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Fingerprint Agreement Using Enhanced Kerberos Authentication Protocol on M-Health

computer Systems science & engineering 2022年第11期43卷 833-847页

作者： A.S.Anakath S.Ambika S.Rajakumar R.Kannadasan K.S.Sendhil Kumar School of Computing E.G.S.Pillay Engineering CollegeNagapattinam611002India Department of Computer Science and Engineering University College of Engineering AriyalurAriyalur621705India Department of Mathematics University College of Engineering AriyalurAriyalur621705India Department of Software Systems School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014India Department of IoT School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014India

Cloud computing becomes an important application development platform for processing user data with high *** providers are accustomed to providing storage centers outside the trusted location preferred by the data ***,ensuring the security and confidentiality of the data while processing in the centralized network is very *** secured key transmission between the sender and the receiver in the network is a huge challenge in managing most of the sensitive data transmission among the cloud *** are very active over the network like real authenticated user to hack the personal sensitive data,such as bank balance,health data,personal data,and confidential documents over the cloud *** this research,a secured key agreement between the sender and the receiver using Kerberos authentication protocol with fingerprint is proposed to ensure security in *** of patients are monitored using wireless sensor devices and are then transferred to the *** protocol helps in avoiding unnecessary communication of authenticated data over the cloud *** security process is a procedure with the best security in most of the authentication *** node is responsible in carrying data packets from the sender to the receiver in the cloud *** Kerberos protocol is used in trust node to ensure *** communication between the local health center and the healthcare server is ensured by using a fingerprint feature called minutiae form,which refers to the fingerprint image of both sender and *** computational and communicational cost of the proposed system is lesser when compared with other existing authentication methods.

关键词： Protocol security m-health cloud computing biometric fingerprint kerberos protocol

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Comparative Study for Identifying and Categorizing DDoS Attacks 21

Comparative Study for Identifying and Categorizing DDoS Atta...

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21st International Learning and Technology Conference, L and T 2024

作者： Saad, Asaad B. Hossny, Eman Omara, Fatma A. Cairo University Faculty of Computers and Artificial Intelligence Software Engineering Department Cairo Egypt Cairo University Faculty of Computers and Artificial Intelligence Computer Science Department Cairo Egypt

ISBN: (纸本)9798350393569

Distributed Denial of Service, known as DDoS attacks, significantly compromise network security and availability. Certain DDoS detection methods utilize machine learning techniques, whereas others are based on statistical techniques. Therefore, this study provides a classification of the currently available DDoS detection techniques based on these two methodologies, strengths, and limitations. In addition, a comparative study of some DDoS detection techniques proposed in recent years is presented. We obtained similar results in related studies using different datasets. Thus, the compared DDoS techniques were dataset-independent. Finally, this study highlights areas for further research and improvement. © 2024 IEEE.

关键词： Network security

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A study on the impact of pre-trained model on Just-In-Time defect prediction 23

A study on the impact of pre-trained model on Just-In-Time d...

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23rd IEEE International Conference on software Quality, Reliability, and Security, QRS 2023

作者： Guo, Yuxiang Gao, Xiaopeng Zhang, Zhenyu Chan, W.K. Jiang, Bo Beihang University State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beijing China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China City University of Hong Kong Department of Computer Science Hong Kong

