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Optimizing User Data Privacy and Confidentiality in Cloud Storage systems Through Advanced Obfuscrypt Encryption Methods for Enhanced Security and Efficient Data Protection

Optimizing User Data Privacy and Confidentiality in Cloud St...

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2024 IEEE International Conference on Recent Advances in Science and engineering Technology, ICRASET 2024

作者： