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arXiv 2025年

作者： Saqib, Muhammad Mehta, Dipkumar Yashu, Fnu Malhotra, Shubham Dept. of Computer Science Texas Tech University LubbockTX United States C.K.Pithawalla College of Engineering and Technology Gujrat India Dept. of Computer Science Stony Brook University Stony BrookNY United States Dept. of Software Engineering Rochester Institute of Technology RochesterNY United States

The security of cloud environments, such as Amazon Web Services (AWS), is complex and dynamic. Static security policies have become inadequate as threats evolve and cloud resources exhibit elasticity [1]. This paper addresses the limitations of static policies by proposing a security policy management framework that uses reinforcement learning (RL) to adapt dynamically. Specifically, we employ deep reinforcement learning algorithms, including deep Q Networks and proximal policy optimization, enabling the learning and continuous adjustment of controls such as firewall rules and Identity and Access Management (IAM) policies. The proposed RL based solution leverages cloud telemetry data (AWS Cloud Trail logs, network traffic data, threat intelligence feeds) to continuously refine security policies, maximizing threat mitigation, and compliance while minimizing resource impact. Experimental results demonstrate that our adaptive RL based framework significantly outperforms static policies, achieving higher intrusion detection rates (92% compared to 82% for static policies) and substantially reducing incident detection and response times by 58%. In addition, it maintains high conformity with security requirements and efficient resource usage. These findings validate the effectiveness of adaptive reinforcement learning approaches in improving cloud security policy management. Copyright © 2025, The Authors. All rights reserved.

关键词： Reinforcement learning

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An Exploratory Study of ML Sketches and Visual Code Assistants

arXiv

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arXiv 2024年

作者： Gomes, Luís F. Hellendoorn, Vincent J. Aldrich, Jonathan Abreu, Rui Software and Societal Systems Dept. Carnegie Mellon University Pittsburgh United States INESC-ID Faculty of Engineering University of Porto Porto Portugal

This paper explores the integration of Visual Code Assistants in Integrated Development Environments (IDEs). In software engineering, whiteboard sketching is often the initial step before coding, serving as a crucial collaboration tool for developers. Previous studies have investigated patterns in SE sketches and how they are used in practice, yet methods for directly using these sketches for code generation remain limited. The emergence of visually-equipped large language models presents an opportunity to bridge this gap, which is the focus of our research. In this paper, we built a first prototype of a Visual Code Assistant to get user feedback regarding in-IDE sketch-to-code tools. We conduct an experiment with 19 data scientists, most of whom regularly sketch as part of their job. We investigate developers' mental models by analyzing patterns commonly observed in their sketches when developing an ML workflow. Analysis indicates that diagrams were the preferred organizational component (52.6%), often accompanied by lists (42.1%) and numbered points (36.8%). Our tool converts their sketches into a Python notebook by querying an LLM. We use an LLM-as-judge setup to score the quality of the generated code, finding that even brief sketching can effectively generate useful code outlines. We also find a positive correlation between sketch time and the quality of the generated code. We conclude the study by conducting extensive interviews to assess the tool's usefulness, explore potential use cases, and understand developers' needs. As noted by participants, promising applications for these assistants include education, prototyping, and collaborative settings. Our findings signal promise for the next generation of Code Assistants to integrate visual information, both to improve code generation and to better leverage developers' existing sketching practices. Copyright © 2024, The Authors. All rights reserved.

关键词： Codes (symbols)

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A Study of the Ecological Dynamics of Batumi, on the Black Sea Coast, Analyzing Environmental Factors and Their Impact

A Study of the Ecological Dynamics of Batumi, on the Black S...

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International Black Sea Conference on Communications and Networking (BlackSeaCom)

作者： Lily Petriashvili Irine Khomeriki Mzia Kiknadze Tamar Lominadze Nona Otkhozoria Dept. of Program Engineering Georgian Technical University Tbilisi Georgia Dept. of Interdisciplinary Informatics Georgian Technical University Tbilisi Georgia Dept. of Computer Engineering Georgian Technical University Tbilisi Georgia Dept. of Information Systems Georgian Technical University Tbilisi Georgia Dept. of Microprocessor and Measurement Systems Georgian Technical University Tbilisi Georgia

ISBN: (数字)9798350351859

ISBN: (纸本)9798350351866

This paper studies the complex ecological dynamics of Batumi on the Black Sea coast, through adetailed analysis of environmental factors and their impact. We use Business Intelligence (BI) methods to explore the complex interactions between natural and human impacts on the local ecosystems. By using data-focused approaches, including statistical analysis and predictive modeling, we aim to distinguish patterns and trends in ecological dynamics. This study aspires to make clear the complex relationships between environmental factors such as climate change, pollution levels, habitat degradation, and biodiversity loss, and their impacts on the coastal ecosystem of Batumi. Through this study, we aim to provide valuable information on sustainable management practices and conservation measures to protect the ecological integrity of this important coastal region.

