The privacy of users must be considered as the utmost priority in distributed networks. To protect the identities of users, attribute-based encryption (ABE) was presented by Sahai et al. ABE has been widely used in many scenarios, particularly in cloud computing. In this paper, public key encryption with equality test is concatenated with key-policy ABE (KP-ABE) to present KP-ABE with equality test (KP-ABEwET). The proposed scheme not only offers fine-grained authorization of ciphertexts but also protects the identities of users. In contrast to ABE with keyword search, KP-ABEwET can test whether the ciphertexts encrypted by different public keys contain the same information. Moreover, the authorization process of the presented scheme is more flexible than that of Ma et al.'s scheme. Furthermore, the proposed scheme achieves one-way against chosen-ciphertext attack based on the bilinear Diffie-Hellman (BDH) assumption. In addition, a new computational problem called the twin-decision BDH problem (tDBDH) is proposed in this paper. tDBDH is proved to be as hard as the decisional BDH problem. Finally, for the first time, the security model of authorization is provided, and the security of authorization based on the tDBDH assumption is proven in the random oracle model.

In the Internet of Things (IoT), cyber physical system (CPS) has achieved a sgreat success in a wide range of distributed integration environments. In the cyber physical system (CPS), interconnected sensing devices collect data in the surrounding environment and send data to all interested nodes through the network, thereby sharing all node data. This process can be implemented by using a publish/subscribe (pub/sub for short) system. Providing the basic security mechanisms such as authorization and confidentiality is a challenge due to the loose coupling of subscribers and publishers in such pub/sub system. At the meanwhile, the existing IoT ecosystem mostly relies on a centralized server and thus faces the problem of single point failure. Thus it is interesting to realize a brokerless or decentralized pub/sub model. Inspired by this motivation, this paper mainly proposes a privacy-preserving publish/subscribe model by using the blockchain technique, which evades the centralized trustroot setting and the problem of single point failure. Another key point of our proposal is that the primitive of public key encryption with equality test (PKEwET) is employed to enable all the required authorization, communication and topics matching can be finished in a confidential manner. Finally, a lightweight prototype of our proposal is implemented by using web3j, and the security and efficiency analysis are also presented.

As a popular transportation mode in urban regions, taxis play an essential role in providing comfortable and convenient services for travelers. For the sake of tackling the imbalance between supply and demand, taxi demand forecasting can help drivers plan their routes and reduce waiting time and oil pollution. This paper proposes a deep learning-based model for taxi demand forecasting with multi-source data using Generative Adversarial Networks. Firstly, main features were extracted from multi-source data, including GPS taxi data, road network data, weather data, and points of interest. Secondly, Generative Adversarial Network, comprised of the recurrent network model and the conventional network model, is adopted for fine-grained taxi demand forecasting. A comprehensive experiment is conducted based on a real-world dataset of the city of Wuhan, China. The experimental results showed that our model outperforms state-of-the-art prediction methods and validates the usefulness of our model. This paper provides insights into the temporal, spatial, and external factors in taxi demand-supply equilibrium based on the results. The findings can help policymakers alter the taxi supply and the taxi lease rents for periods and increase taxi profit.

The public key encryption with equality test (PKEET) allows the cloud server to judge whether two different ciphertexts are generated by the same message without decryption. Through this technique, PKEET provides an effective solution for building secure outsourced databases, and has made some rich achievements. This paper combines multivariate public key encryption and equality test, and proposes the first multivariate public key encryption scheme with equality test (MPKEET), which inherits the advantages of both primitives. Moreover, the equality test algorithm proposed in this paper is based on a straight line. Compared with the schemes based on bilinear pairing, it is simpler and easier to implement. And our MPKEET scheme achieves desirable security, which can resist linearization equation attacks, differential attacks, XL attacks, Gröbner basis attacks and the attack of quantum computer, when appropriate parameters are selected.

The modular exponentiation has been proved better in terms of computational efficiency as compared to bilinear pairing. Therefore, discrete logarithm, a concept of modular exponentiation may be incorporated to present improved security schemes. With this aim, an efficient public key encryption scheme with equality test (PKEwET) is proposed in this paper. Unlike the most of existing bilinear pairing based PKEwET schemes, the presented scheme employs discrete logarithm to improve the computational efficiency. Moreover, we introduce the verification process during the test phase to validate the ciphertext and to improve the security comparative to the prevalent schemes. The performance analysis depicts that the proposed scheme is quite efficient and more practical than the existing PKEwET schemes. More precisely, compared to Lin et al. ’s scheme, the time cost has been reduced by at least 39% for the decryption process. Furthermore, for the type-3 test phase, the time cost has been reduced by at least 68%.

The proliferation of big data has brought exponential amount of increase in data that is being remotely stored around the globe. Thus, making it imperative to secure the remote data through some encryption mechanism to ensure privacy preservation. However, it often becomes difficult to perform operations over the encrypted data. In order to solve this problem, the equality test function based public key encryption (PKEwET) is proposed. PKEwET approach basically allows secure comparison over encrypted data without revealing the underlying data. This work aims to improve Water’s scheme while introducing a new functionality. More precisly, equality test is being introduced to Water’s scheme so that the encrypted data may be compared without decryption process. To achieve this, an authorization mechanism is being included in which the authorized party uses the trapdoor to test the ciphertext. The scheme is designed under standard model. The security of the proposed scheme is proved with two types of adversaries under the standard model. Finally, the superiority of the proposed scheme in terms of performance is also discussed.