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Evaluating the Impact of ChatGPT on Exercises of a Software Security Course 17

Evaluating the Impact of ChatGPT on Exercises of a Software ...

引用

17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023

作者： Li, Jingyue Meland, Per Hakon Notland, Jakob Svennevik Storhaug, Andre Tysse, Jostein Hjortland Dept. of Computer Science Trondheim Norway Ntnu Dept. of Computer Science Trondheim Norway

ISBN: (纸本)9781665452236

Along with the development of large language models (LLMs), e.g., ChatGPT, many existing approaches and tools for software security are changing. It is, therefore, essential to understand how security-aware these models are and how these models impact software security practices and education. In exercises of a software security course at our university, we ask students to identify and fix vulnerabilities we insert in a web application using state-of-the-art tools. After ChatGPT, especially the GPT-4 version of the model, we want to know how the students can possibly use ChatGPT to complete the exercise tasks. We input the vulnerable code to ChatGPT and measure its accuracy in vulnerability identification and fixing. In addition, we investigated whether ChatGPT can provide a proper source of information to support its outputs. Results show that ChatGPT can identify 20 of the 28 vulnerabilities we inserted in the web application in a white-box setting, reported three false positives, and found four extra vulnerabilities beyond the ones we inserted. ChatGPT makes nine satisfactory penetration testing and fixing recommendations for the ten vulnerabilities we want students to fix and can often point to related sources of information. © 2023 IEEE.

关键词： Students

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Enhancing Academic Feedback Systems with Deep Learning and Ensemble Methods 1

Enhancing Academic Feedback Systems with Deep Learning and E...

引用

1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Sharma, Hemant Joshi, Hiren Gujarat University Dept. Computer Science Ahmedabad India

ISBN: (纸本)9798331518578

This paper attempts to improve the academic feedback systems via complex deep learning and ensemble methods. Leveraging the NIRF Rankings 2022 dataset that provides radical performance metrics of Indian academic institutions, the project would attempt to develop trustworthy models to monitor and facilitate improvement in the academic feedback system. The techniques used in data preparation prevent missing values, outliers, and categorical data in using advanced machine learning models. In order to construct the model and capture fine-grained patterns linked to academic achievement, 1D Convolutional Neural Networks (CNNs) along with Multi-Layer Perceptrons (MLPs), both individually and in combination, are employed extrapolated from the National Institutional Ranking Framework to obtain data. Precision, accuracy, recall, along with the F1-score will be used to evaluate these models' performance. By the time these findings are finished, they should be able to provide practical advice on how to improve academic evaluations' effectiveness and advance educational institutions' more flexible feedback systems. © 2025 IEEE.

关键词： Contrastive Learning

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Bioacoustics for North Atlantic Right Whale Detection Based on Deep Learning

Bioacoustics for North Atlantic Right Whale Detection Based ...

引用

OCEANS 2024 - Halifax, OCEANS 2024

作者： Blais, Marc-André Akhloufi, Moulay A. Dept. of Computer Science MonctonNB Canada

ISBN: (纸本)9798331540081

Climate change, pollution, shipping lanes and other man-made factors are significantly impacting the biodiversity of our planet. Whales represent some of the most endangered animals of our time with some species, such as the North Atlantic right whales, have fewer than 400 individuals left. These large mammals play a crucial role in maintaining the health of our planet due to their various attributes, such as their carbon sequestration abilities. Detecting, classifying and tracking these whales can provide us with tools for their management. Passive acoustic monitoring allows researchers to identify whales through audio recordings based on their unique sounds. We propose detecting North Atlantic right whales using passive acoustic monitoring audio clips. Our data consists of whale upcalls collected in the Gulf of St. Lawrence and the Gulf of Maine. In our work, we compare various audio visualization transformations such as the wavelet transformation, Short-Time Fourier Transform and a custom algorithm. Using the visualized audio, our goal is to use various deep learning algorithms to detect whales. We employed multiple pre-trained convolutional neural network algorithms, including DenseNetl21, EfficientNetB7 and Xception. the wavelet transformation achieved the best overall results with a validation accuracy of 90% on most detection algorithms. Specifically, DenseNet169 combined with the wavelet transformation achieved the highest accuracy of 90.39%. Using ensemble learning on the best performing algorithms, we increased the accuracy of our approach to 91.86 %. Overall, our results demonstrate the strong potential of using audio visualization with deep learning algorithms to detect North Atlantic right whales. Further work in this field, such as exploring more algorithms, could further enhance the effectiveness of our approach. © 2024 IEEE.

