Outsourced Mutual Private Set Intersection Protocol for Edge-Assisted IoT

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.

Data Security Analysis Against Chosen Ciphertext Secure Public Key Attack Using Threshold Encryption Scheme

A public key encryption cryptography system can be utilized to generate ciphertext of a message using a public key. However, this public key encryption cryptography system cannot be utilized if you want to generate ciphertext using several different keys. Solving the problems above can use the Chosen Ciphertext Secure Public Key Threshold Encryption scheme but are the securities from Threshold Encryption really strong in securing messages, therefore the above problems can be analyzed for Data Security Against Chosen Ciphertext Secure Public Key Attacks Using Threshold Encryption Schemes. The work process starts from Setup which functions to generate the server's private key and public key. Then, the process is continued with ShareKeyGen which functions to generate private keys based on the user's identity. After that, the process continues with ShareVerify which serves to verify the key generated from the ShareKeyGen process. The process will be continued again with Combine which serves to generate a private key that will be used in the decryption process. After that, the process will continue with the encryption process of the secret message. The ciphertext obtained will be sent to the recipient. The receiver verifies the ciphertext by running ValidateCT. Finally, the ciphertext is decrypted by running Decrypt. The software created can be used to display the workflow process of the Threshold schema. In addition, it makes it easier to test intercepts of ciphertext messages to other users so that generic securities analysis is carried out in testing the resulting ciphertext. The results of the implementation of Threshold Encryption algorithm scheme can protect important personal data, because it involves human rights, namely the right to access, the right to delete, the right to correct, the right to be corrected and the right to transfer personal data safely from attacks.

Secure Sum Computation using Threshold Encryption for Semi-Ideal Model

The need of preserving privacy of data arises when multiple parties work together on some common task. In this scenario each of the parties has to provide its sensitive data for a common function evaluation. But, the parties may be worried about the misuse of the data. Here comes the subject of Secure Multiparty Computation (SMC). The area where multiple cooperating parties jointly evaluate a common function of their data while preserving the privacy and getting the correct result is SMC. Here, we devise a new model and algorithm to compute sum of private data of mutually distrustful cooperating parties. We coin the term Semi-Ideal Model as it is hybrid of Ideal model and real model. The computation is secure on insecure network as well. Keyword