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Australasian Telecommunication Networks and Applications Conference, ATNAC

作者： Santanam Kasturi Xiaolong Li John Pickard Peng Li Technology Management Indiana State University Terre Haute USA Dept. of Electronics and Computer Engineering Indiana State University Terre Haute USA Dept. of Technology Sys East Carolina University Greenville USA Dept. of Technology Systems East Carolina University Greenville USA

Vulnerability data gathered from multiple detection and monitoring capabilities at different layers of an application using a time-series analysis will provide value and insights by doing a statistical correlation with attack requests observed using a Web Application Firewall (WAF) monitoring solution. Static Analysis Security Testing, Software Composition Analysis, Dynamic Analysis Security Testing (DAST), Application Ethical Hack, Application Programming Interface (API) testing are the tests / scans that have been used to gather vulnerability data for this study. Correlations can further help track abnormal transaction paths if we follow specific ones pointed out by the statistical analysis for those requests that are not blocked by the rules and are allowed as valid transactions to pass through. This provides a narrowed down focus on the convergence of observability and security, critical to realizing a near-real time rapid action. Observations must continue for many days as a time series ensuring consistency and reliability in data collections and analysis. Multiple applications must be observed in a similar manner for ensuring validity of the process for analysis. Also, gathering sufficient data that is large enough to represent a reasonable population of web applications within an organization is a significant factor in achieving reliable correlation. Applying Pearson Correlation (or Spearman Correlation for distributions that are not normal) technique provides insight into Significance (two-tailed) as to whether a correlation is present over large number of data points. Results of analysis show evidence of correlations among specific attack requests monitored by the WAF and corresponding vulnerabilities in applications, detected using one or more methods. This is significant to looking for more insights into how these correlations can further explored into predicting attack patterns based on existing vulnerabilities.

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Maximum Length Rll Sequences in De Bruijn Graph

SSRN

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SSRN 2024年

作者： Etzion, Tuvi Chee, Yeow Meng Nguyen, Tien Long Ta, Duy Hoang Tran, Vinh Duc Vu, Van Khu Dept. of Industrial Systems Engineering and Management National University of Singapore Singapore Computer Science Faculty Technion Israel Institute of Technology Haifa3200003 Israel Hanoi University of Science and Technology Viet Nam

To avoid a long period of no-pulse in a synchronized system for free-space quantum key distribution, a system based on a de Bruijn sequence was *** this system on-off pulse is used to simulate a \emph{zero} and on-on pulse is used to simulate a \emph{one}.However, these proposed sequences have high redundancy and low rate. To reduce the redundancy and increase the rate,run-length limited sequences in the de Bruijn graph are proposed in this work for the same *** maximum length of such sequences in the de Bruijn graph is studied and an efficient algorithm to construct a large set of these sequencesis presented. Based on known methods,an enumeration for the number of maximum length sequences is given. © 2024, The Authors. All rights reserved.

关键词： Quantum cryptography

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Maximum Length RLL Sequences in de Bruijn Graph

arXiv

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arXiv 2024年

作者： Chee, Yeow Meng Etzion, Tuvi Nguyen, Tien Long Ta, Duy Hoang Tran, Vinh Duc Vu, Van Khu Dept. of Industrial Systems Engineering and Management National University of Singapore Singapore Computer Science Faculty Technion Israel Institute of Technology Haifa3200003 Israel Hanoi University of Science and Technology Viet Nam

Free-space quantum key distribution requires to synchronize the transmitted and received signals. A timing and synchronization system for this purpose based on a de Bruijn sequence has been proposed and studied recently for a channel associated with quantum communication that requires reliable synchronization. To avoid a long period of no-pulse in such a system on-off pulses are used to simulate a zero and on-on pulses are used to simulate a one. However, these sequences have high redundancy and low rate. To reduce the redundancy and increase the rate, run-length limited sequences in the de Bruijn graph are proposed for the same purpose. The maximum length of such sequences in the de Bruijn graph is studied and an efficient algorithm to construct a large set of these sequences is presented. Based on known algorithms and enumeration methods, maximum length sequence for which the position of each window can be computed efficiently is presented and an enumeration on the number of such sequences is given. © 2024, CC BY.

关键词： Synchronization

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Strategies for Optimizing Time Series Visual Data Exploration

Strategies for Optimizing Time Series Visual Data Exploratio...

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ACS/IEEE International Conference on computer systems and Applications

作者： Heba Helal Mohamed A. Sharaf College of Information Technology United Arab Emirates University UAE Dept. of Computer Engineering and Systems College of Engineering Mansoura University Egypt

Dealing with high-dimensional time series data makes the process of recommending visualizations with "interesting" insights difficult. The challenge originates from finding a way to obtain the recommended visualizations efficiently without compromising their quality. Identifying such visualizations manually is considered a labor-intensive and time-consuming process. In response, this paper introduces different techniques designed to optimize the automated recommendation process. These techniques are entirely based on the concept of computation sharing and pruning. Furthermore, we provide a glimpse into our future research works in PhD thesis. The objective is to broaden the scope of our current work and enhance the generality of our problem statement.

