发布求助
文献互助 智能选刊 最新文献

2023 IEEE Symposium on Computers and Communications (ISCC)最新文献

筛选
英文 中文
MESCAL: Malicious Login Detection Based on Heterogeneous Graph Embedding with Supervised Contrastive Learning 基于监督对比学习的异构图嵌入恶意登录检测
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10218074
Wei-Jung Huang, Yangyang Zong, Zhixin Shi, Puzhuo Liu
{"title":"MESCAL: Malicious Login Detection Based on Heterogeneous Graph Embedding with Supervised Contrastive Learning","authors":"Wei-Jung Huang, Yangyang Zong, Zhixin Shi, Puzhuo Liu","doi":"10.1109/ISCC58397.2023.10218074","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10218074","url":null,"abstract":"Malicious logins via stolen credentials have become a primary threat in cybersecurity due to their stealthy nature. Recent malicious login detection methods based on graph learning techniques have made progress due to their ability to capture interconnected relationships among log entries. However, limited malicious samples pose a critical challenge to the detection performance of existing methods. In this paper, we propose MESCAL, a novel approach based on heterogeneous graph embedding with supervised contrastive learning to solve this challenge. Concretely, we construct authentication heterogeneous graphs to represent multiple and interconnected log events. Then, we pretrain a feature extractor with supervised contrastive learning to capture rich semantics on the graphs from limited malicious samples. Based on this, cost-sensitive learning is adopted to distinguish malicious logins on imbalanced data. Extensive evaluations show that the F1 score of MESCAL based on the imbalance dataset is 94.63%, which outperforms state-of-the-art approaches.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133484345","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
Robustness Analysis of Hybrid Machine Learning Model for Anomaly Forecasting in Radio Access Networks 无线接入网异常预测的混合机器学习模型鲁棒性分析
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10218038
Sara Kassan, Imed Hadj-Kacem, S. B. Jemaa, S. Allio
{"title":"Robustness Analysis of Hybrid Machine Learning Model for Anomaly Forecasting in Radio Access Networks","authors":"Sara Kassan, Imed Hadj-Kacem, S. B. Jemaa, S. Allio","doi":"10.1109/ISCC58397.2023.10218038","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10218038","url":null,"abstract":"Quality of Service in mobile networks is a vigorous necessity that depends on the traffic demand growth and the complex emergence of several new services and technologies. It can be improved by reducing the network failures and avoiding the congestion. As a result, a hybrid model can be used for proactive traffic congestion avoidance to alert the operator thus enhancing the end user perceived QoS. This model consists of a co-clustering algorithm to group cells that have similar behaviour based on key performance indicators and a logistic regression model to predict congestion. The hybrid model is compared to most known deep learning models presented in the literature. We consider a Long Short-Term Memory based on recurrent neural network approach and a Temporal Convolutional Network approach for comparison. The different models are compared using real field data from operational Long Term Evolution networks.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"537 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127785073","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
RegexClassifier: A GNN-Based Recognition Method for State-Explosive Regular Expressions RegexClassifier:一种基于gnn的状态爆炸正则表达式识别方法
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10218248
Yuhai Lu, Xiaolin Wang, Fangfang Yuan, Cong Cao, Xiaoliang Zhang, Yanbing Liu
{"title":"RegexClassifier: A GNN-Based Recognition Method for State-Explosive Regular Expressions","authors":"Yuhai Lu, Xiaolin Wang, Fangfang Yuan, Cong Cao, Xiaoliang Zhang, Yanbing Liu","doi":"10.1109/ISCC58397.2023.10218248","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10218248","url":null,"abstract":"Regular expression (regex) matching technology has been widely used in various applications. For the sake of low time complexity and stable performance, Deterministic Finite Automaton (DFA) has become the first choice to perform fast regular expression matching. However, DFA has the state explosion problem, that is, the number of DFA states may increase exponentially while compiling some specific regexes to DFA. The huge memory consumption restricts its practical applications. A lot of works have addressed the DFA state explosion problem; however, none has met the requirements of fast recognition and small memory image. In this paper, we proposed RegexClassifier to recognize state-explosive regexes intelligently and efficiently. It firstly transforms regexes into Non-deterministic Finite Automatons(NFAs), then uses Graph Neural Network(GNN) models to classify NFAs in order to recognize regexes that may cause DFA state explosion. Experiments on typical rule sets show that the classification accuracy of the proposed model is up to 98%.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127393501","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
Backhaul Assessment in Dual Band WiFi Mesh 双频段WiFi网络回程评估
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10217986
J. Soares, Miguel Luís, Duarte M. G. Raposo, P. Rito, S. Sargento
