Information fusion using evidence theory in wireless sensors networks has been used extensively to identify targets because it offers the advantage of handling uncertainty. But the classical Dempster's combination rule cannot deal with highly conflicting information because it often generates counterintuitive results. In this paper, a new weighted evidence combination approach is proposed to solve this problem. First, two measures, i.e., a new contradiction measure of each body of evidence (BOE) and a probabilistic-based dissimilarity measure between two BOEs, are introduced to estimate the value of weight of each sensor. Then, when combining conflicting information, reasonable results can be produced by using weighted average of BOEs and Dempster's rule. Our experimental results showed that the proposed method has better performance in convergence than the existing methods.

With the advent of large-scale social networks, two communication users need to generate session keys with the help of a remote server to communicate securely. In the existing three-party authenticated key exchange (3PAKE) protocols, users’ passwords need to be stored on the server; it cannot resist the server disclosure attack. To solve this security problem, we propose a more efficient 3PAKE protocol based on the verification element by adopting a public-key cryptosystem and approximate smooth projection hash (ASPH) function on an ideal lattice. Using the structure of separating authentication from the server, the user can negotiate the session key only after two rounds of communication. The analysis results show that it can improve the efficiency of computation and communication and resist the server disclosure attack, quantum algorithm attack, and replay attack; moreover, it has session key privacy to the server. This protocol can meet the performance requirement of the current communication network.

With the emergence and widespread application of cloud computing, the use of cloud platforms to solve the problem of secure multi-party computation has emerged as a new research direction. The traditional computation of a solid geometry is performed through mutual interactions between two parties, which is not suitable in an untrusted cloud computing environment. In this paper, we first design a basic protocol for a secure Euclidean distance calculation that is suitable for cloud platforms and can serve as a building block for other protocols on cloud platforms. Using the solution of the Euclidean distance problem as such a building block, we provide a new method that converts the problems of calculating solid triangular areas and solid tetrahedral volumes into the calculation of distances and determinants in three-dimensional space. Then, we discuss solid point-line distance calculations, which extent the idea of the spatial geometry security problem. We present protocols for the above problems and prove that the proposed protocols can resist conspiracy among users and the untrusted cloud platform so that they can effectively ensure the privacy of the users. We also analyze the performances of these solutions. The analysis results show that our scheme is more versatile.

With the rapid development of edge computing and the Internet of Things, the problem of information resource sharing can be effectively solved through multi-party collaboration, but the risk of data leakage is also increasing. To address the above issues, we propose an efficient multi-party private set intersection (MPSI) protocol via a multi-point oblivious pseudorandom function (OPRF). Then, we apply it to work on a specific commercial application: edge caching. The proposed MPSI uses oblivious transfer (OT) together with a probe-and-XOR of strings (PaXoS) as the main building blocks. It not only provides one-sided malicious security, but also achieves a better balance between communication and computational overhead. From the communication pattern perspective, the client only needs to perform OT with the leader and send a data structure PaXoS to the designated party, making the protocol extremely efficient. Moreover, in the setting of edge caching, many parties hold a set of items containing an identity and its associated value. All parties can identify a set of the most frequently accessed common items without revealing the underlying data.

In secure two-party computation, each party has its input and wants to jointly compute a function from which it obtains the output corresponding to its respective inputs. For achieving security against a malicious adversary, an effective approach is using cut-and-choose, which requires the circuit constructor P₁ to construct S copies of the circuit C (C is used to compute the function F). The circuit evaluator P₂ selects S2 circuits to open for the check. If these S2 circuits are correctly constructed, P₂ assumes that the remaining S2 circuits are also correctly constructed and uses the remaining circuits to compute. However, this method introduces significant computational complexity and interactive rounds, mainly due to more circuits that must be used for security purposes and the need for multiple interactions to transmit the keys. In this paper, regarding the issue above, we present a novel secure two-party computation protocol, and it can achieve security against the malicious adversary. Concretely, we still use the idea of cut-and-choose but improve the cut-and-choose oblivious transfer (CCOT) of the usual secure two-party computation protocol into cut-and-choose bilateral oblivious transfer (CCBOT) and propose a variant of it that we call batch single-choice CCBOT, which makes our protocol only needs two rounds of interaction to complete the transmission of all keys and 28Sl of exponentiations. In addition, we use a check mechanism to prevent the case that p₁ cheats, but P₂ is powerless. Our proposed protocol with an error probability of 2^–s of P₁ significantly optimizes the communication rounds and computation overheads, solves the selective failure attack, and ensures the consistency of the input.

The development of edge computing and Internet of Things technology has brought convenience to our lives, but the sensitive and private data collected are also more vulnerable to attack. Aiming at the data privacy security problem of edge-assisted Internet of Things, an outsourced mutual Private Set Intersection protocol is proposed. The protocol uses the ElGamal threshold encryption algorithm to rerandomize the encrypted elements to ensure all the set elements are calculated in the form of ciphertext. After that, the protocol maps the set elements to the corresponding hash bin under the execution of two hash functions and calculates the intersection in a bin-to-bin manner, reducing the number of comparisons of the set elements. In addition, the introduction of edge servers reduces the computational burden of participating users and achieves the fairness of the protocol. Finally, the IND-CPA security of the protocol is proved, and the performance of the protocol is compared with other relevant schemes. The evaluation results show that this protocol is superior to other related protocols in terms of lower computational overhead.