Fog-assisted mobile crowdsensing (FA-MCS) alleviates challenges with respect to computation, communication, and storage from the traditional model of mobile crowdsensing (MCS) “requester-server-users.” Data aggregation, as a specific MCS task, has attracted a lot of attentions in mining the potential value of the massive crowdsensing data. However, the process of data aggregation in FA-MCS may threaten the privacies of both users' data and aggregation results. The untrusted server and fog nodes (FNs) may damage the correctness of aggregation results. Moreover, bad FNs, which do not upload data to server or fail to verify successfully, can endanger the reliability of FA-MCS and the accuracy of aggregation results. To tackle these problems, we propose a verifiable, reliable, and privacy-preserving data aggregation scheme for FA-MCS. Specifically, the proposed scheme preserves privacies of both users' data and aggregation results, enables requester to verify the correctness of aggregation result, and is able to tolerate several bad FNs without affecting the data aggregation result. Through formal security analysis, the proposed scheme is shown to be secure and privacy preserving. Extensive experiments also show the proposed scheme is efficient and reliable.

The widespread adoption of cloud computing and the exponential growth of data highlight the need for secure data sharing and querying. Attribute-based keyword search (ABKS) has emerged as an efficient means of searching encrypted data stored in the cloud. However, existing ABKS schemes incur high end-to-end delay and are vulnerable to quantum computer attacks and/or (insider) keyword guessing attacks (KGA). To address these vulnerabilities, this paper introduces a new concept called attribute-based authenticated encryption with keyword search (ABAEKS) and proposes an efficient ABAEKS scheme. Our ABAEKS has low end-to-end delay, and is resistant to both quantum computer attacks and (insider) KGA. In addition, we formalize the security model of ABAEKS system and prove its security in the random oracle model. Finally, we conduct a comprehensive performance evaluation of ABAEKS, and the experimental results show that our ABAEKS is computationally efficient and outperforms current state-of-the-art ABKS schemes.

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 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 paper proposes a Blockchain-assisted authentication and key agreement scheme for UAVs networks 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 authentication and key agreement. Based on the network model, both types of authentication and key agreement mechanisms, UAV-2-GCS and UAV-2-UAV, are proposed, respectively. In particular, the ground control station (GCS) does not participate in the authentication and key agreement 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 authentication and key agreement 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.

Communication efficient secret sharing (CESS) schemes are a class of threshold schemes that aim to minimize the so-called decoding bandwidth, namely the necessary amount of communication between a combiner who wants to reconstruct the secret and the available participants storing shares of the secret. Previous works proved that the decoding bandwidth had a tight lower bound related to the number of available participants. Some threshold schemes that achieved the lower bound (optimal decoding bandwidth) and optimal information rate were constructed for a given number (non-universal case) or multiple distinct number ( $\triangle $ -universal case) of available participants. However, all those CESS schemes have large share sizes. Moreover, they have a common feature that each secret and share are a vector with multiple coordinates, which results in the decoding delay since the combiner must reconstruct a part of coordinates of the secret at first, and these recovered coordinates will be used to reconstruct another part of coordinates of the secret. In this work, we describe a new construction for CESS schemes of non-universal and $\triangle $ -universal cases, whereas each secret and share of our schemes are a single element of a finite field $\mathbb {F}_{q^{e}}$ , and each participant of an authorized subset provides a single element of a same subfield of $\mathbb {F}_{q^{e}}$ to the combiner to reconstruct the secret. We find that the CESS schemes of this type, termed balanced CESS schemes, have an inevitable restriction on the number of available participants, but our schemes has no decoding delay. Furthermore, our schemes have smaller share sizes than other existing works, which are realized by using a smaller sub-packetization $e$ and a smaller base field $\mathbb {F}_{q}$ . Indeed, the sub-packetizations of our schemes are minimum for given $\mathbb {F}_{q}$ among balanced CESS schemes. In addition, when our constructions are used to generate communication efficient $(n,r)$ threshold schemes, we derive a generalized Shamir’s scheme that universally achieves optimal decoding bandwidth and optimal information rate for the first time , where the restriction on the number of available participants is removed.