2022 IEEE Symposium on Computers and Communications (ISCC)最新文献

Enhancing Privacy of Online Chat Apps Utilising Secure Node End-to-End Encryption (SNE2EE) 利用安全节点端到端加密(SNE2EE)增强在线聊天应用的隐私

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9912888

Nithish Velagala, Leandros A. Maglaras, N. Ayres, S. Moschoyiannis, L. Tassiulas

引用次数: 0

A First Look at Accurate Network Traffic Generation in Virtual Environments 虚拟环境中准确的网络流量生成的第一眼

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9913058

Giuseppe Aceto, Ciro Guida, Antonio Montieri, V. Persico, A. Pescapé

引用次数: 1

A Platform for Federated Learning on the Edge: a Video Analysis Use Case 边缘联合学习平台:一个视频分析用例

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9912968

Alessio Catalfamo, A. Celesti, M. Fazio, Giovanni Randazzo, M. Villari

引用次数: 5

ActDetector: A Sequence-based Framework for Network Attack Activity Detection ActDetector:基于序列的网络攻击活动检测框架

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9912824

Jiaqi Kang, Huiran Yang, Y. Zhang, Yueyue Dai, Mengqi Zhan, Weiping Wang

{"title":"ActDetector: A Sequence-based Framework for Network Attack Activity Detection","authors":"Jiaqi Kang, Huiran Yang, Y. Zhang, Yueyue Dai, Mengqi Zhan, Weiping Wang","doi":"10.1109/ISCC55528.2022.9912824","DOIUrl":"https://doi.org/10.1109/ISCC55528.2022.9912824","url":null,"abstract":"The cyber security situation is not optimistic in recent years due to the rapid growth of security threats. What's more worrying is that threats are tending to be more sophis-ticated, which poses challenges to attack activity analysis. It is quite important for analysts to understand attack activities from a holistic perspective, rather than just pay attention to alerts. Currently, the attack activity analysis generally relies on human resources, which is a heavy workload for manual analysis. Besides, it's difficult to achieve high detection accuracy due to the missing and false-positive alerts. In this paper, we propose a new framework, ActDetector, to detect attack activities automatically from the raw Network Intrusion Detection System (NIDS) alerts, which will greatly reduce the workload of security analysts. We extract attack phase descriptions from alerts and embed attack activity descriptions to obtain their numerical expression. Finally, we use a temporal-sequence-based model to detect potential attack activities. We evaluate ActDetector with three datasets. Experimental results demonstrate that ActDetector can detect attack activities from the raw NIDS alerts with an average of 94.8% Precision, 95.0% Recall, and 94.6% F1-score.","PeriodicalId":309606,"journal":{"name":"2022 IEEE Symposium on Computers and Communications (ISCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125569346","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

Deep-Learning for Cooperative Spectrum Sensing Optimization in Cognitive Internet of Things 认知物联网中协同频谱感知优化的深度学习

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9912823

Hind Boukhairat, M. Koulali

引用次数: 0

Efficient OFDM Channel Estimation with RRDBNet 基于RRDBNet的OFDM信道估计

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9912769

Wei Gao, Meihong Yang, Wei Zhang, Libin Liu

引用次数: 1

Privacy vs Accuracy Trade-Off in Privacy Aware Face Recognition in Smart Systems 智能系统中隐私感知人脸识别的隐私与准确性权衡

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9912465

Wisam Abbasi, Paolo Mori, A. Saracino, V. Frascolla

引用次数: 2

Scalable Digital Pathology Platform Over Standard Cloud Native Technologies 基于标准云原生技术的可扩展数字病理平台

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9912933

Tibério Baptista, Rui Jesus, Luís Bastião Silva, C. Costa

引用次数: 0

Real-time Resource Management in Smart Energy-Harvesting Systems 智能能量收集系统中的实时资源管理

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9912792

M. Abdulla, Audrey Queudet, M. Chetto, Lamia Belouaer

引用次数: 0

Deep Reinforcement Learning-based Radio Resource Allocation and Beam Management under Location Uncertainty in 5G mm Wave Networks 5G毫米波网络中基于深度强化学习的无线资源分配与波束管理

2022 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2022-06-30 DOI: 10.1109/ISCC55528.2022.9912837

Y. Yao, Hao Zhou, M. Erol-Kantarci

{"title":"Deep Reinforcement Learning-based Radio Resource Allocation and Beam Management under Location Uncertainty in 5G mm Wave Networks","authors":"Y. Yao, Hao Zhou, M. Erol-Kantarci","doi":"10.1109/ISCC55528.2022.9912837","DOIUrl":"https://doi.org/10.1109/ISCC55528.2022.9912837","url":null,"abstract":"Millimeter Wave (mmWave) is an important part of 5G new radio (NR), in which highly directional beams are adapted to compensate for the substantial propagation loss based on UE locations. However, the location information may have some errors such as GPS errors. In any case, some uncertainty, and localization error is unavoidable in most settings. Applying these distorted locations for clustering will increase the error of beam management. Meanwhile, the traffic demand may change dynamically in the wireless environment. Therefore, a scheme that can handle both the uncertainty of localization and dynamic radio resource allocation is needed. In this paper, we propose a UK-means-based clustering and deep reinforcement learning-based resource allocation algorithm (UK-DRL) for radio resource allocation and beam management in 5G mm Wave networks. We first apply UK-means as the clustering algorithm to mitigate the localization uncertainty, then deep reinforcement learning (DRL) is adopted to dynamically allocate radio resources. Finally, we compare the UK-DRL with K-means-based clustering and DRL-based resource allocation algorithm (K-DRL), the simulations show that our proposed UK-DRL-based method achieves 150% higher throughput and 61.5% lower delay compared with K-DRL when traffic load is 4Mbps.","PeriodicalId":309606,"journal":{"name":"2022 IEEE Symposium on Computers and Communications (ISCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129202662","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: 4