检索结果-内蒙古大学图书馆

Security measures and intrusion detection systems for preventing and mitigating SSL renegotiation denial of service attacks

引用

AIP Conference Proceedings 2024年第1期3135卷

作者： Amalia Nurain Teddy Mantoro Rudy A. G. Gultom Richardus E. Indrajit Cyber Defense Engineering Study Program Faculty of Defense Science and Technology The Republic of Indonesia Defense University Bogor Indonesia Media-Tech Lab Departement of Computer Science Sampoerna University Jakarta Indonesia Pradita University Jakarta Indonesia

Inundating a system, network, or application with traffic is the goal of Denial of Service (DoS) attacks, a disruptive form of attack. SSL DoS attacks, particularly those involving renegotiation, are of particular concern. In order to address these types of attacks, the study proposes several security measures, including rate restriction, session caching, SSL acceleration, and integrating Intrusion Detection Systems (IDS) with a systematic technique method to reduce the risks associated with SSL renegotiation DoS attacks. This study investigates the security measures for preventing and mitigating SSL DoS attacks, with a focus on renegotiation attacks. It offers advice and insights for protecting systems to SSL server administrators and network security professionals by doing rate restriction, session caching, and SSL acceleration to avoid SSL DoS attacks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Information Fragmentation, Encryption and Information Flow in Complex Biological Networks

arXiv

引用

arXiv 2021年

作者： Bohm, Clifford Kirkpatrick, Douglas Cao, Victoria Adami, Christoph Deptartment of Integrated Biology Michigan State University East Lansing48824 United States BEACON Center for the Study of Evolution in Action Michigan State University East Lansing48824 United States Department of Computer Science and Engineering Michigan State University East Lansing48824 United States Department of Microbiology and Molecular Genetics Michigan State University East Lansing48824 United States Program in Ecology Evolution and Behavior Michigan State University East Lansing48824 United States

Assessing where and how information is stored in biological networks (such as neuronal and genetic networks) is a central task both in neuroscience and in molecular genetics, but most available tools focus on the network's structure as opposed to its function. Here we introduce a new information-theoretic tool: information fragmentation analysis that, given full phenotypic data, allows us to localize information in complex networks, determine how fragmented (across multiple nodes of the network) the information is, and assess the level of encryption of that information. Using information fragmentation matrices we can also create information flow graphs that illustrate how information propagates through these networks. We illustrate the use of this tool by analyzing how artificial brains that evolved in silico solve particular tasks, and show how information fragmentation analysis provides deeper insights into how these brains process information and "think". The measures of information fragmentation and encryption that result from our methods also quantify complexity of information processing in these networks and how this processing complexity differs between primary exposure to sensory data (early in the lifetime) and later routine processing. © 2021, CC BY.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Empowering Biomedical Discovery with AI Agents

arXiv

引用

arXiv 2024年

作者： Gao, Shanghua Fang, Ada Huang, Yepeng Giunchiglia, Valentina Noori, Ayush Schwarz, Jonathan Richard Ektefaie, Yasha Kondic, Jovana Zitnik, Marinka Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Program in Biological and Biomedical Sciences Harvard Medical School BostonMA United States Department of Brain Sciences Imperial College London London United Kingdom Harvard College CambridgeMA United States Program in Biomedical Informatics Harvard Medical School BostonMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University MA United States Broad Institute of MIT and Harvard CambridgeMA United States Harvard Data Science Initiative CambridgeMA United States

We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI’s ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies. © 2024, CC BY.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Graph Artificial Intelligence in Medicine

引用

Biomedical Data science 1000年第1期7卷 345-368页

作者： Ruth Johnson Michelle M. Li Ayush Noori Owen Queen Marinka Zitnik 1Department of Biomedical Informatics Harvard Medical School Boston Massachusetts USA email: marinka@hms.harvard.edu 2Berkowitz Family Living Laboratory Harvard Medical School Boston Massachusetts USA 3Bioinformatics and Integrative Genomics Program Harvard Medical School Boston Massachusetts USA 4Department of Computer Science Harvard John A. Paulson School of Engineering and Applied Sciences Allston Massachusetts USA 5Broad Institute of MIT and Harvard Cambridge Massachusetts USA 7Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University Allston Massachusetts USA 6Harvard Data Science Initiative Cambridge Massachusetts USA

In clinical artificial intelligence (AI), graph representation learning, mainly through graph neural networks and graph transformer architectures, stands out for its capability to capture intricate relationships and structures within clinical datasets. With diverse data—from patient records to imaging—graph AI models process data holistically by viewing modalities and entities within them as nodes interconnected by their relationships. Graph AI facilitates model transfer across clinical tasks, enabling models to generalize across patient populations without additional parameters and with minimal to no retraining. However, the importance of human-centered design and model interpretability in clinical decision-making cannot be overstated. Since graph AI models capture information through localized neural transformations defined on relational datasets, they offer both an opportunity and a challenge in elucidating model rationale. Knowledge graphs can enhance interpretability by aligning model-driven insights with medical knowledge. Emerging graph AI models integrate diverse data modalities through pretraining, facilitate interactive feedback loops, and foster human–AI collaboration, paving the way toward clinically meaningful predictions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Charting the territory of AI-Mediated informal digital learning in teaching design thinking for addressing design problems

