Energy big data: A survey <s> D. THIRD-PARTY PROTECTION <s> Every function of n inputs can be efficiently computed by a complete network of n processors in such a way that: If no faults occur, no set of size t n /2 of players gets any additional information (other than the function value), Even if Byzantine faults are allowed, no set of size t n /3 can either disrupt the computation or get additional information. Furthermore, the above bounds on t are tight! <s> BIB001 </s> Energy big data: A survey <s> D. THIRD-PARTY PROTECTION <s> Cloud computing allows the use of Internet-based services to support business processes and rental of IT-services on a utility-like basis. It offers a concentration of resources but also poses risks for data privacy. A single breach can cause significant loss. The heterogeneity of “users” represents a danger of multiple, collaborative threats. In cloud computing, entities may have multiple accounts associated with a single or multiple service providers (SPs). Sharing sensitive identity information (that is, Personally Identifiable information or PII) along with associated attributes of the same entity across services can lead to mapping of the identities to the entity, tantamount to privacy loss. Identity management (IDM) is one of the core components in cloud privacy and security and can help alleviate some of the problems associated with cloud computing. Available solutions use trusted third party (TTP) in identifying entities to SPs. The solution providers do not recommend the usage of their solutions on untrusted hosts. We propose an approach for IDM, which is independent of TTP and has the ability to use identity data on untrusted hosts. The approach is based on the use of predicates over encrypted data and multi-party computing for negotiating a use of a cloud service. It uses active bundle—which is a middleware agent that includes PII data, privacy policies, a virtual machine that enforces the policies, and has a set of protection mechanisms to protect itself. An active bundle interacts on behalf of a user to authenticate to cloud services using user’s privacy policies. <s> BIB002
Damages via the communication systems, except safety hazards of the controlled plant itself, can be averted by the protection of a third-party, such as a cloud service provider. The power system can be used for launching various attacks on the smart grid or the third party after being attacked. This will do damage to a smart grid system owner's reputation, or even reach to legal liability for damaging the third party. Since the third party isn't listed in authentication table in power network, it may have no access permission. Trusted Third Party (TTP) has been a promising approach for Personally Identifiable Information (PII) in power system security. Ranchal et al. BIB002 used a predicate encryption scheme and multi-party computing to process identity data on untrusted hosts. Shamir  proposed a threshold secret sharing on private information. First a private data set D is divided into n shares: Then a threshold t is chosen to recover D. This operation may require t or more shares of arbitrary D i . Ben-Or et al. BIB001 defined a multi-party computing protocol which uses secret input from all the parties. This protocol involves n mutual parties which only calculate partial function outputs. In this protocol, one player from a party has been selected as the dealer(DLR) and provided partial outputs to figure out the full computation results. Denote a linear function f of n degree which is known to n parties, an arbitrary threshold t, the i-th party P i , and x i as the input of P i for f . By using a set of input {x 1 , x 2 , · · · , x n }, n parties will calculate the output through f and send the result to the DLR. Each P i generates a polynomial h i of t degree such that h i (0) = x i . When P i sends one share to P j in the left parties, P i will compute the portion of function f using this sent share.