The Industrial Internet of Things (IIoT) achieves the automation, monitoring, and optimization of industrial processes by interconnecting various sensors, smart devices, and the Internet, which dramatically increases productivity and product quality. Nevertheless, the IIoT comprises a substantial amount of sensitive data, which requires encryption to ensure data privacy and security. Recently, Sun et al. proposed a certificateless searchable encryption scheme for IIoT to enable the retrieval of ciphertext data while protecting data privacy. However, we found that their scheme not only fails to satisfy trapdoor indistinguishability but also lacks defense against keyword guessing attacks. In addition, some schemes use deterministic algorithms in the encryption process, resulting in the same ciphertexts after encryption for the same keyword, thereby leaking the potential frequency distribution of the keyword in the ciphertext space, thereby leaking the potential frequency distribution of the keyword in the ciphertext space, allowing attackers to infer the plaintext information corresponding to the ciphertext through statistical analysis. To better protect data privacy, we propose an improved certificateless searchable encryption scheme with a designated server. With security analysis, we prove that our scheme provides multi-ciphertext indistinguishability and multi-trapdoor indistinguishability security under the random oracle. Experimental results show that the proposed scheme has good overall performance in terms of computational overhead, communication overhead, and security features.

Wireless body area network (WBAN) integrates body sensors to collect and upload various health indicators, which facilitates timely remote healthcare. To realize the real-time monitoring of the patient’s health status while ensuring the security of sensitive data, signcryption schemes with equality test provide a feasible solution. Nevertheless, most of the existing schemes suffer from heavy computational burdens and are vulnerable to some inherent threats, such as offline message recovery attack and known session temporary key attack. Additionally, some of them cannot provide the essential security properties. To cope with these problems, this paper constructs a secure and lightweight signcryption scheme with group equality test, which is suitable for the heterogeneous environment. To formally define the resistance to offline message recovery attack and known session temporary key attack, we first propose two corresponding security models. Then, we introduce a group mechanism to the equality test to support the aforementioned security properties. Besides, we adopt the online/offline construction to avert the time-consuming operations in the real-time data processing phase. Furthermore, our scheme supports message aggregation to reduce the computational overhead of handling multiple messages. Formal security proof shows that our scheme satisfies confidentiality and unforgeability. Compared to several recent schemes, the experimental results demonstrate that our scheme enjoys the best performance in terms of both computational overhead and communication cost. With implementation, our scheme is proved to be feasible for lightweight devices in real-world applications.

In the above paper, Wei et al. proposed a lightweight conditional privacy-preserving authentication protocol in VANET to achieve both ultra-low transmission delay and SSK updating. To decrease communication overhead, their scheme adopts a signature scheme with message recovery to achieve message authentication. And they claimed that the adopted signature was secure against adaptively chosen message attacks, and gave the detailed security proof. Unfortunately, in this work, by analyzing the security of Wei et al. scheme, we show that their scheme is insecure, and it is universally forgeable, i.e., anyone can forge a valid signature on any message; it also makes their scheme does not satisfy conditional privacy. Finally, after analyzing the reasons to produce the attack, we give the corresponding suggestion to overcome the attacks.

As a people-centric sensing paradigm, crowdsourcing has attracted considerable attention since it can solve a complicated task by gathering the wisdom of a crowd of workers. To increase the efficiency of task allocating and recruit suitable workers, the crowdsourcing server needs to obtain information related to task content and worker profiles, which poses a threat to privacy leaks of both tasks and workers. Although several privacy-preserving crowdsourcing mechanisms with simultaneously achieving task privacy and worker privacy have been proposed, there are two problems for these schemes, either the ability of workers is not taken into account or they are computationally intensive. To address the above problems simultaneously, fog-assisted privacy-preserving task allocation in crowdsourcing is proposed by means of the advantages of fog computing, which can not only achieve privacy protection of both the task and the worker but also alleviate the workers' computational burden by offloading partial computation to the fog node. By applying threshold secret sharing technology, the proposed scheme enables that only workers satisfying task requirements can decrypt the task content, which achieves the verification of the workers' ability and resists the attacks of the greedy workers. Then, rigorous security proofs about privacy properties are given in the proposed scheme. Finally, the proposed scheme is estimated through theoretical analysis and experiments. The experimental results show that compared with the current state-of-the-art scheme, the proposed scheme has more advantages in terms of computational cost and storage overhead. Especially for a worker, it only requires one pairing and two multiplication operations in the decrypting phase.

Network virtualization is widely considered to be one of the main paradigms to solve the Internet ossification problem. One of the most challenging works in this paradigm will be the efficient use of the substrate resources, which is known as virtual network embedding (VNE) problem. The VNE problem is known to be an NP-hard problem which needs some heuristic and approximate algorithms to be solved. In this paper, the VNE is decomposed into two stages: virtual node and virtual link mapping. In the node mapping stage, the breadth first search algorithm is employed to construct loop-free tree for each substrate node, then we explored different hops sufficient capacity of each SN node via the loop-free tree, and analyze the best value of hops that contributes to gain better performance for the algorithm. And the link mapping stage, it can be seen as multi-constraint routing, which is known to be an NP-hard problem. The paths algebra framework was adopted to address this problem, for its convergence for multi-constraint routing problem and a large solution space that the algorithm can gain an enhanced optimization performance.