scheme based on Iflene＇s general secret sharing, the generalized Chinese remainder theorem, and the RSA threshold signature, which is itself based on the Chinese reminder theorem. In our scheme, group members are divided into different subgroups, and a positive weight is associated to each subgroup, where all members of the same subgroup have the same weight. The group signature can be generated if and only if the sum of the weights of members involved is greater than or equal to a fixed threshold value. Meanwhile, the private key of the group members and the public key of the group can be updated periodically by performing a simple operation aimed at refreshing the group signature message. This periodical refreshed individual signature message can enhance the security of the proposed weighted threshold signature scheme.展开更多
Traditional k-anonymity schemes cannot protect a user＇s privacy perfectly in big data and mobile network environments. In fact, existing k-anonymity schemes only protect location in datasets with small granularity. B...Traditional k-anonymity schemes cannot protect a user＇s privacy perfectly in big data and mobile network environments. In fact, existing k-anonymity schemes only protect location in datasets with small granularity. But in larger granularity datasets, a user＇s geographical region-location is always exposed in realizations of k-anonymity because of interaction with neighboring nodes. And if a user could not find enough adjacent access points, most existing schemes would be invalid. How to protect location information has become an important issue. But it has not attracted much attention. To solve this problem, two location-privacy protection models are proposed. Then a new generalized k-anonymity Location Privacy Protection Scheme based on the Chinese Remainder Theorem （LPSS-CRT） in Location-Based Services （LBSs） is proposed. We prove that it can guarantee that users can access LBSs without leaking their region-location information, which means the scheme can achieve perfect anonymity. Analysis shows that LPPS-CRT is more secure in protecting location privacy, including region information, and is more efficient, than similar schemes. It is suitable for dynamic environments for different users＇ privacy protection requests.展开更多
基金supported by the National Natural Science Foundation of China under Grant No. 61103233
文摘This paper proposes a new proactive weighted threshold signature scheme based on Iflene＇s general secret sharing, the generalized Chinese remainder theorem, and the RSA threshold signature, which is itself based on the Chinese reminder theorem. In our scheme, group members are divided into different subgroups, and a positive weight is associated to each subgroup, where all members of the same subgroup have the same weight. The group signature can be generated if and only if the sum of the weights of members involved is greater than or equal to a fixed threshold value. Meanwhile, the private key of the group members and the public key of the group can be updated periodically by performing a simple operation aimed at refreshing the group signature message. This periodical refreshed individual signature message can enhance the security of the proposed weighted threshold signature scheme.
基金supported in part by the National Natural Science Foundation of China (Nos.61272492 and 61572521)the Shaanxi Province Natural Science Foundation of China (No.2015JM6353)the Basic Foundation of Engineering University of CAPF (No.WJY201521)
文摘Traditional k-anonymity schemes cannot protect a user＇s privacy perfectly in big data and mobile network environments. In fact, existing k-anonymity schemes only protect location in datasets with small granularity. But in larger granularity datasets, a user＇s geographical region-location is always exposed in realizations of k-anonymity because of interaction with neighboring nodes. And if a user could not find enough adjacent access points, most existing schemes would be invalid. How to protect location information has become an important issue. But it has not attracted much attention. To solve this problem, two location-privacy protection models are proposed. Then a new generalized k-anonymity Location Privacy Protection Scheme based on the Chinese Remainder Theorem （LPSS-CRT） in Location-Based Services （LBSs） is proposed. We prove that it can guarantee that users can access LBSs without leaking their region-location information, which means the scheme can achieve perfect anonymity. Analysis shows that LPPS-CRT is more secure in protecting location privacy, including region information, and is more efficient, than similar schemes. It is suitable for dynamic environments for different users＇ privacy protection requests.
