The Research Of Privacy-Preserving Aggregation Of User’s Data In Smart Grid

Smart grid can realize the two-way flows of information and electric transmission already has been regarded as the next power grid to replace the current power grid with the feature of reliable、safety、efficient、 flexible、and friendly et al. Smart grid need to aggregate and analyze user’s data continuously to control and schedule the whole grid. However, in this process has the risk of exposing the individuals privacy,if the security problem is not be solved, it will threat to everyone in the grid seriously and bring them series bad consequences and personal losses Therefore, security issues also be an important obstacle to further implement of smart grid. Privacy-preserving aggregation in smart grid has be the key and hot issue in research filed and the papers about privacy data aggregation emerged in endlessly. Our article mainly research the issue about privacy data aggregation in smart grid. Due to the smart grid will aggregate use’s data frequently,the data in transmission、storage、and processing may suffer the problem of privacy disclose. Nonetheless sacrifice the data utility in returns for user’s data privacy also insignificance to smart grid. Hence there need secure and reliable scheme can achieve both utility and safety.Our scheme offer a solution to solve the instability of previous programs and eliminated the restriction about the size of plaintext and the number of users. We ensure individual’s privacy not be disclosed without missing the data utility. Our main contributions are the following two aspects1:In this paper, we wipe off the restrict that not allowing any use’s failure at every data aggregation time on the basis of original scheme, our scheme allow one or more user failure at aggregation time. No longer limited that at each round of data aggregation time all users should participate in effectively. Greatly improve the effectiveness^ reliability and feasibility of the scheme.2:Our scheme not limited the limitation of plaintext scale and the number of users at multidimensional data aggregation compared with the formal scheme, greatly reduce the computational overhead. Meanwhile scheme can work quickly and effectively without restrict of plaintext scale and users number. Furthermore we further enhance the scheme security by differential privacy, in this case even if there is an adversary with strong ability and some extra auxiliary information about user can not obtain users’ personal data.