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Machine Learning Techniques and Data Science最新文献

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The Evolution of Vector Machine Support in the Field of Intrusion Detection Systems 向量机支持在入侵检测系统中的发展
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111817
Ouafae Elaeraj, C. Leghris
{"title":"The Evolution of Vector Machine Support in the Field of Intrusion Detection Systems","authors":"Ouafae Elaeraj, C. Leghris","doi":"10.5121/csit.2021.111817","DOIUrl":"https://doi.org/10.5121/csit.2021.111817","url":null,"abstract":"With the increase in Internet and local area network usage, malicious attacks and intrusions into computer systems are growing. The design and implementation of intrusion detection systems became extremely important to help maintain good network security. Support vector machines (SVM), a classic pattern recognition tool, has been widely used in intrusion detection. They make it possible to process very large data with great efficiency and are easy to use, and exhibit good prediction behavior. This paper presents a new SVM model enriched with a Gaussian kernel function based on the features of the training data for intrusion detection. The new model is tested with the CICIDS2017 dataset. The test proves better results in terms of detection efficiency and false alarm rate, which can give better coverage and make the detection more effective.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121231757","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
LFO2: An Enhanced Version of Learning-From-OPT Caching Algorithm LFO2:一种改进版本的learn - from - opt缓存算法
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111806
Yipkei Kwok, David L. Sullivan
{"title":"LFO2: An Enhanced Version of Learning-From-OPT Caching Algorithm","authors":"Yipkei Kwok, David L. Sullivan","doi":"10.5121/csit.2021.111806","DOIUrl":"https://doi.org/10.5121/csit.2021.111806","url":null,"abstract":"Recent machine learning-based caching algorithm have shown promise. Among them, Learning-FromOPT (LFO) is the state-of-the-art supervised learning caching algorithm. LFO has a parameter named Window Size, which defines how often the algorithm generates a new machine-learning model. While using a small window size allows the algorithm to be more adaptive to changes in request behaviors, experimenting with LFO revealed that the performance of LFO suffers dramatically with small window sizes. This paper proposes LFO2, an improved LFO algorithm, which achieves high object hit ratios (OHR) with small window sizes. This results show a 9% OHR increase with LFO2. As the next step, the machine-learning parameters will be investigated for tuning opportunities to further enhance performance.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128439701","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
Security in Agile Development, use Case in Typeform 敏捷开发中的安全性，Typeform中的用例
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111809
Pau Julià, David Salvador, Marc Peña
{"title":"Security in Agile Development, use Case in Typeform","authors":"Pau Julià, David Salvador, Marc Peña","doi":"10.5121/csit.2021.111809","DOIUrl":"https://doi.org/10.5121/csit.2021.111809","url":null,"abstract":"Software development methodologies have evolved during the last years to reduce the time to market to the minimum possible. Agile is one of the most common and used methodologies for rapid application development. As the agile manifesto defines in its 12 principles, one of its main goals is to satisfy the customer needs through early and continuous delivery of valuable software. Significantly, that none of the principles refers to security. In this paper, we will explain how Typeform integrates security activities into the whole development process, reducing at the same time the phases on the S-SDLC to reduce friction and improve delivery while maintaining the security level.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124503640","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 Novel Privacy-Preserving Scheme in IoT-Based Social Distancing Technologies 基于物联网的社交距离技术中的一种新的隐私保护方案
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111820
Arwa Alrawais, Fatemah Alharbi, Moteeb Almoteri, S. A. Aljwair, Sara SAljwair