关键词： Invertebrates

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Bad Neighbors? On the Impact of IEEE 802.11p and Cellular 5G on Vehicular Neighbor Sets

Bad Neighbors? On the Impact of IEEE 802.11p and Cellular 5G...

引用

2024 IEEE International Performance, Computing, and Communications Conference, IPCCC 2024

作者： Welzel, Simon Klingler, Florian TU Ilmenau Dept. of Computer Science Germany

ISBN: (纸本)9798350367942

In vehicular networks, information about the surroundings is of crucial importance. There are various applications that rely on information about a vehicle's neighboring vehicles, such as autonomous and teleoperated driving, platooning and message forwarding being some of them. While maintaining an overview of vehicles in direct communication range via beaconing is a well-explored concept, recent works have shown that collecting the neighbor information of direct neighbors, which are the neighbor's neighbors, is beneficial for certain applications. This data can be aggregated to the so-called two-hop neighbor set. Creating an accurate two-hop neighbor set is, however, a difficult task, as information is quickly outdated due to the mobility of vehicles and delays of data transmission. While previous work has used mainly ad-hoc communication, this work introduces a central vision utilizing 5G cellular communication to improve the freshness of neighbor data. We conduct a first simulation study to compare the performance of our centralized approach to a purely ad-hoc approach and present the results in this poster paper. We conclude with an outlook to future research directions. In future work, a deeper investigation of potential optimizations and challenges will be conducted. © 2024 IEEE.

关键词： 5G mobile communication systems

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TEST-Web: An Automated Web Application Testing Tool for Enhanced Efficiency and Consistency 3

TEST-Web: An Automated Web Application Testing Tool for Enha...

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Verma, Ishaan Wason, Ritika Arora, Parul Dept. of Computer Science and Applications Delhi India

ISBN: (纸本)9798331518592

This manuscript specifies the development of TEST-Web an automated testing tool projected to evolve the efficacy and reliability of web application testing process. Using the Selenium WebDriver and the TestNG framework, TEST-Web restructures the testing process by automating repetitive and comprehensive testing in large organizations. The tool generates detailed reports, providing valued visions into application performance and functionality. TEST-Web development follows an iterative approach, beginning with prototype development and then expanding functionality through user feedback. This work aims to achieve a user-friendly and robust solution for enhancing the accuracy, speed, and reliability of web application testing processes. © 2024 IEEE.

关键词： Automated Testing Tool Software Testing TestNG Web Application Testing

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Quantum Network Routing with Heterogeneous Nodes 17

Quantum Network Routing with Heterogeneous Nodes

引用

17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Pandey, Anoop Kumar Tamma, Bheemarjuna Reddy Rao, M.V. Panduranga IIT Hyderabad Dept. of Computer Science and Engineering India

ISBN: (纸本)9798331531195

Deciding a route for the transfer of quantum information (namely, qubits) on a quantum network is a significant problem that is being studied extensively. In this work, we investigate the problem of routing on a quantum network of heterogeneous nodes both with and without fidelity and timing *** propose a Path Request Packet (PRP) based routing scheme for dynamically selecting a path that maximizes the overall probability of transmission success while maintaining fidelity above a threshold and adhering to time constraints. While the proposed scheme can perform suboptimally under fidelity and timing constraints, we discuss a straightforward proof of optimality in the absence of these constraints. Simulations on random graphs demonstrate that the PRP-based scheme performs better, both in terms of reliability and fidelity, than a non-trivial baseline routing algorithm. © 2025 IEEE.

关键词： Quantum electronics

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Leveraging AI-Generated Image for Scene Classification: A transfer Learning Approach 11

Leveraging AI-Generated Image for Scene Classification: A tr...

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Khan, Seher Singh, Krishna Kumar Symbiosis Centre for Information Technology Dept. of Data Science and Data Analytics Pune India

ISBN: (纸本)9798350350357

When it comes to scene classification, the lack of labelled data is a significant obstacle that forces researchers to think about innovative solutions. This work presents a revolutionary method to strengthen scene classification models by combining transfer learning with AI-generated images. A key component of this project is the construction of a carefully curated dataset of 3672 augmented AI-generated photos in a total of 6 scenes. This database not only serves as a helpful resource for additional research but also makes a substantial contribution to this area of research. Using this dataset, a VGG16 model is trained, demonstrating the usefulness of synthetic data with a notable increase in accuracy. The model's performance is further improved through subsequent training using realistic photos through transfer learning, thereby surpassing the initial baseline. This work demonstrates the transformative effect of transfer learning on scene categorization accuracy and verifies its effectiveness using synthetic data through rigorous testing and evaluation. The results open the door for AI-generated photos to be used as an effective approach to address data scarcity issues in scene classification, which will help real-world applications improve. © 2024 IEEE.

