Biblio

In healthcare 4.0 ecosystems, authentication of healthcare information allows health stakeholders to be assured that data is originated from correct source. Recently, biometric based authentication is a preferred choice, but as the templates are stored on central servers, there are high chances of copying and generating fake biometrics. An adversary can forge the biometric pattern, and gain access to critical health systems. Thus, to address the limitation, the paper proposes a scheme, PHBio, where an encryption-based biometric system is designed prior before storing the template to the server. Once a user provides his biometrics, the authentication process does not decrypt the data, rather uses a homomorphic-enabled Paillier cryptosystem. The scheme presents the encryption and the comparison part which is based on euclidean distance (EUD) strategy between the user input and the stored template on the server. We consider the minimum distance, and compare the same with a predefined threshold distance value to confirm a biometric match, and authenticate the user. The scheme is compared against parameters like accuracy, false rejection rates (FARs), and execution time. The proposed results indicate the validity of the scheme in real-time health setups.

Data security and privacy have become an important problem while big data systems are growing dramatically fast in various application fields. Paillier additive homomorphic cryptosystem is widely used in information security fields such as big data security, communication security, cloud computing security, and artificial intelligence security. However, how to improve its computational performance is one of the most critical problems in practice. In this paper, we propose two modifications to improve the performance of the Paillier cryptosystem. Firstly, we introduce a key generation method to generate the private key with low Hamming weight, and this can be used to accelerate the decryption computation of the Paillier cryptosystem. Secondly, we propose an acceleration method based on Hensel lifting in the Paillier cryptosystem. This method can obtain a faster and improved decryption process by showing the mathematical analysis of the decryption algorithm.

With the shift in storage paradigm, there is an increasing need for privacy of dataset and also for an encryption scheme that permits computation on encrypted data. Paillier cryptosystem is a good example of such a homomorphic encryption scheme. To improve the efficiency of the Paillier homomorphic encryption scheme in terms of its decryption speed and overall computational cost, we propose an improved decryption process. Specifically, the inclusion of a variable k to reduce the modular multiplicative arithmetic. The variable k is combined with the L function and CRT recombination method, to arrive at a fast and improved decryption process, showing the mathematical correctness of the decryption algorithm. Experimental results validate that our scheme is significantly efficient in its decryption speed.

In this paper, we introduce a secure energy trading auction approach to schedule the power plant limited resources during peak hours time slots. In the proposed auction model, the power plant serving a power grid shares with the smart meters its available amount of resources that is expected during the next future peak time slot; smart meters expecting a demand for additional power participate in the power auction by submitting bids of their offered price for their requested amount of power. In order to secure the power auction and protect smart meters' privacy, homomorphic encryption through Paillier cryptosystem is used to secure the bidding values and ensure avoiding possible insincere behaviors of smart meters or the grid operator (i.e. the auctioneer) to manipulate the auction for their own benefits. In addition, we use a payment rule that maximizes the power plant's revenue. We propose an efficient power scheduling mechanism to distribute the operator's limited resources among smart meters participating in the power auction. Finally, we present simulation results for the performance of our secure power scheduling auction mechanism.

This article presents PrOLoc, a localization system that combines partially homomorphic encryption with a new way of structuring the localization problem to enable emcient and accurate computation of a target's location while preserving the privacy of the observers.

Centralized spectrum management is one of the key dynamic spectrum access (DSA) mechanisms proposed to govern the spectrum sharing between government incumbent users (IUs) and commercial secondary users (SUs). In the current centralized DSA designs, the operation data of both government IUs and commercial SUs needs to be shared with a central server. However, the operation data of government IUs is often classified information and the SU operation data may also be commercial secret. The current system design dissatisfies the privacy requirement of both IUs and SUs since the central server is not necessarily trust-worthy for holding such sensitive operation data. To address the privacy issue, this paper presents a privacy-preserving centralized DSA system (P2-SAS), which realizes the complex spectrum allocation process of DSA through efficient secure multi-party computation. In P2-SAS, none of the IU or SU operation data would be exposed to any snooping party, including the central server itself. We formally prove the correctness and privacy-preserving property of P2-SAS and evaluate its scalability and practicality using experiments based on real-world data. Experiment results show that P2-SAS can respond an SU's spectrum request in 6.96 seconds with communication overhead of less than 4 MB.