ISBN: (纸本)9798350319583

Previous researchers conducting Just-In-Time (JIT) defect prediction tasks have primarily focused on the performance of individual pre-trained models, without exploring the relationship between different pre-trained models as backbones. In this study, we build six models: RoBERTaJIT, CodeBERTJIT, BARTJIT, PLBARTJIT, GPT2JIT, and CodeGPTJIT, each with a distinct pre-trained model as its backbone. We systematically explore the differences and connections between these models. Specifically, we investigate the performance of the models when using Commit code and Commit message as inputs, as well as the relationship between training efficiency and model distribution among these six models. Additionally, we conduct an ablation experiment to explore the sensitivity of each model to inputs. Furthermore, we investigate how the models perform in zero-shot and few-shot scenarios. Our findings indicate that each model based on different backbones shows improvements, and when the backbone's pre-training model is similar, the training resources that need to be consumed are closer. We also observe that Commit code plays a significant role in defect detection, and different pre-trained models demonstrate better defect detection ability with a balanced dataset under few-shot scenarios. These results provide new insights for optimizing JIT defect prediction tasks using pre-trained models and highlight the factors that require more attention when constructing such models. Additionally, CodeGPTJIT and GPT2JIT achieved better performance than DeepJIT and CC2Vec on the two datasets respectively under 2000 training samples. These findings emphasize the effectiveness of transformer-based pre-trained models in JIT defect prediction tasks, especially in scenarios with limited training data. © 2023 IEEE.

关键词： Forecasting

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Roman Urdu Fake Reviews Detection Using Stacked LSTM Architecture

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SN computer science 2022年第6期3卷 470页

作者： Hayat, Umer Saeed, Ali Vardag, Muhammad Humayon Khan Ullah, Muhammad Farhat Iqbal, Nadeem Department of Software Engineering University of Lahore Lahore Pakistan Department of Software Engineering University of Central Punjab Lahore Pakistan Department of Computer Science and IT University of Lahore Lahore Pakistan

Fake reviews detection is a considerable challenge to the different e-commerce and online business settings. This task aims to develop such systems that could ensure the veracity of reviews. The research community has made a range of attempts to deal with this issue. But unluckily, these attempts were geared to only small set of languages like English, Arabic, and some others. In the subcontinent, Roman Urdu is being used on the web. It has not been explored thoroughly for this task, however. On the other hand, over the last few years, deep learning methods have proved very successful for the diverse Natural Language Processing tasks. But, deep learning methods have not been explored for the Roman Urdu fake review detection task. To address this gap, this study has rendered a two-fold contribution (1) Construction of a novel Roman Urdu Fake Reviews Detection Corpus (RU-FRDC) which composes 5150 annotated reviews and (2) Comparison of various deep learning architectures including Simple RNN, LSTM, GRU, Bi-LSTM, and Bi-GRU. The evaluation has been carried out using widely used evaluation measures, i.e., Precision, Recall, F₁, and ACC-ROC. The highest results were achieved using the stacked LSTM model (ACC - ROC = 0.943 and F₁= 0.88). © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Deep learning approaches Roman Urdu fake reviews detection Supervised learning approaches Word embeddings

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Enhancing Deep Reinforcement Learning with Scenario-Based Modeling

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SN computer science 2023年第2期4卷 1-13页

作者： Yerushalmi, Raz Amir, Guy Elyasaf, Achiya Harel, David Katz, Guy Marron, Assaf Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot 76100 Israel School of Computer Science and Engineering The Hebrew University of Jerusalem Jerusalem 91904 Israel Software and Information Systems Engineering Ben-Gurion University of the Negev Beer-Sheva 8410501 Israel

Deep reinforcement learning agents have achieved unprecedented results when learning to generalize from unstructured data. However, the “black-box” nature of the trained DRL agents makes it difficult to ensure that they adhere to various requirements posed by engineers. In this work, we put forth a novel technique for enhancing the reinforcement learning training loop, and specifically—its reward function, in a way that allows engineers to directly inject their expert knowledge into the training process. This allows us to make the trained agent adhere to multiple constraints of interest. Moreover, using scenario-based modeling techniques, our method allows users to formulate the defined constraints using advanced, well-established, behavioral modeling methods. This combination of such modeling methods together with ML learning tools produces agents that are both high performing and more likely to adhere to prescribed constraints. Furthermore, the resulting agents are more transparent and hence more maintainable. We demonstrate our technique by evaluating it on a case study from the domain of internet congestion control, and present promising results. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Deep reinforcement learning Domain expertise Machine learning Rule-based specifications Scenario-based modeling

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Static Eccentricity Fault Analysis in Three-Phase Induction Motors Using Current Signal 2

Static Eccentricity Fault Analysis in Three-Phase Induction ...

