Mobile edge computing (MEC) solves the high latency problem of cloud computing by offloading tasks to edge servers. Due to limited resources, it is necessary to improve the efficiency of computation offloading. However, there is a lot of redundant data transmission between MEC servers and users in the existing methods. Additional data transmission increases the task processing delay. To reduce the total delay, a new cache-assisted computation offloading strategy is proposed. In response to a large number of similar requests from users, a new cache management mechanism is designed. This mechanism can select reusable calculation results more accurately in the cache space through an approximate matching method and improve the cache hit ratio. Then, aiming at the problem of offloading efficiency, the delay optimization problem is transformed into an optimal path problem, a cost function is defined to determine the optimal offloading position, and an improved path planning method is used to plan the optimal offloading path. The simulation results indicate that the proposed scheme can improve the cache hit ratio and reduce the total processing delay of tasks compared with other standard schemes.

Because of a large number of vehicles in Internet of Vehicle(IoV), distributed nodes and complex driving environment, data security and certification speed are easily affected. Blockchain enables different devices that do not trust each other to work together, maintain the general state in the process of information dissemination and sharing, and protect the privacy of devices. However, at present, the speed of vehicle certification in IoV is slow, and the use of idle resources is not considered. To address this problem, this paper provides a blockchain-based vehicle identity verification scheme by using a hybrid identity code verification method to ensure the nodes in the network securely share information. Meanwhile, a task processing algorithm based on time window is proposed to optimize the utilization of idle resources. In addition, the method is evaluated by simulation experiment, and the designed scheme can reduce malicious behavior of a registered vehicle in the network, and can shorten the processing task delay.

In smart grid systems, electric utilities require real-time access to customer electricity data; however, these data might reveal users’ private information, presenting opportunities for edge computing to encrypt the information while also posing new challenges. In this paper, we propose an Edge-assisted Lightweight Power Data Aggregation Encryption (E-LPDAE) scheme for secure communication in a smart grid. First, in the edge privacy aggregation model, the data of smart meters are rationally divided and stored in a distributed manner using simulated annealing region division, and the edge servers of trusted organizations perform key one-time settings. The model encrypts the data using Paillier homomorphic encryption. It then runs a virtual name-based verification algorithm to achieve identity anonymization and verifiability of the encrypted data. The experimental results indicate that the E-LPDAE scheme reduces overall system power consumption and has significantly lower computation and communication overhead than existing aggregation schemes.

Online crowdfunding, an innovative model based on “[Formula: see text]”, is a hot spot for financing via Internet. Crowdfunding based on blockchain is an emerging economic phenomenon and becomes one of the most advanced risk financing strategies. However, crowdfunding transactions face security threats due to identity leaks, quantum attacks and the untraceable nature of blind signatures, which facilitate criminal activity. Different from the previous works, which ignored the importance of traceability, in this paper, we establish a blockchain-empowered secure crowdfunding architecture and propose an anti-quantum partially blind signature algorithm based on the verifiable identity of both sides. Specially, for one thing, the private key decided by user identity is generated by lattice-based sample matrix, and the privacy of user identity can be ensured and traced by the rejection sampling theorem. For another thing, we design an improved krill herd algorithm (IKHA) to increase the credit factor of fundraisers for dealing with project investment issues. The simulation evaluates the correctness and effectiveness of our theoretical analyses. Compared with the current popular schemes, the proposed IKH algorithm has a higher convergence speed and can optimize investment efficiency.