Cloud storage provides tremendous storage resources for both individual and enterprise users. In a cloud storage system, the data owned by a user are no longer possessed locally. Hence, it is not competent to ensure the integrity of the outsourced data using traditional data integrity checking methods. A privacy-preserving public auditing protocol allows a third party auditor to check the integrity of the outsourced data on behalf of the users without violating the privacy of the data. However, existing privacy-preserving public auditing protocols assume that the end devices of users are powerful enough to compute all costly operations in real time when the data to be outsourced are given. In fact, the end devices may also be those with low computation capabilities. In this paper, we propose two lightweight privacy-preserving public auditing protocols. Our protocols are based on online/offline signatures, by which an end device only needs to perform lightweight computations when a file to be outsourced is available. Besides, our proposals support batch auditing and data dynamics. Experiments show that our protocols are hundreds of times more efficient than a recent proposal regarding to the computational overhead on user side.

While cloud computing is relatively mature and its potential benefits well understood by individual, industry and government consumers, a number of security and privacy concerns remain. Unsurprisingly, designing cryptographic solutions to ensure the security of cloud services and the privacy of data outsourced to the cloud remains an ongoing research area. This paper provides a critique of the wide range of cryptographic schemes designed for securing sensitive data in the cloud computing environment, as well as outlining the research opportunities in the use of cryptographic techniques in cloud computing.

Fog computing is an extension of cloud computing and enables computing directly at the edge of the network. In fog computing paradigm, the fog nodes reside between smart end devices and the cloud. Benefiting from the structure of fog computing, fog computing can provide services with low latency, location awareness, and mobility. Since the fog nodes are not as powerful as the cloud, resource allocation techniques are usually adapted to optimize the utilization of the resources of fog nodes. However, the current resource allocation techniques are not privacy-preserving, i.e., an attacker can easily find end devices' sensitive information. In this paper, we propose a privacy-preserving resource allocation scheme for fog computing. The new proposal has constant message expansion, and it is secure against both an eavesdropper and a smart gateway that is employed to perform the resource allocation algorithm. Our scheme is also robust, since it achieves a full key compromise resistance which guarantees that even if the private keys of all the fog nodes in a fog system are corrupted the scheme remains secure.

The Internet of Vehicles (IoV) was proposed as an approach to enable intelligent traffic management and enhance road safety. In order to achieve the intended objective of improving road safety, vehicles are required to constantly broadcast messages to the traffic management infrastructure as well as to other vehicles in the vicinity. Cybersecurity protection of the IoV system is critical as security attacks on IoV and safety-related messages could be life threatening. In this connection, it is essential to ensure the authenticity of IoV messages. Whereas, from the angle of privacy protection, it is undesirable to directly authenticate the identities of vehicles that send the IoV messages. To cope with these conflicting requirements, researchers proposed the notion of conditional anonymous authentication, which aims to authenticate message senders anonymously. When necessary, a trusted third party, named tracer, will be allowed to reveal the true identities of malicious vehicles who sent fake messages. However, existing security techniques, including pseudonyms and group signatures typically assume that the tracer is trusted. This assumption may not be desirable in situations when a curious tracer may reveal the identities of honest vehicles in the IoV system. To address this challenge, this article proposes a privacy-preserving authentication scheme with abuse-resistant tracing. Compared with existing conditional anonymous authentication schemes, our scheme prevents a single tracer from revealing the identity of vehicles. Besides, the tracing key is generated in a distributed manner, and hence no single authority in the system can reveal the true identity of a vehicle.