引用

AIP Conference Proceedings 2024年第1期3207卷

作者： Ahmad Al Yakin Ahmad J. Obaid Muthmainnah Muthmainnah Abdul Razzaq Jabr Al-Majidi Teacher Training and Education Faculty Pancasila and Civic education study program Universitas Al Asyariah Mandar Polewali Mandar Indonesia Faculty of Computer Science and Mathematics University of Kufa Najaf Iraq Teacher Training and Education Faculty Indonesian Language study program Universitas Al Asyariah Mandar Polewali Mandar Indonesia Al-Esraa University Baghdad Iraq

In the era of digital-based education, the learning process is officially in the AI era. Given recent advances in generative AI, this research seeks to investigate how users of language modelling platforms (Monica Bot) use and utilise this tool to develop design problems (DP) for pre-service teachers and how design thinking can work together. This implies that, today, design thinking can be more practical with the help of AI. Using an interview guide and an adapted Technology Acceptance Model (TAM) questionnaire, this study used an explanatory sequential mixed-methods approach to collect data. The research population was 207 teachers of professional education (PPG), and 32 pre-service teachers were the sample in this study who were selected using purposive techniques and participated in AI and an online survey, with seven pre-service teachers attending follow-up interviews. Quantitative analysis provides a statistical explanation for the implementation of AI bot technology by teacher professional education (PPG) as perceived ease of use, perceived usefulness, intention to use, actual use, and design problem. The interview data revealed three main themes: (1) how students’ ideas about how easy Monica Bot is to use changed as they used it; (2) how students’ desire to use grows as they learn more about AI-Bot’s strengths and weaknesses; and (3) how students actually use AI-Bots for design thinking, which means using them as design partners. How pre-service teachers engage in innovative DT activities while navigating the opportunities and limitations of advanced AI systems can be better understood when quantitative and qualitative data are correlated. This study offers implications for future classroom practice and research by understanding these activities, thereby paying attention to attitudes and adding to the existing body of knowledge about the theoretical foundations of design thinking and education using design thinking and computational thinking and the practice

关键词：

来源：评论

学校读者我要写书评

暂无评论

Emergence of functional information from multivariate correlations

arXiv

引用

arXiv 2021年

作者： Adami, Christoph Nitash, C.G. Department of Microbiology and Molecular Genetics Michigan State University East LansingMI48824 United States Beacon Center for the Study of Evolution Action Michigan State University East LansingMI48824 United States Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Program in Ecology Evolution and Behavior Michigan State University East LansingMI48824 United States Department of Computer Science and Engineering Michigan State University East LansingMI48824 United States

The information content of symbolic sequences (such as nucleic- or amino acid sequences, but also neuronal firings or strings of letters) can be calculated from an ensemble of such sequences, but because information cannot be assigned to single sequences, we cannot correlate information to other observables attached to the sequence. Here we show that an information score obtained from multivariate (multiple-variable) correlations within sequences of a \training" ensemble can be used to predict observables of out-of-sample sequences with an accuracy that scales with the complexity of correlations, showing that functional information emerges from a hierarchy of multi-variable correlations. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Digital Forensics Investigation and Incident Response in Internet of Things (IoT-DFIR): Challenges and Models

Digital Forensics Investigation and Incident Response in Int...

引用

International Conference on Wireless and Telematics (ICWT)

作者： Syaiful Ahdan Eki Ahmad Zaki Hamidi Sampurna Dadi Riskiono Ridha Muldina Negara Ratna Mayasari Suci Ramadona Ade Nurhayati Adi Sucipto Jupriyadi Galih Nugraha Nurkahfi Dzata Farahiyah Muchammad Naseer Faculty of Engineering & Computer Science Universitas Teknokrat Indonesia Lampung Indonesia Electrical Engineering Department UIN Sunan Gunung Djati Bandung Bandung Indonesia School of Electrical Engineering Telkom University Bandung Indonesia Elearical Engineering Study Program Politeknik Caltex Riau Riau Indonesia Faculty of Engineering Institut Teknologi Telkom Jakarta Jakarta Indonesia National Research and Innovation Agency (BRIN) Bandung Indonesia Faculty of Industrial Technology Universitas Islam Indonesia Yogyakarta Yogyakarta Indonesia Informatics Department Sekolah Tinggi Teknologi Bandung Bandung Indonesia