关键词： Sea coast Pollution Statistical analysis Ecosystems Habitats Sea measurements Predictive models

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SWIN and Vision Transformer-Driven Crack Detection in the Al Qattara Oasis, UAE: Towards Sustainable Infrastructure Management

SWIN and Vision Transformer-Driven Crack Detection in the Al...

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IEEE/ACM International Symposium on Big Data Computing (BDC)

作者： Luqman Ali Medha Mohan Ambali Parambil Muhammed Swavaf Fady Alnajjar Hamad Aljassmi Adriaan De Man Dept. Computer Science and Software Engineering Emirates Centre for Mobility Research United Arab Emirates University Al Ain UAE Dept. Computer Science and Software Engineering United Arab Emirates University Al Ain UAE Dept. Civil and Enviromental Engieering Engieering Emirates Centre for Mobility Research Al Ain UAE Dept. Tourism and Heritage United Arab Emirates University Al Ain UAE

ISBN: (数字)9798350367300

ISBN: (纸本)9798350367317

Heritage sites are central to the cultural identity and historical narrative of a community. The Al Qattara Oasis, located in the United Arab Emirates (UAE), illustrates this function well. This study addresses the pressing need to preserve and maintain built heritage by employing modern technological solutions for infrastructure upkeep. Specifically, it focuses on crack detection, a critical aspect of ensuring the structural integrity of heritage buildings. Utilizing data collected from various structures across the UAE, obtained through handheld cameras, the effectiveness of Vision Transformers (ViTs) and Swin Transformers in identifying cracks within Al Qattara is assessed. The research thoroughly evaluates models, with particular attention to different input patch sizes. Through systematic experimentation and analysis over 100 epochs, ViT models with a patch size 16 exhibit significant promise in crack detection. Notably, the ViT-16 model achieves good performance metrics, including training and validation accuracies of 85% and (82%) respectively, and correctly classifies 791 out of 957 cracks and 772 out of 903 non-cracks. In contrast, Swin Transformers show lower validation accuracies (70-74%) and higher misclassification rates. The outcomes underscore the potential of ViT models in enhancing infrastructure maintenance efforts within heritage sites like Qattara Oasis. By combining advanced technology with a profound respect for historical preservation, this study aims to contribute to the sustainable conservation and protection of cultural heritage, ensuring that future generations can continue to appreciate the enduring legacy of sites such as Qattara Oasis.

关键词： Training Measurement computer vision Accuracy Systematics Pressing Transformers Maintenance Cultural differences Protection

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Intrusion Detection System (IDS) of Multiclassification IoT by using Pipelining and an Efficient Machine Learning

Intrusion Detection System (IDS) of Multiclassification IoT ...

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International Conference on engineering and Emerging Technologies (ICEET)

作者： Layth Rafea Hazim Abdulrahman Ahmed Jasim Oguz Ata Muhammad Ilyas College of Computer Science and Mathematics Tikrit University Tikrit Iraq Dept. of Electrical and Computer Engineering Altinbas University Istanbul Turkey College of Engineering Al-Iraqia University Baghdad Iraq Dept. of Software Engineering Altinbas University Istanbul Turkey Dept. of Computer Engineering Altinbas University Istanbul Turkey

ISBN: (数字)9798350316926

ISBN: (纸本)9798350316933

The Internet of Things (IoT) has quickly advanced and been incorporated into many different fields. With the use of IoT technology, gadgets can receive, process, and send data automatically. IoT has been rapidly accepted in many important fields since it makes life easier and increases service quality, yet it still faces significant privacy and security problems. An Intrusion Detection System (IDS) could be implemented as a security feature to protect IoT networks from a variety of cyberattacks. This study suggests using IDS to defend against a wide range of cyberattacks on IoT systems. The suggested approach makes use of the Multi-layer Perceptron (MLP) as well as Extra Trees (ExT) as efficient algorithms of classification. Also, the study uses the pipeline to put together several cross-validated phases while selecting various parameters to increase the detection rate. One dataset is utilized for evaluating and analyzing the performance outcomes so as to validate the efficiency of the suggested IDS approach. The evaluation findings show that the suggested IDS methods may greatly increase detection performance results concerning accuracy rate, precision, F1-score, and recall while also improving detection efficiency.

