2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)最新文献_第7页

Evaluating the Performance of Containerized Webservers against web servers on Virtual Machines using Bombardment and Siege 使用轰炸和围攻评估容器化web服务器对虚拟机上web服务器的性能

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-05-23 DOI: 10.1109/SERA57763.2023.10197818

Daniel Ukene, H. Wimmer, Jongyeop Kim

引用次数: 0

TIPICAL - Type Inference for Python In Critical Accuracy Level Python临界精度级别的典型类型推断

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-05-23 DOI: 10.1109/SERA57763.2023.10197800

Jonathan Elkobi, Bernd Gruner, Tim Sonnekalb, C. Brust

引用次数: 0

Multi-level Adaptive Execution Tracing for Efficient Performance Analysis 用于高效性能分析的多级自适应执行跟踪

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-05-23 DOI: 10.1109/SERA57763.2023.10197790

Mohammed Adib Khan, Naser Ezzati-Jivan

引用次数: 0

LSTM-AE for Anomaly Detection on Multivariate Telemetry Data 基于多变量遥测数据的LSTM-AE异常检测

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-05-23 DOI: 10.1109/SERA57763.2023.10197673

Anes Abdennebi, Alp Tunçay, Cemal Yilmaz, Anil Koyuncu, Oktay Gungor

{"title":"LSTM-AE for Anomaly Detection on Multivariate Telemetry Data","authors":"Anes Abdennebi, Alp Tunçay, Cemal Yilmaz, Anil Koyuncu, Oktay Gungor","doi":"10.1109/SERA57763.2023.10197673","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197673","url":null,"abstract":"Organizations and companies that collect data generated by sales, transactions, client/server communications, IoT nodes, devices, engines, or any other data generating/exchanging source, need to analyze this data to reveal insights about the running activities on their systems. Since streaming data has multivariate variables bearing dependencies among each other that extend temporally (to previous time steps).Long-Short Term Memory (LSTM) is a variant of the Recurrent Neural Networks capable of learning long-term dependencies using previous timesteps of sequence-shape data. The LSTM model is a valid option to apply to our data for offline anomaly detection and help foresee future system incidents. Anything that negatively affects the system and the services provided via this system is considered an incident.Moreover, the raw input data might be noisy and improper for the model, leading to misleading predictions. A wiser choice is to use an LSTM Autoencoder (LSTM-AE) specialized for extracting meaningful features of the examined data and looking back several steps to preserve temporal dependencies.In our work, we developed two LSTM-AE models. We evaluated them in an industrial setup at Koçfinans (a finance company operating in Turkey), where they have a distributed system of several nodes running dozens of microservices. The outcome of this study shows that our trained LSTM-AE models succeeded in identifying the atypical behavior of offline data with high accuracies. Furthermore, after deploying the models, we identified the system failing at the exact times for the previous two reported failures. While after deployment, it launched cautions preceding the actual failure by a week, proving efficiency on online data. Our models achieved 99.7% accuracy and 89.1% as F1-score. Moreover, it shows potential in finding the proper LSTM-AE model architecture when time series data with temporal dependency property is fed to the model.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121952596","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

Calibrating Cybersecurity Experiments: Evaluating Coverage Analysis for Fuzzing Benchmarks 校准网络安全实验:评估模糊基准的覆盖分析

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-05-23 DOI: 10.1109/SERA57763.2023.10197736

J. Alves-Foss, Aditi Pokharel, Ronisha Shigdel, Jia Song

引用次数: 0

Customer Segmentation Using Credit Card Data Analysis 利用信用卡数据分析进行客户细分

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-05-23 DOI: 10.1109/SERA57763.2023.10197704

S. Raj, Santanu Roy, Surajit Jana, Soumyadip Roy, Takaaki Goto, S. Sen

引用次数: 0

Commit Message Can Help: Security Patch Detection in Open Source Software via Transformer 提交消息可以帮助:安全补丁检测在开放源码软件通过变压器

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-05-23 DOI: 10.1109/SERA57763.2023.10197730