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2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2023

作者： Refaat, Shady S. Al-Shemmery, Ahmed Abdulmawjood, Kais Kameli, Sayed Mohammad Abuelrub, Abdelaziz Texas A&m University at Qatar Electrical and Computer Engineering Department Doha Qatar School of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom Ontario Tech University Department of Electrical Computer and Software Engineering Canada

ISBN: (纸本)9798350300802

Preventing mechanical faults in motors is often impossible, early detection of air gap eccentricity faults in induction motors is critical in preventing damage to the machine. Therefore, designing a reliable, effective fault detection system can help to improve its operation. This paper presents an analysis of static eccentricity fault for induction motors. This paper proposes the use of the empirical mode decomposition (EMD) followed by the implementation of wavelet packet decomposition (WPD) on current signals to extract and identify static eccentricity fault frequency signatures. The accuracy in fault detection and diagnosis of the effects of static airgap eccentricity using stator current based monitoring with WPD based on EMD is experimentally verified. © 2023 IEEE.

关键词： Airgap eccentricity fault empirical mode decomposition induction machine wavelet packet decomposition

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Staging of Different Tumor by Utilizing Laser Guidance (@405 nm) in CT Scan Images Along with Statistical Analysis

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Lasers in engineering 2025年第4-6期59卷 309-325页

作者： Amjad, M. Ullah, H. Siddique, M.A. Majid, M.A. Aleem, A. Akhtar, M. Gilanie, G. Abdullah-Al-Wadud, M. Farhan, M. Akram, A. Batool, Z. Nazir, A. Biophotonics Imaging Techniques Laboratory Institute of Physics The Islamia University of Bahawalpur 63100 Pakistan Department of Computer Science Faculty of Computing The Islamia University of Bahawalpur Bahawalpur Pakistan Dept. of Software Engineering College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia School of Earth Sciences and Engineering Hohai University Nanjing China

Early detection of lung cancer, liver cancer (HCC), and pancreatitis is crucial for effective treatment. This study assessed the use of laser guidance CT scans for diagnosis and staging. 26 patients of CT scan which were collected from BVH and civil hospital Bahawalpur, Pakistan. Visible light with a 405 nm wavelength is used. Results showed staging of lung cancer (2 at stage 1, 2 at stage 2, 3 at stage 4) and HCC (stages 1 to 4a). Pancreatic diseases detected included acute pancreatitis (44%), chronic pancreatitis (22%), gallstones (22%), and pancreatic tumors (11%). Alkaline phosphatase, SGOT, and blood urea levels were notably elevated in all three cancers compared to controls. CT scans show promise in identifying cancer stages and diagnosing pancreatitis, aiding in tailored treatment. Statistical analysis shows that alkaline phosphatase emerges as a potential biomarker for these conditions. ©2025 Old City Publishing, Inc.

关键词： Image analysis

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Identification and Visualization of Spatial and Temporal Trends in Textile Industry

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computers, Materials & Continua 2023年第2期74卷 4165-4181页

作者： Umair Yousaf Muhammad Asif Shahbaz Ahmed Noman Tahir Azeem Irshad Akber Abid Gardezi Muhammad Shafiq Jin-Ghoo Choi Habib Hamam Department of Computer Science National Textile UniversityFaisalabad38000Pakistan Department of Computer Science and Software Engineering International Islamic UniversityIslamabad44000Pakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea Faculty of Engineering Uni de MonctonMonctonNB E1A3E9Canada International Institute of Technology and Management Commune d’AkandaBPLibreville1989Gabon School of Electrical Engineering Department of Electrical and Electronic Eng.ScienceUniversity of JohannesburgJohannesburg2006South Africa Spectrum of Knowledge Production&Skills Development Sfax3027Tunisia

