With the rapid advancement of industrial automation and intelligent manufacturing, an increasing volume of sensing data generated by Industrial Internet of Things (IIoT) devices is being transmitted to cloud platforms. Identity-based broadcast proxy re-encryption (IB-BPRE), as an efficient cryptographic mechanism, has been deployed in IIoT data-sharing environments. However, existing IB-BPRE schemes are susceptible to identity privacy breaches of data recipients. Furthermore, IIoT devices are structurally vulnerable to key escrow compromises resulting from the exposure of encrypted key. To mitigate these critical security challenges, we propose a privacy-preserving certificateless-based broadcast proxy re-encryption scheme for data sharing in cloud-based IIoT, and formally prove its security against chosen ciphertext attacks under the random oracle model. The PCL-BPRE scheme employs a Lagrange interpolation polynomial to obfuscate the identity information of data receivers. Additionally, it integrates certificateless encryption to eliminate the inherent key escrow dependency in IB-BPRE, thereby preventing unauthorized disclosure of private keys in the event of a compromised key generation center. Experimental results validate that the proposed scheme achieves both strong practical feasibility and computational efficiency in IIoT data-sharing.

With the advancing application of Unmanned Aerial Vehicles (UAVs, also known as Drones), UAV swarms are deployed in various complex mission scenarios to collaborate on particular assignments. However, UAV group communication encounters security and privacy challenges due to the open and insecure communication environment. Moreover, many existing UAV group authentication and key agreement (GAKA) schemes provide limited support for dynamic membership and fail to enforce mandatory participation of the leader UAV in hierarchical architectures. To address these limitations, we propose a blockchain-enabled scalable GAKA scheme tailored for dynamic IoD, named BSGAKA-IoD. The scheme achieves UAV threshold GAKA through an enhanced designated participant$ (ID, t, n)^*$-secret sharing scheme, which cryptographically enforces leader participation and enables threshold-based GAKA among the cluster leader and member UAVs. The scheme supports efficient group authentication, secure group key establishment, and dynamic joining/leaving without requiring any secure channel, while achieving$ O(n)$computational and communication complexity. We conduct comprehensive security analysis and develop two blockchain prototypes: a Solidity smart contract implementation validated in Remix, and a Hyperledger Fabric implementation benchmarked using Hyperledger Caliper under two network configurations. The results confirm that BSGAKA-IoD provides strong security guarantees, maintains linear scalability, and is feasible for deployment in realistic consortium-chain IoD settings.

Unmanned aerial vehicles (UAVs, also known as Drones) have been widely employed in military defense and civilian service. However, as UAVs communicate over insecure open wireless channels, the security challenges and privacy concerns are becoming increasingly prominent. Moreover, some existing schemes to achieve authentication and key agreement (AKA) among UAVs are spliced with the assistance of two UAV-2-GCS mechanisms, which are not flexible enough to be applied in the Internet of Drones (IoD) scenarios. This article proposes a blockchain-assisted AKA scheme for UAVs networks (BAKAS-UAV) referred to as BAKAS-UAV, which addresses security and privacy concerns and overcomes high computational and communication costs in the IoD. A blockchain-based network model is presented in which the ground station acts as an edge node and manages the blockchain, which assists AKA. Based on the network model, both types of AKA mechanisms, UAV-2-GCS and UAV-2-UAV, are proposed, respectively. In particular, the ground control station (GCS) does not participate in the AKA of UAV-2-UAV process; only upon the process is completed the two UAVs synchronize the updated information with GCS. We also implement a smart contract as the authentication service, and the experimental implementation demonstrates the availability of our scheme in IoD. Physical unclonable functions (PUFs) is introduced on the UAVs side to defend against physical capture attacks and also to implement AKA mechanisms. The semantic security is proved formally based on the real-or-random (ROR) model, and the informal analysis shows that the scheme satisfies the demanded security requirements. The scheme’s performance is evaluated by simulating the UAVs and GCS settings with Raspberry Pi 4B and MacOS platforms, respectively, with implementation of several cryptographic primitives. The experimental results show that BAKAS-UAV achieves high efficiency.

Smart contracts are programmable units that possess the ability to execute a wide range of computational tasks, operating on a decentralized ledger called a blockchain, frequently employed for the management of valuable digital assets. Unlike conventional programs, once smart contracts are deployed, they are immutable and cannot be altered. As the value associated with smart contracts increases, they become increasingly enticing targets for potential attackers. It is therefore crucial to conduct comprehensive testing of smart contracts prior to their deployment. Fuzzing is an important testing approach. Regrettably, existing coverage-based fuzzing tools treat all covered code in the same manner and cannot perform extensive tests on specific code fragments. In this research, we present LDfuzz, a targeted greybox fuzzer explicitly developed for Ethereum smart contracts. Its primary goal is to generate inputs that efficiently navigate towards potentially suspicious program locations. We propose suspicious branch marked, an innovative approach that assesses branch-level security implications. Utilizing the suggested metrics as a foundation, we calculate the distance of each fuzzing inputs to the marked branch and formulate a power scheduling algorithm based on simulated annealing, which progressively allocates additional energy to seeds in proximity to the suspicious branch while diminishing energy for seeds that are more distant. We assess the efficacy of LDfuzz by conducting a comparative analysis with a leading fuzzer for smart contracts, benchmarking their respective performance. The results from our experimentation findings demonstrate that LDfuzz exhibits superior efficiency compared to current advanced tools in identifying bugs within real-world contracts. Moreover, LDfuzz excels beyond current tools in achieving broader branch coverage.

Remote data backup technology facilitates data storage for users. However, an attacker may intercept some sensitive data on transfer. To solve this problem, sensitive data should be encrypted before uploading to the remote storage. Thus, protecting the secret encryption key is very important. Liu et al . have designed a scheme to protect the secret key using the secret‐sharing method and multi‐factor authentication. Unfortunately, the authors find some security weaknesses of Liu et al .’s scheme. Liu et al .’s scheme cannot resist offline password guessing attack, the server impersonation attack, the user impersonation attack and an attacker updating password/biometrics attack. They present an enhanced secure data backup scheme using multi‐factor authentication to overcome all above‐mentioned security threats. The user first divided a secret used to encrypt sensitive data into three shares using Shamir's secret sharing. Moreover, then the user uses the own password and biometrics to hide the true shares, and stores the pseudo three shares in the smart card, the laptop and the server, separately. Furthermore, the proposed scheme is illustrated in detail, and they give a security comparison of their scheme with Liu et al .’s scheme and computational costs.