Fei Zuo, Xin Zhang, Yuqi Song, J. Rhee, Jicheng Fu

{"title":"Commit Message Can Help: Security Patch Detection in Open Source Software via Transformer","authors":"Fei Zuo, Xin Zhang, Yuqi Song, J. Rhee, Jicheng Fu","doi":"10.1109/SERA57763.2023.10197730","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197730","url":null,"abstract":"As open source software is widely used, the vulnerabilities contained therein are also rapidly propagated to a large number of innocent applications. Even worse, many vulnerabilities in open-source projects are secretly fixed, which leads to affected software being unaware and thus exposed to risks. For the purpose of protecting deployed software, designing an effective patch classification system becomes more of a need than an option. To this end, some researchers take advantage of the recent advancements in natural language processing to learn both commit messages and code changes. However, they often incur high false positive rates. Not only that, existing works cannot yet answer how much the textual description (such as commit messages) alone can influence the final triage. In this paper, we propose a Transformer based patch classifier, which does not use any code changes as inputs. Surprisingly, the extensive experiment shows the proposed approach can significantly outperform other state-of-the-art work with a high precision of 93.0% and low false positive rate. Therefore, our research further confirms the critical importance of well-crafted commit messages for the later software maintenance. Finally, our case study also identifies 48 silent security patches, which can benefit those affected software.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132087638","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

3 B (Block Byte Bit) Cipher Algorithm for Secure Socket Layer 安全套接字层的B(块字节位)密码算法

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-05-23 DOI: 10.1109/SERA57763.2023.10197799

Y. Geum

引用次数: 0

Operation Management Method of Software Defined Perimeter for Promoting Zero-Trust Model 推广零信任模型的软件定义周界运行管理方法

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-05-23 DOI: 10.1109/SERA57763.2023.10197716

S. Tanimoto, Sogen Hori, Hiroyuki Sato, Atsushi Kanai

{"title":"Operation Management Method of Software Defined Perimeter for Promoting Zero-Trust Model","authors":"S. Tanimoto, Sogen Hori, Hiroyuki Sato, Atsushi Kanai","doi":"10.1109/SERA57763.2023.10197716","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197716","url":null,"abstract":"Telework has been on the rise since the advent of COVID-19, and concerns have arisen about issues such as information leakage due to internal fraud. The zero-trust model is attracting attention as a countermeasure. This model reduces risk by constantly performing authentication and authorization, thus leading to improved security levels and safer operation. However, currently less than 40% of the companies in Japan have introduced zero trust into their security policies, mainly due to the lack of specific guidelines for operational management. We have therefore developed a security policy (service authorization conditions) for the software defined perimeter (SDP) zero-trust model as a universal operational management method to promote zero-trust implementation. Specifically, we simplify the time/place/occasion (TPO) conditions of users as T (inside/outside working hours), P (inside/outside the company, telework), and O (with/without visitors), resulting in 12 patterns, and for each of these TPO conditions, we propose detailed new service authorization conditions for SDP. The results of qualitative evaluation demonstrated the effectiveness of the proposed method. Our findings will contribute to the introduction of the zero-trust model and pave the way for safer and more secure corporate networks.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122233897","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

Evaluating Code Metrics in GitHub Repositories Related to Fake News and Misinformation 评估与假新闻和错误信息相关的GitHub存储库中的代码度量

2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2023-04-26 DOI: 10.1109/SERA57763.2023.10197739

Jason Duran, M. Sakib, Nasir U. Eisty, Francesca Spezzano

{"title":"Evaluating Code Metrics in GitHub Repositories Related to Fake News and Misinformation","authors":"Jason Duran, M. Sakib, Nasir U. Eisty, Francesca Spezzano","doi":"10.1109/SERA57763.2023.10197739","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197739","url":null,"abstract":"The surge of research on fake news and misinformation in the aftermath of the 2016 election has led to a significant increase in publicly available source code repositories. Our study aims to systematically analyze and evaluate the most relevant repositories and their Python source code in this area to improve awareness, quality, and understanding of these resources within the research community. Additionally, our work aims to measure the quality and complexity metrics of these repositories and identify their fundamental features to aid researchers in advancing the field’s knowledge in understanding and preventing the spread of misinformation on social media. As a result, we found that more popular fake news repositories and associated papers with higher citation counts tend to have more maintainable code measures, more complex code paths, a larger number of lines of code, a higher Halstead effort, and fewer comments. Utilizing these findings to devise efficient research and coding techniques to combat fake news, we can strive towards building a more knowledgeable and well-informed society.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127308314","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