The research volume increases at the study rate,causing massive text *** to these enormous text corpora,we are drowning in data and starving for ***,recent research employed different text mining approaches to extract information from this text *** proposed approaches extract meaningful and precise phrases that effectively describe the text’s *** extracted phrases are commonly termed ***,these key phrases are employed to determine the different fields of study ***,these key phrases can also be used to determine the spatiotemporal trends in the various research *** this research,the progress of a research field can be better revealed through spatiotemporal bibliographic trend ***,an effective spatiotemporal trend extraction mechanism is required to disclose textile research trends of particular regions during a specific *** study collected a diversified dataset of textile research from 2011–2019 and different countries to determine the research *** data was collected from various open access ***,this research determined the spatiotemporal trends using quality *** research also focused on finding the research collaboration of different countries in a particular research *** research collaborations of other countries’researchers show the impact on import and export of those *** visualization approach is also incorporated to understand the results better.

关键词： Text mining spatiotemporal trend research collaboration

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Metamorphic Relation Patterns for Metamorphic Testing, Exploration and Robustness

Metamorphic Relation Patterns for Metamorphic Testing, Explo...

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作者： Ying, Zhihao Towey, Dave Bellotti, Anthony Chua, Caslon Quan Zhou, Zhi School of Computer Science University of Nottingham Ningbo China Zhejiang Ningbo China Department of Computer Science and Software Engineering Swinburne University of Technology HawthornVIC Australia School of Computing and Information Technology University of Wollongong WollongongNSW Australia

Metamorphic testing (MT) is an effective software quality assurance method;it uses metamorphic relations (MRs) to examine the inputs and outputs of multiple test cases. Metamorphic exploration (ME) and metamorphic robustness testing (MRT) are advanced additions to the MT literature: ME can enable better understanding, and thus testing, of systems;MRT can test software robustness without an oracle. Metamorphic relation patterns (MRPs) are abstractions or templates for multiple concrete MRs. The performance of MT/ME/MRT relies on the quality of MRs, but the identification of MRs is often a manual task requiring some knowledge of MRPs, creative thinking and a good understanding of the system. In other words, the effective identification of MRs remains a challenge and requires further study. In this paper, we propose formal definitions to describe the relationship between multiple MRPs in order to classify them. We also identify a series of new MRPs and propose a new MT framework that can guide the identification and application of MRPs. Based on our definitions, we present the notion of MRP family trees and further propose two trees by classifying previously published MRPs and our proposed MRPs, in order to make it easier for users to find their target MRPs for reuse, reference or inference. Finally, we report on case studies using the MRPs and our framework to guide the identification of MRs for MT/ME/MRT and successfully detect multiple violations. © 2025 John Wiley & Sons Ltd.

关键词： software testing

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Visualizing the Path of a Photo Taker from Image Metadata 4

Visualizing the Path of a Photo Taker from Image Metadata

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4th International Informatics and software engineering Conference, IISEC 2023

作者： Majid, Rasty Shakhawan Varol, Cihan Varol, Asaf Nasab, Ahad Firat University Department of Software Engineering Erbil Iraq Sam Houston State University Computer Science Department HuntsvilleTX United States College of Engineering and Computer Science Dept. of Engineering Management and Technology ChattanoogaTN United States

ISBN: (纸本)9798350318036

One of the most challenging investigations in forensic analysis is the work conducted on smartphones. Specifically using smartphone data to provide evidence for a case is becoming a norm nowadays. Many Android device applications use and work with location services that assist investigators in working with log files that store valuable information. Images captured on Android devices will save geolocation information, date, and time in the properties. In this work, a tool is developed to acquire the date and geolocation for each taken photo so that the path of the photo taker can be displayed on Google Maps. The work showed that the application can take about 4 and a half seconds to process four images and display the map to the investigator. © 2023 IEEE.

关键词： Metadata

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