关键词： computer vision

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NFT Marketplace: What are NFTs, and how does OpenSea succeed in acquiring the most of the NFT Space 1

NFT Marketplace: What are NFTs, and how does OpenSea succeed...

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1st IEEE Karachi Section Humanitarian Technology Conference, Khi-HTC 2024

作者： Thakur, Anil Divya, K. Verma, Sahil Kaur, Maninder Chandigarh University Dept. of Computer Science & Engineering Mohali India Uttaranchal University Dept. of Computer Science & Engineering Dehradun India Guru Gobind Singh College for Women Dept. of Computer Science & Applications Chandigarh India

ISBN: (纸本)9798350373042

Nowadays, the world is becoming smarter, so as the technology, the new era is on the boom, which is blockchain because of its different use cases and benefits. The blockchain is a growing list of records called blocks that are linked together with the use of cryptography. Because all servers on a network are corresponding and a significant concern in the types of network style, its data sources are managed through a peer-to-peer (p2p) network. The servers engage in negotiation and communication through the agreement method. The dispersed network is a network system in which information, software application, and computer system programs are spread out on greater than one node (computer systems). These nodes also depend on each other. It is only a p2p network that gets rid of a solitary factor of failing. It is a decentralized, dispersed, and unalterable journal to show electronic purchases. One of the concepts of blockchain is NFTs. These are digital assets with a unique identity and cannot be replicated. They can be used for a variety of purposes, such as in-game items, digital collectibles, or even to represent real-world assets like cars or houses. They can represent any digital asset or physical goods. NFTs can represent ownership and authenticity of any type of digital asset or physical goods. They can also represent a stake in the game, such as ownership in a casino or a share in a company. © 2024 IEEE.

关键词： Smart contract

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Do large language models and humans have similar behaviors in causal inference with script knowledge? 13

Do large language models and humans have similar behaviors i...

引用

13th Joint Conference on Lexical and Computational Semantics, StarSEM 2024

作者： Hong, Xudong Ryzhova, Margarita Biondi, Daniel Adrian Demberg, Vera Dept. of Computer Science Saarland University Germany Dept. of Language Science and Technology Saarland University Germany

ISBN: (纸本)9798891761063

Recently, large pre-trained language models (LLMs) have demonstrated superior language understanding abilities, including zero-shot causal reasoning. However, it is unclear to what extent their capabilities are similar to human ones. We here study the processing of an event B in a script-based story, which causally depends on a previous event A. In our manipulation, event A is stated, negated, or omitted in an earlier section of the text. We first conducted a self-paced reading experiment, which showed that humans exhibit significantly longer reading times when causal conflicts exist (¬A → B) than under logical conditions (A → B). However, reading times remain similar when cause A is not explicitly mentioned, indicating that humans can easily infer event B from their script knowledge. We then tested a variety of LLMs on the same data to check to what extent the models replicate human behavior. Our experiments show that 1) only recent LLMs, like GPT-3 or Vicuna, correlate with human behavior in the ¬A → B condition. 2) Despite this correlation, all models still fail to predict that nil → B is less surprising than ¬A → B, indicating that LLMs still have difficulties integrating script knowledge. Code and data are available at https://***/tony-hong/causal-script. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Forecasting Traffic Air Pollution Increases from Urban Transportation Using Machine Learning in Metropolitan Cities-A Review 4

Forecasting Traffic Air Pollution Increases from Urban Trans...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Bhaskar, Hari Naga Vijaya Mayil, V. Valli KL University Dept. of Computer Science and Applications India

ISBN: (纸本)9798331523923

Rapid urban growth and industrial expansion in Indian cities have led to a 30% increase in vehicles over the past 5-10 years, causing a rise in air pollution and health risks. Existing methods to predict air quality face challenges like limited data, inaccurate models, slow predictions, and changing environmental conditions. This review explores how machine learning, including deep learning and hybrid models, can improve pollution forecasting. It also highlights issues such as unreliable sensors, high computing costs, and difficulty in understanding model results. Finally, the study suggests future directions for better air quality management using AI-driven predictions and policy improvements. © 2025 IEEE.

关键词： Air Pollution Forecasting Environmental Impact Machine Learning Metropolitan Cities Public Health Urban Transportation

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