2022 International Conference on Networking and Network Applications (NaNA)最新文献_第3页

A Proposal of ClouEdge (Cloud-Edge) Architecture by Using JYAGUCHI Computing Framework 基于JYAGUCHI计算框架的ClouEdge(云边缘)架构方案

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00064

B. P. Gautam, Amit Batajoo, N. Shiratori

引用次数: 0

Privacy risk estimation of online social networks 在线社交网络的隐私风险评估

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00032

Shitong Fu, Zhiqiang Yao

引用次数: 2

An Attributed Network Anomaly Detection Method Based on Dual Autoencoder Joint Embedding 基于双自编码器联合嵌入的属性网络异常检测方法

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00057

Jing Han, Yizhi Zhang, Kenan Qin

引用次数: 0

A Fair Federated Learning Framework based on Clustering 基于聚类的公平联邦学习框架

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00088

Jiaomei Zhang, Ayong Ye, Zhiqiang Yao, Minghui Sun

引用次数: 0

Paris Subway Pricing-based Link Selection in Air-Space-Ground Networks 基于空-空-地网络定价的巴黎地铁线路选择

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00017

Yuanxin Yan, Yang Xu, L. xilinx Wang, Jianbo Shao, H. He, Shanshan Zhang

引用次数: 0

OKV: Optimized Key-Value Data Collection with Local Differential Privacy OKV:具有本地差分隐私的优化键值数据收集

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00078

Bowen Deng, Lele Zheng, Ze Tong, Jing Gao, Tao Zhang, Qi Li

{"title":"OKV: Optimized Key-Value Data Collection with Local Differential Privacy","authors":"Bowen Deng, Lele Zheng, Ze Tong, Jing Gao, Tao Zhang, Qi Li","doi":"10.1109/NaNA56854.2022.00078","DOIUrl":"https://doi.org/10.1109/NaNA56854.2022.00078","url":null,"abstract":"Local differential privacy (LDP), where each user obfuscates their data locally before sending it to an untrustworthy data collector, provides a strict privacy guarantee for users' sensitive data. However, the existing key-value data collection mechanisms based on the LDP assume that all keys are equally sensitive, which leads to excessive protection and thus loss of utility. To address the reduced utility caused by overprotection, we introduce the notion of key-value data utility-optimized LDP (KV-ULDP), which only offers a basic LDP-equivalent privacy guarantee for sensitive keys and all values. Subsequently, we design a new framework, named optimized key-value data collection (OKV) with LDP, which satisfies the KV-ULDP with high utility while keeping secret for each user. We instantiate the OKV framework by using OKV-UE (based on Unary Encoding) and OKV-GRR (based on Generalized Randomized Response) mechanisms. The OKV-UE is effective with a large number of key types, and OKV-GRR works well under high privacy budgets. The theoretical analysis and the experiments on two real datasets show that our mechanisms outperform the existing key-value mechanisms with LDP in terms of utility.","PeriodicalId":113743,"journal":{"name":"2022 International Conference on Networking and Network Applications (NaNA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121081775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Study of Service Registration and Discovery Techniques in Microservice Architecture 微服务体系结构中的服务注册与发现技术研究

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00053

Xinghui Zhu, Yalong Lv, Jia Liu, Xuewen Dong, Lin Li, Jiandong Wang

{"title":"A Study of Service Registration and Discovery Techniques in Microservice Architecture","authors":"Xinghui Zhu, Yalong Lv, Jia Liu, Xuewen Dong, Lin Li, Jiandong Wang","doi":"10.1109/NaNA56854.2022.00053","DOIUrl":"https://doi.org/10.1109/NaNA56854.2022.00053","url":null,"abstract":"The microservice architecture has become a key technology in the development of the Internet. It brings a revolutionary development to the software production relationship and effectively improves the scalability and stability of the system. However, as the system evolves and the microservice splitting granularity is wrefined, the scale of microservices explodes and problems such as extended service discovery time and high service maintenance costs arise. For these problems, this paper proposes a detection mesh scheme (DM) based on service mesh and service semantics, which is divided into two main parts: service registration and service discovery. In terms of the service registration, based on the idea of a service mesh, the microservice governance and microservice development are deeply decoupled. In terms of the service discovery, the local-remote algorithm is proposed by considering the path, semantics, and state of microservices. In addition, a hierarchical ontology model is builded to provide a solid foundation for service registration and service discovery. Through experimental verification, compared with the web service discovery based on the maximum weighted bipartite graphs scheme(WSDMWBG), the DM scheme improves 12.71% in first hit rate and 28.3% in total microservice call time, effectively reducing the service discovery latency.","PeriodicalId":113743,"journal":{"name":"2022 International Conference on Networking and Network Applications (NaNA)","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122534957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Visualizable Malware Detection based on Multi-dimension Dynamic Behaviors 基于多维动态行为的可视化恶意软件检测

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00049

Zhidong Ma, Zhiwei Zhang, Chengliang Liu, Tianzhu Hu, Hongjun Li, Baoquan Ren

{"title":"Visualizable Malware Detection based on Multi-dimension Dynamic Behaviors","authors":"Zhidong Ma, Zhiwei Zhang, Chengliang Liu, Tianzhu Hu, Hongjun Li, Baoquan Ren","doi":"10.1109/NaNA56854.2022.00049","DOIUrl":"https://doi.org/10.1109/NaNA56854.2022.00049","url":null,"abstract":"For different motives and reasons, malicious software, or malware, has been frequently used to damage and destroy information systems in many various environments. Especially, with the widespread application of the Internet and the reemergence of artificial intelligence, security and privacy are significantly stressed by individuals and businesses, and the influence of malware is being more and more serious in recent years. Unfortunately, the previous traditional malware detection schemes are infeasible in the AI era, as they cannot effectively recognize and identify the unknown or new types of malware, which could be easily and quickly brought out by automatic combination and improvement. Although many AI-based malware detection schemes also have been proposed at the same time, they are suffering from heavy training and low accuracy problems. Therefore, in this paper, we propose a visual malware detection model and concrete scheme based on multi-dimensional dynamic behaviors including all API and network operation information. To train our model, we collected a malware behavior dataset containing over 700 malware-image pairs, where the images are grayscale and converted from the malware execution behaviors recorded in the Cuckoo sandbox. Compared with the existing visual detection schemes, we introduce and employ the malware's dynamic behaviors information to produce the visual images, and we avoid the manual feature extraction in constructing the training dataset. Moreover, our experimental result shows that our scheme can outperform the existing schemes in detection accuracy and efficiency as well as the ability of new malware recognition.","PeriodicalId":113743,"journal":{"name":"2022 International Conference on Networking and Network Applications (NaNA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125747375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Covert Monitoring for D2D-enabled Cellular Networks 支持d2d的蜂窝网络的隐蔽监控

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00016

Wu Wang, Sibo Wang, Kaiguo Qian, Shaojun Yu, Bin Yang

引用次数: 0

Effective Secrecy Throughput Analysis for Communication Systems with a DF Satellite Relay DF卫星中继通信系统的有效保密吞吐量分析

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00028

Yeqiu Xiao, Yichuan Wang, Wenjiang Ji, Lei Zhu, Xinhong Hei

引用次数: 0