{"title":"A Novel Privacy-Preserving Scheme in IoT-Based Social Distancing Technologies","authors":"Arwa Alrawais, Fatemah Alharbi, Moteeb Almoteri, S. A. Aljwair, Sara SAljwair","doi":"10.5121/csit.2021.111820","DOIUrl":"https://doi.org/10.5121/csit.2021.111820","url":null,"abstract":"The COVID-19 pandemic has swapped the world, causing enormous cases, which led to high mortality rates across the globe. Internet of Things (IoT) based social distancing techniques and many current and emerging technologies have contributed to the fight against the spread of pandemics and reduce the number of positive cases. These technologies generate massive data, which will pose a significant threat to data owners’ privacy by revealing their lifestyle and personal information since that data is stored and managed by a third party like a cloud. This paper provides a new privacy-preserving scheme based on anonymization using an improved slicing technique and implying distributed fog computing. Our implementation shows that the proposed approach ensures data privacy against a third party intending to violate it for any purpose. Furthermore, our results illustrate our scheme’s efficiency and effectiveness.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125418965","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
Reducing Cyber Incident Response to Protect CNI from Cyber Attacks using an N-SIEM Integration with an ICTI-CNI 通过与ict -CNI集成N-SIEM，减少网络事件响应，保护CNI免受网络攻击
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111818
Igli Tafa, Kevin Shahollari
{"title":"Reducing Cyber Incident Response to Protect CNI from Cyber Attacks using an N-SIEM Integration with an ICTI-CNI","authors":"Igli Tafa, Kevin Shahollari","doi":"10.5121/csit.2021.111818","DOIUrl":"https://doi.org/10.5121/csit.2021.111818","url":null,"abstract":"The rapid evolution of technology has increased the role of cybersecurity and put it at the center of nationalcritical infrastructure. This role supports and guarantees the vital services of (CNI) while provides the proper functionalities for running operations between the public and private sectors. This evolution has hadthe same impact on cyberattack tools, methods, techniques used to gain unauthorized access to these computer systems that contain confidential and high-value information in the digital data sales market or asit called \"darkweb\". As a result, it has become necessary to monitor all events of the National Critical Infrastructure (CNI) computer systems. This proposed system uses a centralized National SIEM (N-SIEM) specializing in the correlation of security events caused by cyber attacks, collected by CNIs systems while integrating with anInternational Cyber Threat Intelligence system (ICTI-CNI). In addition, this conceptual model collects security breach events of CNIs systems, analyzes only cyber attacks, and correlates these security events in real-time with an intelligent automated platform while reducing the response time of security analysts.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125420335","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
Automated Testing of Data Survivability and Restorability 数据生存性和可恢复性的自动化测试
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111810
Sylvain Muller, C. Bryce
{"title":"Automated Testing of Data Survivability and Restorability","authors":"Sylvain Muller, C. Bryce","doi":"10.5121/csit.2021.111810","DOIUrl":"https://doi.org/10.5121/csit.2021.111810","url":null,"abstract":"Regular data backups are fundamental for protection against cyber-attacks and damage to infrastructure. To ensure a successful restoration, backed up data must be tested regularly for restorability to the company’s current environment. Cloud providers generally test their backedup data, but a testing framework is also required for locally stored files and databases. The paper proposes an automated test framework that validates the continued usability of backed up data for target restoration environments. The framework tests backups of Excel files, MySQL and Postgres databases, PDF documents and flat files.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130126294","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
An Analysis of Face Recognition under Face Mask Occlusions 人脸遮挡下的人脸识别分析
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111804
Susith Hemathilaka, A. Aponso
{"title":"An Analysis of Face Recognition under Face Mask Occlusions","authors":"Susith Hemathilaka, A. Aponso","doi":"10.5121/csit.2021.111804","DOIUrl":"https://doi.org/10.5121/csit.2021.111804","url":null,"abstract":"The face mask is an essential sanitaryware in daily lives growing during the pandemic period and is a big threat to current face recognition systems. The masks destroy a lot of details in a large area of face and it makes it difficult to recognize them even for humans. The evaluation report shows the difficulty well when recognizing masked faces. Rapid development and breakthrough of deep learning in the recent past have witnessed most promising results from face recognition algorithms. But they fail to perform far from satisfactory levels in the unconstrained environment during the challenges such as varying lighting conditions, low resolution, facial expressions, pose variation and occlusions. Facial occlusions are considered one of the most intractable problems. Especially when the occlusion occupies a large region of the face because it destroys lots of official features.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133164358","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: 2