{"title":"Backhaul Assessment in Dual Band WiFi Mesh","authors":"J. Soares, Miguel Luís, Duarte M. G. Raposo, P. Rito, S. Sargento","doi":"10.1109/ISCC58397.2023.10217986","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10217986","url":null,"abstract":"Over the years, WiFi became an essential technology. The success of the introduction of wireless devices with WiFi connectivity increased the demand for better WiFi networks. Such networks need better service and better coverage, either in mobile or residential environments. To solve this challenge, WiFi Alliance developed WiFi EasyMesh, a standard for WiFi networks that uses multiple access points that allow an easy setup and compatibility with WiFi certified devices. This work studies the performance of a mesh wireless network with different frequencies in use by the backhaul links (2.4 GHz and 5 GHz). The results can then be used to derive better backhaul steering algorithms to a better Quality-of-Service.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115191734","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
The Effect of Non-Reference Point Cloud Quality Assessment (NR-PCQA) Loss on 3D Scene Reconstruction from a Single Image 非参考点云质量评估(NR-PCQA)损失对单幅图像重建三维场景的影响
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10218197
Mohamed Zaytoon, Marwan Torki
{"title":"The Effect of Non-Reference Point Cloud Quality Assessment (NR-PCQA) Loss on 3D Scene Reconstruction from a Single Image","authors":"Mohamed Zaytoon, Marwan Torki","doi":"10.1109/ISCC58397.2023.10218197","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10218197","url":null,"abstract":"This paper proposes a two-stage approach for 3D scene reconstruction from a single image. The first stage involves a monocular depth estimation model, and the second stage involves a point cloud model that recovers depth shift and the focal length from the generated depth map. The paper investigates the use of various pre-trained state-of-the-art transformer models and compares them to existing work without transformers. The loss function is improved by adding a No-Reference point cloud quality assessment (NR-PCQA) to account for the quality of the generated point cloud structure. The paper reports results on four datasets using Locally Scale Invariant RMSE (LSIV) as the metric of evaluation. The paper shows that transformer models outperform previous methods, and transformer models that took into account NR-PCQA outperformed those that did not.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115390045","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
P4CTM: Compressed Traffic Pattern Matching Based on Programmable Data Plane 基于可编程数据平面的压缩流量模式匹配
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10218028
Hang Lint, W. Lint, J. Lint, Longlong Zhu, Dong Zhang, Chunming Wu
{"title":"P4CTM: Compressed Traffic Pattern Matching Based on Programmable Data Plane","authors":"Hang Lint, W. Lint, J. Lint, Longlong Zhu, Dong Zhang, Chunming Wu","doi":"10.1109/ISCC58397.2023.10218028","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10218028","url":null,"abstract":"Pattern matching is an important technology applied to many security applications. Most network service providers choose to compress network traffic for better transmission, which brings the challenges of compressed traffic matching. However, existing works focus on improving the performance of uncompressed traffic matching or only realize the compressed traffic matching on end-host that can not keep pace with the dramatic increase in traffic. In this paper, we present P4CTM, a proof-of-concept method to conduct efficient compressed traffic matching on the programmable data plane. P4CTM uses the two-stage scan scheme to skip some bytes of compressed traffic, the 2-stride DFA combines with the compression algorithm to condense the state space, and the wildcard match to downsize the match action tables in the programmable data plane. The experiment indicates that P4CTM skips 83.10% bytes of compressed traffic, condenses the state space by order of magnitude, and reduces most of the table entries.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115598501","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 Deep Learning Approach For Airport Runway Detection and Localization From Satellite Imagery 基于卫星图像的机场跑道检测与定位的深度学习方法
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10217868
Amine Khelifi, Mahmut Gemici, Giuseppina Carannante, C. Johnson, N. Bouaynaya
{"title":"A Deep Learning Approach For Airport Runway Detection and Localization From Satellite Imagery","authors":"Amine Khelifi, Mahmut Gemici, Giuseppina Carannante, C. Johnson, N. Bouaynaya","doi":"10.1109/ISCC58397.2023.10217868","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10217868","url":null,"abstract":"The US lacks a complete national database of private prior permission required airports due to insufficient federal requirements for regular updates. The initial data entry into the system is usually not refreshed by the Federal Aviation Administration (FAA) or local state Department of Transportation. However, outdated or inaccurate information poses risks to aviation safety. This paper suggests a deep learning (DL) approach using Google Earth satellite imagery to identify and locate airport landing sites. The study aims to demonstrate the potential of DL algorithms in processing satellite imagery and improve the precision of the FAA's runway database. We evaluate the performance of Faster Region-based Convolutional Neural Networks using advanced backbone architectures, namely Resnet101 and Resnet-X152, in the detection of airport runways. We incorporate negative samples, i.e., highways images, to enhance the performance of the model. Our simulations reveal that Resnet-X152 outperformed Resnet101 achieving a mean average precision of 76%.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124151401","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