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Multi-agent and Reinforcement Learning Schemes for Demand Response Estimation in Distributed Microgrids

Multi-agent and Reinforcement Learning Schemes for Demand Re...

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International Conference on Energy Conservation and Efficiency (ICECE)

作者： Muhammad Ikram Salman Ahmed Safdar Nawaz Khan Marwat Muhammad Nasir Dept. of Computer Systems Engineering University of Engineering and Technology Peshawar Pakistan Department of Physics Allama Iqbal Open University Islamabad Pakistan

Demand response (DR) is an approach that encourages consumers to shape consumption patterns in peak demands for the reliability of the power system and cost minimization. The optimal DR scheme has not only leverages the distribution system operators (DSOs) but also the consumers in the energy network. This paper introduced a multi-agent coordination control and reinforcement learning approach for optimal DR management. Each microgrid is considered an agent for the state and action estimation in the smart grid and programmed rewards and incentive plans. In this regard, the Multi-agent Markov game (MAMG) is utilized for the state and action. At the same time, the reward is articulated through reinforcement learning deep Q-network (DQN) and deep deterministic policy gradient (DDPG) schemes. The proposed DR model also encourages consumer participation for long-term incentivized benefits through integrating battery energy storage systems (BESS) in the SG network. The reliability of DQN and DDPG schemes is demonstrated and observed that the dynamically changing electricity cost is reduced by 19.86%. Moreover, the controllability of complex microgrids is achieved with limited control information to ensure the integrity and reliability of the network. The proposed schemes were simulated and evaluated in MATLAB and Python (PyCharm IDE) environments.

关键词： Costs Estimation Microgrids Reinforcement learning Mathematical models Power system reliability Smart grids

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Enhancing Eye Health Diagnosis through Deep Transfer Learning: Unveiling Insights from Low Quality Fundus Images

Enhancing Eye Health Diagnosis through Deep Transfer Learnin...

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IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： R. Sathishkumar T. Karthikeyan P. Praveen Kumar Chitra Rengarajan A. Tharagesh M. Govindarajan Dept. of CSE Manakula Vinayagar Institute of Technology Puducherry Dept. of Computer Science and Business Systems Sri Manakula Vinayagar Engineering College Puducherry Dept. of Information Technology Sri Manakula Vinayagar Engineering College Puducherry Centre for Agricultural Nanotechnology Tamil Nadu Agricultural University Tamil Nadu Dept. of CSE Annamalai University Chidambaram Tamil Nadu India

ISBN: (数字)9798331510022

ISBN: (纸本)9798331510039

Due to the frequency of eye illnesses, effective and precise diagnostic instruments are required. This work suggests an approach that uses low quality fundus images with deep transfer learning more precisely, the EfficientNetB0 architecture to improve eye health diagnosis. We tackle the problem caused by the quality of fundus photographs that are commonly found in clinical settings, which frequently display noise and abnormalities. Our methodology consists of pretraining the EfficientNetB0 model on a sizable dataset of excellent fundus photos, followed by fine-tuning it on a dataset of poor fundus photos. By employing this transfer learning technique, the model enhances its diagnostic capabilities by learning to identify significant features from the low-quality images. We ran tests on a variety of datasets that included fundus photos of varying degrees of deterioration in order to assess our approach. As compared to conventional techniques, the results reveal a significant improvement in diagnostic accuracy, demonstrating the effectiveness of deep transfer learning for improving eye health diagnosis from difficult fundus images. With fused features from MobileNet and DenseNet-121 models, the ANN specifically achieved accuracies of 98.5% for cataracts, 99.1% for diabetic retinopathy, 99% for glaucoma, and 99.5% for normal conditions.

关键词： Training Glaucoma Accuracy Image analysis Instruments Transfer learning Noise Imaging Artificial neural networks Retina

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Arabic Sentiment Analysis of Food Delivery Services Reviews

Arabic Sentiment Analysis of Food Delivery Services Reviews

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International Symposium on Networks, computers and Communications (ISNCC)

作者： Dheya Mustafa Safaa M. Khabour Ahmed S. Shatnawi Eyad Taqieddin Dept. of Computer Engineering Faculty of Engineering The Hashemite University Zarqa Jordan Dept. of Information Systems Faculty of Information Technology and Computer Sciences Yarmouk University Irbid Jordan Dept. of Software Engineering Jordan University of Science & Technology Irbid Jordan Dept. of Cyber Security School of Computing and Informatics Al-Hussein Technical University Amman Jordan

Customer reviews on online platforms have grown to become an important source of insight into a company's performance. Food delivery services (FDS) companies aim to effectively use customers' feedback to identify areas for improvement of customer satisfaction. Although Arabic is becoming one of the most widely used languages on the Internet, only a few studies have focused on Arabic sentiment analysis to date. The present study conducts an extensive emotion mining and sentiment analysis on FDS-related reviews in Arabic, exploiting natural language processing, and machine learning techniques to extract information that reflects customers' subjective viewpoints, recognize their feelings, and determine polarity in the FDS domain. This work begins with collecting the FDS dataset (Talabat), and then extracting and creating a dialects lexicon for Arabic dialects, followed by walking the reader through detailed steps of cleaning and pre-processing a manually annotated dataset. Finally, we examined classification algorithms including Decision Tree (DT), and Support Vector Machine (SVM). We achieved a maximum accuracy of about 82% using the SVM classifier.

