Many regions are in urgent need of facial masks for slowing down the spread of COVID-19. To fight the pandemic, people are contributing masks through donation systems. Most existing systems are built on a centralized architecture which is prone to the single point of failure and lack of transparency. Blockchain-based solutions neglect fundamental privacy concerns (<italic>donation privacy</italic>) and security attacks (<italic>collusion attack, stealing attack</italic>). Moreover, current auditing solutions are not designed to achieve donation privacy, thus not appropriate in our context. In this work, we design a decentralized, anonymous, and secure auditing framework <italic>Astraea</italic> based on private smart contracts for donation systems. Specifically, we integrate a Distribute Smart Contract (DiSC) with an SGX Enclave to distribute donations, prove the integrity of donation number (intention) and donation sum while preserving donation privacy. With DiSC, we design a Donation Smart Contract to refund deposits and defend against the stealing attack the collusion attack from malicious collector and transponder. We formally define and prove the privacy and security of Astraea by using security reduction. We build a prototype of Astraea to conduct extensive performance analysis. Experimental results demonstrate that Astraea is practically efficient in terms of both computation and communication.

The protection of multicast transmission with optimized secrecy in millimeter-wave (mmWave) communication is still an open problem. In this paper, we propose a low sidelobe secret multicast transmission scheme in mmWave communication based on physical layer security techniques. By utilizing oblique projection, we jointly adopt the directional modulation (DM) and the artificial noise (AN) to achieve secret multicast transmission at low computational costs, without jeopardizing the low sidelobe transmitting pattern. Specifically, considering the constraint of multibeam with the channel knowledge of all target users, a primary transmitting weight vector of the base station (BS) is designed to achieve a low sidelobe transmitting pattern. Then, in each symbol period, the transmitting weight vector of the BS is updated by performing a linear transformation on the primary weight vector with a transformation matrix, which is obtained from the oblique projection matrices of all the target users' channel vectors. In this way, without deteriorating the primary weight vector's low sidelobe transmitting pattern, the obtained transmitting weight vector synthesizes the expected symbols at the target users and adds randomness to the eavesdroppers at undesired directions. Finally, the simulations demonstrate that our proposed scheme achieves outstanding communication performance for the target users at low computational costs, while keeping the high symbol error rates at the undesired directions.