Honoring Heritage, Managing Health: A Mobile Diabetes Self-Management App for Native Americans with Cultural Sensitivity and Local Factors 尊重传统，管理健康:一个具有文化敏感性和当地因素的美国原住民移动糖尿病自我管理应用程序
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10218192
W. Hasan, Juan Li, Shadi Alian, Tianyi Liang, Vikram Pandey, Kimia Tuz Zaman, Jun Kong, Cui Tao
{"title":"Honoring Heritage, Managing Health: A Mobile Diabetes Self-Management App for Native Americans with Cultural Sensitivity and Local Factors","authors":"W. Hasan, Juan Li, Shadi Alian, Tianyi Liang, Vikram Pandey, Kimia Tuz Zaman, Jun Kong, Cui Tao","doi":"10.1109/ISCC58397.2023.10218192","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10218192","url":null,"abstract":"Diabetes has a disproportionate impact on Native Americans (NAs) as a chronic health condition, yet there is a dearth of mobile apps specifically designed for this population. In this paper, we present the design and development of a culturally tailored mobile app for NAs, taking into account their cultural traditions. Our app incorporates NA's traditional foods, food availability, the importance of family and community, cultural practices and beliefs, local resources, and heritage heroes into the app interface and self-management design. The app includes personalized nutrition guidance, family and community-based support, seamless connection to tribal health providers, access to local resources, and integration of cultural elements. By considering the cultural context of NAs, the developed app has the potential to provide culturally sensitive and relevant features that address the unique needs and preferences of NA users, facilitating effective self-management of diabetes.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"767 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117022748","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
Driving into Danger: Adversarial Patch Attack on End-to-End Autonomous Driving Systems Using Deep Learning 驾驶进入危险:使用深度学习的端到端自动驾驶系统的对抗性补丁攻击
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10218291
Tong Wang, Xiaohui Kuang, Hu Li, Qianjin Du, Zhan Hu, Huan Deng, Gang Zhao
{"title":"Driving into Danger: Adversarial Patch Attack on End-to-End Autonomous Driving Systems Using Deep Learning","authors":"Tong Wang, Xiaohui Kuang, Hu Li, Qianjin Du, Zhan Hu, Huan Deng, Gang Zhao","doi":"10.1109/ISCC58397.2023.10218291","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10218291","url":null,"abstract":"Deep learning-based autonomous driving systems have been extensively researched due to their superior performance compared to traditional methods. Specifically, end-to-end deep learning systems have been developed, which directly output control signals for vehicles using various sensor inputs. However, deep learning techniques are vulnerable to security issues, generating adversarial examples that can attack the output of the relevant model. This paper proposes an adversarial example generation method that applies a patch to pedestrians' clothing, which can generate dangerous behaviors when the pedestrian appears within the camera lens, thereby attacking the end-to-end autonomous driving system. The proposed method is validated using the CARLA simulator, and the results demonstrate successful attacks in various weather and lighting conditions, exposing the security vulnerabilities of this type of system. This study highlights the need for further research to address these vulnerabilities and ensure the safety of autonomous driving systems.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121955511","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
Emotional Artificial Intelligence Enabled Facial Expression Recognition for Tele-Rehabilitation: A Preliminary Study 情感人工智能在远程康复中面部表情识别的初步研究
2023 IEEE Symposium on Computers and Communications (ISCC) Pub Date : 2023-07-09 DOI: 10.1109/ISCC58397.2023.10217921
Davide Ciraolo, A. Celesti, M. Fazio, Mirjam Bonanno, M. Villari, R. Calabró
{"title":"Emotional Artificial Intelligence Enabled Facial Expression Recognition for Tele-Rehabilitation: A Preliminary Study","authors":"Davide Ciraolo, A. Celesti, M. Fazio, Mirjam Bonanno, M. Villari, R. Calabró","doi":"10.1109/ISCC58397.2023.10217921","DOIUrl":"https://doi.org/10.1109/ISCC58397.2023.10217921","url":null,"abstract":"Tele-rehabilitation has recently emerged as an effective approach for providing assisted living, increasing clinical outcomes, positively enhancing patients' Quality of Life (QoL) and fostering their reintegration into society, also pushing down clinical costs. Nowadays, tele-rehabilitation has to face two main challenges: motor and cognitive rehabilitation. In this paper, we focus on the latter. Our idea is to monitor the patient's cognitive rehabilitation by analysing his/her facial expressions during motor rehabilitation exercises with the objective to understand if there is a correlation between motor and cognitive outcomes. Therefore, the aim of this preliminary study is to leverage the concept of Emotional Artificial Intelligence (AI) with a Facial Expression Recognition (FER) system which uses the face mesh generated by the MediaPipe suite of libraries to train a Machine Learning (ML) model in order to identify the facial expressions, according to the Ekman's model, contained inside images or video captured during motor rehabilitation exercises performed at home. In particular, different datasets, face features maps and ML models are tested providing an advancement in the state of the art.","PeriodicalId":265337,"journal":{"name":"2023 IEEE Symposium on Computers and Communications (ISCC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124059806","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信