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Simplicial Convolutional Filters

arXiv

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arXiv 2022年

作者： Yang, Maosheng Isufi, Elvin Schaub, Michael T. Leus, Geert Dept. of Intelligent Systems Delft University of Technology Netherlands Dept. of Computer Science RWTH Aachen University Germany Dept. of Microelectronics Delft University of Technology Netherlands

We study linear filters for processing signals supported on abstract topological spaces modeled as simplicial complexes, which may be interpreted as generalizations of graphs that account for nodes, edges, triangular faces, etc. To process such signals, we develop simplicial convolutional filters defined as matrix polynomials of the lower and upper Hodge Laplacians. First, we study the properties of these filters and show that they are linear and shift-invariant, as well as permutation and orientation equivariant. These filters can also be implemented in a distributed fashion with a low computational complexity, as they involve only (multiple rounds of) simplicial shifting between upper and lower adjacent simplices. Second, focusing on edge-flows, we study the frequency responses of these filters and examine how we can use the Hodge-decomposition to delineate gradient, curl and harmonic frequencies. We discuss how these frequencies correspond to the lower- and the upper-adjacent couplings and the kernel of the Hodge Laplacian, respectively, and can be tuned independently by our filter designs. Third, we study different procedures for designing simplicial convolutional filters and discuss their relative advantages. Finally, we corroborate our simplicial filters in several applications: to extract different frequency components of a simplicial signal, to denoise edge flows, and to analyze financial markets and traffic networks. © 2022, CC BY-SA.

关键词： Chebyshev polynomials

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Path-Integral Formula for Computing Koopman Eigenfunctions

Path-Integral Formula for Computing Koopman Eigenfunctions

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IEEE Conference on Decision and Control

作者： Shankar A. Deka Sriram S.K.S. Narayanan Umesh Vaidya Dept. of Electrical Engr. and Computer Science Decision and Control Systems division KTH Royal Institute of Technology Sweden Dept. of Mechanical Engr. Clemson University Clemson SC

The paper is about the computation of the principal spectrum of the Koopman operator (i.e., eigenvalues and eigenfunctions). The principal eigenfunctions of the Koopman operator are the ones with the corresponding eigenvalues equal to the eigenvalues of the linearization of the nonlinear system at an equilibrium point. The main contribution of this paper is to provide a novel approach for computing the principal eigenfunctions using a path-integral formula. Furthermore, we provide conditions based on the stability property of the dynamical system and the eigenvalues of the linearization towards computing the principal eigenfunction using the path-integral formula. Further, we provide a Deep Neural Network framework that utilizes our proposed path-integral approach for eigenfunction computation in high-dimension systems. Finally, we present simulation results for the computation of principal eigenfunction and demonstrate their application for determining the stable and unstable manifolds and constructing the Lyapunov function.

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Mitigating Insecure Outputs in Large Language Models(LLMs): A Practical Educational Module

Mitigating Insecure Outputs in Large Language Models(LLMs): ...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： MD Abdul Barek Md Mostafizur Rahman Shapna Akter A.B.M Kamrul Islam Riad Md Abdur Rahman Hossain Shahriar Akond Rahman Fan Wu Department of Intelligent Systems and Robotics University of West Florida USA Dept. of Cybersecurity and Information Technology University of West Florida USA Center for Cybersecurity University of West Florida USA Computer Science and Software Engineering Auburn University USA Dept. of Computer Science Tuskegee University USA

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Large Language Models (LLMs) have extensive ability to produce promising output. Nowadays, people are increasingly relying on them due to easy accessibility, rapid and outstanding outcomes. However, the use of these results without appropriate scrutiny poses serious security risks, particularly when they are integrated with other software, APIs, or plugins. This is because the LLM outputs are highly dependent on the prompts they receive. Therefore, it is essential to carefully clean these outputs before using them in additional software environments. This paper is designed to teach students about the potential dangers of contaminated LLM output within the context of web development through prelab, hands-on, and postlab experiences. Hands-on lab provides practical guidance on how to handle LLM vulnerabilities to make applications safe with some real-world examples in Python. This approach aims to provide students with a deeper understanding of the precautions necessary to ensure software against the vulnerabilities introduced by LLM output.

关键词： Training Navigation Large language models Computational modeling Software Security Software development management

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