关键词： Measurement Privacy Correlation Redundancy Intrusion detection Machine learning Security

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LoRaWAN Scheduling Mechanism for 6G-Based LEO Satellite Communications

LoRaWAN Scheduling Mechanism for 6G-Based LEO Satellite Comm...

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IEEE Conference on Vehicular Technology (VTC)

作者： Abhijeet Manoj Varma Nikumani Choudhury Jay Dave Anakhi Hazarika Moustafa M. Nasralla Dept. of Computer Science & Information Systems Birla Institute of Technology & Science Pilani Hyderabad India Dept. of Electrical & Electronics Engineering Birla Institute of Technology & Science Pilani Hyderabad India Dept. of Communications & Networks Engineering Smart Systems Engineering Lab Prince Sultan University Riyadh Saudi Arabia

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

As the Internet of Things (IoT) is poised to become a global phenomenon, it is imperative to schedule the transmissions of IoT devices effectively and in a fair way. Leveraging Long Range (LoRa) technology, we can achieve transmissions that consume minimal power while covering vast distances, aligning with the requirements of IoT devices. However, the proximity of multiple devices within the same area often leads to packet interference and collisions. To address this, our study introduces a pioneering scheduling method utilizing a constellation of Low Earth Orbit (LEO) satellites to manage and streamline the transmission of data from End Devices (EDs). This method employs two LEO satellites: the first satellite assigns the sequence for EDs to dispatch their packets, and the second collects these packets in the predetermined sequence before forwarding them to the LoRa Network Server (LNS). For urgent (URG) communications, EDs can alert the first satellite, which then coordinates with the LNS to schedule these priority transmissions. The LNS generates a schedule that is relayed to the second satellite, informing EDs with URG packets of their specific transmission times and channels. This scheduling approach is designed to optimize channel usage effectively while accommodating the transmission of urgent data.

关键词： 6G mobile communication Schedules Vehicular and wireless technologies Satellites Scheduling algorithms Low earth orbit satellites LoRaWAN

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Automatic Network Intrusion Detection System Using Machine Learning and Deep Learning

Automatic Network Intrusion Detection System Using Machine L...

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Artificial Intelligence and Mechatronics systems (AIMS), International Conference on

作者： Mohammed Mynuddin Sultan Uddin Khan Zayed Uddin Chowdhury Foredul Islam Md Jahidul Islam Mohammad Iqbal Hossain Dewan Mohammed Abdul Ahad Dept. of Electrical Engineering North Carolina A & T State University Data Scientist Data Bid Machine Inc. Associate Power Systems Engineer-II Open Systems International Inc. Dept. of Electrical Engineering Tuskegee University Dept. of Electrical and Computer Engineering University of North Carolina at Charlotte

In recent years, the popularity of network intrusion detection systems (NIDS) has surged, driven by the widespread adoption of cloud technologies. Given the escalating network traffic and the continuous evolution of cyber threats, the need for a highly efficient NIDS has become paramount for ensuring robust network security. Typically, intrusion detection systems utilize either a pattern-matching system or leverage machine learning for anomaly detection. While pattern-matching approaches tend to suffer from a high false positive rate (FPR), machine learning-based systems, such as SVM and KNN, predict potential attacks by recognizing distinct features. However, these models often operate on a limited set of features, resulting in lower accuracy and higher FPR. In our research, we introduced a deep learning model that harnesses the strengths of a Convolutional Neural Network (CNN) combined with a Bi-directional LSTM (Bi-LSTM) to learn spatial and temporal data features. The model, evaluated using the NSL-KDD dataset, exhibited a high detection rate with a minimal false positive rate. To enhance accuracy, K-fold cross-validation was employed in training the model. This paper showcases the effectiveness of the CNN with Bi-LSTM algorithm in achieving superior performance across metrics like accuracy, F1-score, precision, and recall. The binary classification model trained on the NSL-KDD dataset demonstrates outstanding performance, achieving a high accuracy of 99.5% after 10-fold cross-validation, with an average accuracy of 99.3%. The model exhibits remarkable detection rates (0.994) and a low false positive rate (0.13). In the multiclass setting, the model maintains exceptional precision (99.25%), reaching a peak accuracy of 99.59% for $\text{k-value} =10$ . Notably, the Detection Rate for $\text{k-value}=10$ is 99.43%, and the mean False Positive Rate is calculated as 0.214925.

