A spatial attentive and temporal dilated(SATD)GCN for skeleton-based action recognition

Current studies have shown that the spatial-temporal graph convolutional network(STGCN)is effective for skeleton-based action recognition.However,for the existing STGCN-based methods,their temporal kernel size is usually fixed over all layers,which makes them cannot fully exploit the temporal dependency between discontinuous frames and different sequence lengths.Besides,most of these methods use average pooling to obtain global graph feature from vertex features,resulting in losing much fine-grained information for action classification.To address these issues,in this work,the authors propose a novel spatial attentive and temporal dilated graph convolutional network(SATD-GCN).It contains two important components,that is,a spatial attention pooling module(SAP)and a temporal dilated graph convolution module(TDGC).Specifically,the SAP module can select the human body joints which are beneficial for action recognition by a self-attention mechanism and alleviates the influence of data redundancy and noise.The TDGC module can effectively extract the temporal features at different time scales,which is useful to improve the temporal perception field and enhance the robustness of the model to different motion speed and sequence length.Importantly,both the SAP module and the TDGC module can be easily integrated into the ST-GCN-based models,and significantly improve their performance.Extensive experiments on two large-scale benchmark datasets,that is,NTU-RGB+D and Kinetics-Skeleton,demonstrate that the authors’method achieves the state-of-the-art performance for skeleton-based action recognition.

Physical Layer Security for UAV Communications:A Comprehensive Survey

Due to its high mobility and flexible deployment,unmanned aerial vehicle(UAV)is drawing unprecedented interest in both military and civil applications to enable agile and ubiquitous connectivity.Mainly operating in an open environment,UAV communications benefit from dominant line-of-sight links;however,this on the other hand renders the communications more vulnerable to malicious attacks.Recently,physical layer security(PLS)has been introduced to UAV systems as an important complement to the conventional cryptography-based approaches.In this paper,a comprehensive survey on the current achievements of UAV-PLS is conducted.We first introduce the basic concepts including typical static/-mobile UAV deployment scenarios,the unique air-toground channel and aerial nodes distribution models,as well as various roles that a UAV may act when PLS is concerned.Then,we start by reviewing the secrecy performance analysis and enhancing techniques for statically deployed UAV systems,and extend the discussion to the more general scenario where the UAVs’mobility is further exploited.For both cases,respectively,we summarize the commonly adopted methodologies,then describe important works in the litera ture in detail.Finally,potential research directions and challenges are discussed to provide an outlook for future works in the area of UAV-PLS.

A trustless architecture of blockchain-enabled metaverse

Metaverse has rekindled human beings’desire to further break space-time barriers by fusing the virtual and real worlds.However,security and privacy threats hinder us from building a utopia.A metaverse em-braces various techniques,while at the same time inheriting their pitfalls and thus exposing large attack surfaces.Blockchain,proposed in 2008,was regarded as a key building block of metaverses.it enables transparent and trusted computing environments using tamper-resistant decentralized ledgers.Currently,blockchain supports Decentralized Finance(DeFi)and Non-fungible Tokens(NFT)for metaverses.How-ever,the power of a blockchain has not been sufficiently exploited.In this article,we propose a novel trustless architecture of blockchain-enabled metaverse,aiming to provide efficient resource integration and allocation by consolidating hardware and software components.To realize our design objectives,we provide an On-Demand Trusted Computing Environment(OTCE)technique based on local trust evalua-tion.Specifically,the architecture adopts a hypergraph to represent a metaverse,in which each hyper-edge links a group of users with certain relationship.Then the trust level of each user group can be evaluated based on graph analytics techniques.Based on the trust value,each group can determine its security plan on demand,free from interference by irrelevant nodes.Besides,OTCEs enable large-scale and flexible application environments(sandboxes)while preserving a strong security guarantee.