The deep integration of Internet of Vehicles (IoV) and edge computing technologies brings new requirements for the Vehicular Edge Computing (VEC) information system security evaluation. Facing the two core problems of resource-constrained scenarios and dynamic security evaluation, the GFCIV-CGTOPSIS model for VEC information system dynamic security evaluation is proposed. In the model, subjective and objective evaluation indexes are considered and calculated separately to improve operability. An improved grey correlation F-statistics clustering and index validity combination index screening (GFCIV) method is proposed in order to improve the operational efficiency of the traditional grey F-statistics rough set (GFRS) index screening method. The CRITIC method is used to determine the subjective and objective comprehensive index set weights, and the grey TOPSIS method is used to realize the dynamic security evaluation. Experimental results demonstrate that the GFCIV-CGTOPSIS model, compared to the pre-improved GFRS-CGTOPSIS model, achieves reduced index tree redundancy and efficient dynamic security evaluation while exhibiting less information loss and lower evaluation result deviation due to index screening.

Blockchain-based distributed storage systems offer enhanced security, transparency, and lower costs compared to traditional centralized storage, making them ideal for peer-to-peer collaboration. However, with the trend towards the Web of Things (WoT), lower transaction speeds and higher computational requirements limit their access to high-density data such as IoT. To address this, we propose TimeChain, an efficient off-chain blockchain storage system for IoT time series data. TimeChain batches discrete time series data, storing only the hash value of each batch on-chain while keeping the complete data off-chain. This significantly reduces storage overhead on the blockchain and storage latency by 37.4 times. TimeChain adopts an adaptive packaging mechanism to reduce the additional latency in range queries by converting the batch processing problem into a graph partitioning problem. To reduce the overhead of node selection, TimeChain integrates a node selection mechanism based on consensus protocol, combining node selection and consensus processes together. TimeChain also proposes a Locality-Sensitive Hashing tree-based data integrity verification mechanism to reduce transmission size. Our evaluation shows a reduction in query latency by 64.6% and storage latency by 35.3% compared to existing systems.

ABSTRACT In password‐based or two‐factor (password and smart card) authentications, password changing is one of common techniques used to improve the security of the systems protected by the password. However, the password‐changing operations in existing password authentications either depend on the login phase or violate the common practice that an old password should not be valid for subsequent login after being updated. On the other hand, password mistyping is very common in reality, which may be random or be skewed by the adversary via technical means or social engineering manipulation [i.e., a kind of denial‐of‐service (DoS) attack]. In human‐centric authentication mechanisms, password changing and DoS resilience are not marginal issues. The paper addresses the requirements of robust password changing in authentication and presents , a password authentication scheme with robust password changing, DoS resilience, and card‐compromise security. Thus, the proposal can be viewed as a suitable candidate instantiation for authentication services of human‐centric security, by embedding in the computer and software systems. also achieves other appealing features, such as self‐healing ability and strong privacy protection, which may be useful for human‐centric applications. Copyright © 2013 John Wiley & Sons, Ltd.