BurnoutWords - Detecting Burnout for a Clinical Setting BurnoutWords -检测倦怠的临床设置
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111815
Sukanya Nath, Mascha Kurpicz-Briki
{"title":"BurnoutWords - Detecting Burnout for a Clinical Setting","authors":"Sukanya Nath, Mascha Kurpicz-Briki","doi":"10.5121/csit.2021.111815","DOIUrl":"https://doi.org/10.5121/csit.2021.111815","url":null,"abstract":"Burnout, a syndrome conceptualized as resulting from major workplace stress that has not been successfully managed, is a major problem of today's society, in particular in crisis times such as a global pandemic situation. Burnout detection is hard, because the symptoms often overlap with other diseases and syndromes. Typical clinical approaches are using inventories to assess burnout for their patients, even though free-text approaches are considered promising. In research of natural language processing (NLP) applied to mental health, often data from social media is used and not real patient data, which leads to some limitations for the application in clinical use cases. In this paper, we fill the gap and provide a dataset using extracts from interviews with burnout patients containing 216 records. We train a support vector machine (SVM) classifier to detect burnout in text snippets with an accuracy of around 80%, which is clearly higher than the random baseline of our setup. This provides the foundation for a next generation of clinical methods based on NLP.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121879808","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
Method for Orthogonal Edge Routing of Directed Layered Graphs with Edge Crossings Reduction 有向分层图正交边路由的边交减少方法
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111821
Jordan Raykov
{"title":"Method for Orthogonal Edge Routing of Directed Layered Graphs with Edge Crossings Reduction","authors":"Jordan Raykov","doi":"10.5121/csit.2021.111821","DOIUrl":"https://doi.org/10.5121/csit.2021.111821","url":null,"abstract":"This paper presents a method for automated orthogonal edge routing of directed layered graphs using the described edge crossings reduction heuristic algorithm. The method assumes the nodes are pre-arranged on a rectangular grid composed of layers across the flow direction and lanes along the flow direction. Both layers and lanes are separated by rectangular areas defined as pipes. Each pipe has associated segment tracks. The edges are represented as orthogonal polylines consisting of line segments and routed along the shortest paths. Each segment is assigned to a pipe and to a segment track in it. The edge crossings reduction uses an iterative algorithm to resolve crossings between segments. Conflicting segments are reassigned to adjacent segment tracks, either by swapping with adjacent segments, or by inserting new tracks and calculating the shortest paths of edges. The algorithm proved to be efficient and was implemented in an interactive graph design tool.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127148816","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
Federated Learning with Random Communication and Dynamic Aggregation 具有随机通信和动态聚合的联邦学习
Machine Learning Techniques and Data Science Pub Date : 2021-11-20 DOI: 10.5121/csit.2021.111816
Ruolin Huang, Ting Lu, Yiyang Luo, Guohua Liu, Shan Chang
{"title":"Federated Learning with Random Communication and Dynamic Aggregation","authors":"Ruolin Huang, Ting Lu, Yiyang Luo, Guohua Liu, Shan Chang","doi":"10.5121/csit.2021.111816","DOIUrl":"https://doi.org/10.5121/csit.2021.111816","url":null,"abstract":"Federated Learning (FL) is a setting that allows clients to train a joint global model collaboratively while keeping data locally. Due to FL has advantages of data confidential and distributed computing, interest in this area has increased. In this paper, we designed a new FL algorithm named FedRAD. Random communication and dynamic aggregation methods are proposed for FedRAD. Random communication method enables FL system use the combination of fixed communication interval and constrained variable intervals in a single task. Dynamic aggregation method reforms aggregation weights and makes weights update automately. Both methods aim to improve model performance. We evaluated two proposed methods respectively, and compared FedRAD with three algorithms on three hyperparameters. Results at CIFAR-10 demonstrate that each method has good performance, and FedRAD can achieve higher classification accuracy than state-of-the-art FL algorithms.","PeriodicalId":414015,"journal":{"name":"Machine Learning Techniques and Data Science","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130928263","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
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