Titlebook: Collaborative Computing: Networking, Applications and Worksharing; 18th EAI Internation Honghao Gao,Xinheng Wang,Tasos Dagiuklas Conference

Harpoon

A Visual Tool for?Interactively Privacy Analysis and?Preservation on?Order-Dynamic Tabular Data adjustment. Novel visual designs, i.e., data abstract, risk tree, integrated privacy enhancement, are developed to explore data correlations and acquire privacy awareness. We demonstrate TPA’s effectiveness with a case study on the prototype and qualitatively discuss the pros and cons with domain experts for future improvement.

deviate

dandruff

An Adaptive Ensembled Neural Network-Based Approach to?IoT Device Identificationtures of IoT traffic, which is able to automatically extract the high-level features from raw IoT traffic. The further evaluation indicates that our method is capable of identifying diverse IoT devices with satisfactory accuracy.

Budget

Research on?Depth-Adaptive Dual-Arm Collaborative Grasping Methodd pixel information. Finally, the task is assigned to the left and right robotic arms, and the target grabbing task is realized based on the main-auxiliary control. The proposed approach is validated in multiple experiments on a Baxter robot under different conditions.

CLEFT

https://doi.org/10.1007/b136519ng the privacy information of victims while maintaining the accuracy of the global model. Comprehensive experimental results demonstrated that our method is effective in the prevention of GAN-based privacy inferring attacks.

突變

https://doi.org/10.1007/b136519change servers also provide message storage service in case that the receiver of these messages are offline, in which way, the communication becomes more simple and flexible. The experimental results show that our proposed system guarantees the strong tracking-resistance and high communication effic

憤憤不平

https://doi.org/10.1007/b136519formance hardware devices. And some methods require professional instruments such as oscilloscopes to collect fine-grained RF signals. For these reasons, we propose a lightweight clone detection method Anti-Clone. We combine convolutional neural networks (CNN) with transfer learning to combat data-c

粗糙濫制

https://doi.org/10.1007/b136519attach it on the chain. At the same time, the delay problem is added as a constraint to the trust calculation. Finally, the simulation experiment shows that the mechanism improves security of edge computing.

aquatic

https://doi.org/10.1007/b136519 with three models (SVM, CNN, etc.) and compared it with other popular schemes in the classification accuracy and training time. Our scheme proved to be efficient and practical, which achieved 2% better than the second one in model accuracy, costing merely 4% of its training time with the 0.05 priva

祖?zhèn)髫敭a(chǎn)