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A Study on Traceable Group Signature Scheme for Blockchain

A Study on Traceable Group Signature Scheme for Blockchain

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Information and Network Technologies (ICINT), International Conference on

作者： Hyo-Jin Song Im-Yeong Lee Dept. of Software Convergence Soonchunhyang Univ. Asan-si 31538 Republic of Korea Dept. of Computer Software Engineering Soonchunhyang Univ. Asan-si 31538 Republic of Korea

A blockchain is a decentralized database system in which a ledger containing transactions is stored and maintained identically by all through consensus among network participants without a central server. Instead of having a central server, network participants make sure that everyone stores and maintains the same ledger containing transactions through consensus. Integrity and reliability of the data stored in the blockchain are guaranteed, but on the other hand, privacy issues may arise. The pseudonymity of the public key reused in transactions causes a privacy invasion of the user’s behavioral pattern, asset size, and offline identity. Therefore, instead of assigning unique public keys to everyone, they are provided through a single signature in a blockchain environment. It can also be described as a method for ensuring anonymity by having members of the same group use the same public key in a transaction while employing the group signature, which has been studied in this paper. This paper defines the key used for group signature is defined as a composition of a “group private key” and a “partial key”. Mainly among them, we consider the leakage of the partial key. In the proposed scheme, it is possible to trace the leaker and the signer from the signature generated by the outsider with the leaked partial key. In this paper, we provide a secure traceable group signature scheme to cope with the leakage of the group signing key.

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Trusted Access to 6G Testbeds Through a Security Intent-Driven software-Defined Perimeter Framework 29

Trusted Access to 6G Testbeds Through a Security Intent-Driv...

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29th IEEE International Workshop on computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2024

作者： Fernandez-Martinez, Carolina Bikos, Anastasios Verikoukis, Christos Siddiqui, Shuaib i2CAT Foundation Barcelona08034 Spain Universitat Pompeu Fabra Dept. of Information and Communication Technologies Barcelona08018 Spain Iquadrat Informatica Sl Barcelona08006 Spain Universitat Politècnica de Catalunya Dept. of Signal Theory and Communications Barcelona08034 Spain Industrial Systems Institute Athena Research Center Patras26504 Greece University of Patras Dept. of Computer Engineering and Informatics Patras26504 Greece

ISBN: (纸本)9798350377644

Parallel to the evolution of recent trends in the cybersecurity industry and the increase of cyberattacks in the last few years, there is renovated interest on the application of software-defined techniques to enforce best security practices, such as in the software-Defined Perimeter specification and the Zero Trust architectures. This work proposes a software-defined network segmentation and access control framework aligned with these principles. This solution captures minimal security requirements from testbed operators to establish ad-hoc, isolated connectivity and access control for end-users (experimenters) interacting with exposed endpoints from the exposed services in the cloud testbeds. The elicited architecture, design decision and initial implementation are introduced. © 2024 IEEE.

关键词： Testbeds

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Data Security Enhancement in Cloud Computing by Proposing A DKE Encryption Protocol 23

Data Security Enhancement in Cloud Computing by Proposing A ...

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Proceedings of the 2023 International Conference on Advances in Artificial Intelligence and Applications

作者： Sahar Ebadinezhad Halmat Ayub Abdulmajed Department of Computer Information Systems Near East University North Cyprus and Computer Information Systems Research and Technology Center (CISRT) Near East University North Cyprus Dept. Engineering and Computer Systems Lebanese French University (LFU) Iraq

ISBN: (纸本)9798400708268

This study uses cryptography to tackle the important problem of data security in cloud computing. Two keys are used in the Dual Key Encryption (DKE) method for both encryption and decryption. DKE employs a public key for the first encryption round before cloud upload and a user-only private key for the second round of encryption. Decryption operates oppositely. When tested and simulated with different file sizes on a CloudAnalyst simulator, DKE operates faster and more efficiently than cryptographic methods such as Triple DES (3DES), AES, RSA, and DES. Thanks to developments in information technology, cloud computing has made several services available online. Data security assurance is still very difficult to achieve, nevertheless. In this context, cryptography is essential and has led to the creation of the novel DKE technology. This technology is not only far more efficient than well-known cryptographic techniques such as 3DES, but it also improves data security.

关键词： Cloud Services Cryptography Data Integrity Data Security Dual Key Encryption

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