Many different industries are currently making substantial use of the Internet of Things (IoT). IoT is the process through which electronic devices communicate with their surrounding virtual environment by continuously exchanging data via sensors. Due to increased IoT security concerns, digital forensic investigators now possess greater knowledge and abilities to investigate IoT devices. IoT-DigFor are required in terms of cybercrime due to the rapid growth in the number of electronic devices and the collection and consumption of enormous amounts of data. IoT systems with billions of devices have produced a significant amount of evidence, which presents a significant challenge to digital investigators and practitioners who must connect with IoT devices to conduct fast and thorough investigations into cybercrimes. This article presents detailed information about forensics in the IoT environment. The IoT forensic paradigm and the challenges that design-based security requirements and IoT system security offer for IoT-DigFor are covered in great detail at the beginning of the article.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An analysis of Fama and French three factor model in market reaction to Indonesia presidential election in 2019

引用

Journal of Physics: Conference Series 2019年第6期1341卷

作者： Diaraya L Haryanto A Lawi S Amir A Navira A R Raya Lecturers in Computer Science Study Program Faculty of Mathematics and Natural Sciences Hasanuddin University Student of Department of Mathematics Faculty of Mathematics and Natural Sciences Hasanuddin University Student of Department of Accounting Faculty of Economy and Business Hasanuddin University

This study reveals stock market reaction to Indonesia presidential election in 2019 using Fama and French Three Factor Model with accounting dependent variable being Average Abnormal Return (AAR) in addition to Earning Per Share (EPS), Debt to Equity ratio (DER), Return on Assets (ROA), and Return on Equity (ROE) as independent variables. The research population was all stocks of the companies registered in the Indonesia Stock Exchange in 2019 with their dividend announcement. The characteristic of the observed object was stock price measured by return, abnormal return and average abnormal return during 111-day-observation comprising of 11 days of windows period observation and 100 days of estimation period. The data from 101 companies as samples determined through the purposive sampling technique were analyzed using SPSS software version 23, which represented all industrial sectors in Indonesia Stock Exchange. The measure and analysis of companies stocks concluded that a gradual rise in AAR values was witnessed in all stock portfolios during the announcement date.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comparison heuristics method for solving two echelon vehicle routing problem

引用

AIP Conference Proceedings 2024年第1期3029卷

作者： Muhammad Khahfi Zuhanda Saib Suwilo Opim Salim Sitompul Mardiningsih Informatics Engineering Study Program Faculty Engineering Universitas Medan Area Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Today, almost everyone has done online shopping activities. The presence of e-commerce makes it easier for humans to do shopping. E-commerce companies compete to provide the best service to the community. One of them is in the delivery within the city. In terms of city delivery, the 2E-VRP model has been discussed a lot lately in terms of consolidating shipments. This study aims to present the 2E-VRP mathematical model and work in two stages to find a solution. In this article, the author also compares solutions with several heuristic models including 2-opt, repetitive nearest neighbor, nearest neighbor, farthest insertion, cheapest insertion, arbitrary insertion, and nearest insertion. From the results of research conducted by the 2-opt method, farthest insertion, cheapest insertion, and nearest insertion, the total distance is the best, all three get the same distance, then followed by the nearest insertion, arbitrary insertion, and nearest insertion methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Variational quantum circuit-based quantum machine learning approach for predicting corrosion inhibition efficiency of pyridine-quinoline compounds

Materials Today Quantum

引用

Materials Today Quantum 2024年 2卷

作者： Muhamad Akrom Supriadi Rustad Hermawan Kresno Dipojono Study Program in Informatics Engineering Faculty of Computer Science Universitas Dian Nuswantoro Semarang 50131 Indonesia Research Center for Materials Informatics Faculty of Computer Science Universitas Dian Nuswantoro Semarang 50131 Indonesia Quantum and Nano Technologies Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung 40132 Indonesia

This work used a variational quantum circuit (VQC) in conjunction with a quantitative structure-property relationship (QSPR) model to completely investigate the corrosion inhibition efficiency (CIE) displayed by pyridine-quinoline compounds acting as corrosion inhibitors. Compared to conventional methods like multilayer perceptron neural networks (MLPNN), the VQC model predicts the CIE more accurately. With a coefficient of determination (R 2 ), root mean square error (RMSE), mean absolute error (MAE), and mean absolute deviation (MAD) values of 0.989, 0.027, 0.024, and 0.019, respectively, VQC performs better. The established VQC model predicts the CIE with outstanding predictive accuracy for four newly synthesized pyrimidine derivative compounds: 1-(4-fluorophenyl)- 3-(4-(pyridin-4-ylmethyl)phenyl)urea (P1) , 1-phenyl-3-(4-(pyridin-4-ylmethyl)phenyl)urea (P2) , 1-(4-methylphenyl)-3-(4-(pyridin-4-ylmethyl)phenyl)urea (P3) , and quaternary ammonium salt dimer (P4) . It generates remarkably high CIE values of 92.87, 94.05, 94.96, and 96.93 for P1, P2, P3, and P4, respectively. With its ability to streamline the testing and production processes for novel anti-corrosion materials, this innovative approach holds the potential to revolutionize the market.

关键词： Variational quantum circuit QSPR Corrosion inhibition Pyridine-quinoline

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：