Mobile edge computing (MEC) has been consideredas a promising technology to provide seamless integration ofmultiple application services. Federated learning (FL) is carriedout at edge clients in MEC for privacy-preserving training ofdata processing models. Despite that the edge clients with smalldata payloads consume less energy on FL training, the small datapayload gives rise to a low learning accuracy due to insufficientinput to the FL training. Inadequate selection of the edge clientscan result in a large energy consumption at the edge clients,or a low learning accuracy of the FL training. In this paper,a new FL-based client selection optimization is proposed tobalance the trade-off between energy consumption of the edgeclients and the learning accuracy of FL. We first show thatthis optimization problem is NP-complete. Next, we proposea FL-based energy-accuracy balancing heuristic algorithm toapproximate the optimal client selection in polynomial time. Thenumerical results show the advantage of our proposed algorithm.

Thanks to flexible deployment and excellent maneuverability, autonomous drones have been recently considered as an effective means to act as aerial data relays for wireless ground devices with limited or no cellular infrastructure, e.g., smart farming in a remote area. Due to the broadcast nature of wireless channels, data communications between the drones and the ground devices are vulnerable to eavesdropping attacks. This article develops BloothAir, which is a secure multi-hop aerial relay system based on Bluetooth Low Energy ( BLE ) connected autonomous drones. For encrypting the BLE communications in BloothAir, a channel-based secret key generation is proposed, where received signal strength at the drones and the ground devices is quantized to generate the secret keys. Moreover, a dynamic programming-based channel quantization scheme is studied to minimize the secret key bit mismatch rate of the drones and the ground devices by recursively adjusting the quantization intervals. To validate the design of BloothAir, we build a multi-hop aerial relay testbed by using the MX400 drone platform and the Gust radio transceiver, which is a new lightweight onboard BLE communicator specially developed for the drone. Extensive real-world experiments demonstrate that the BloothAir system achieves a significantly lower secret key bit mismatch rate than the key generation benchmarks, which use the static quantization intervals. In addition, the high randomness of the generated secret keys is verified by the standard NIST test, thereby effectively protecting the BLE communications in BloothAir from the eavesdropping attacks.

With the continuous development of multimedia, more and more digital works such as videos are spread, stored, and used in the network. In recent years, digital copyright infringement disputes have occurred frequently. The traditional copyright protection system has some problems, such as difficulty confirming copyright, monitoring infringement, and obtaining evidence for rights protection. To this end, we have designed and implemented a novel video copyright protection scheme based on the blockchain and double watermarking technology. We use the image correlation coefficient method to extract video keyframes. And we combine with Contourlet Transform domain, QR decomposition, and SIFT algorithm to improve the robustness of watermark against geometric attacks on the premise of invisibility. After that, we use Arnold Transformation (Cat Map) based on the Maximum Entropy Threshold Segmentation to encrypt the robust watermark and strengthen the security. Moreover, based on the characteristics of the fragile watermarking, we accurately locate the attacked video’s tamper position and complete the integrity authentication of the watermarked video. In addition, the hash digest of the video watermark and the user ID of the copyright owner is signed by SM2 and uploaded to the blockchain. The user can register the copyright after passing the identity authentication. We conduct tests and security analysis on the blockchain performance of the system, the performance of the commercial cryptography algorithm, and the security of the watermarking system. The experimental results show that the blockchain used in this system conforms to the industry standard, the performance of SM2 and SM3 is better than ECC-256 and SHA-256, and the system security is well guaranteed.

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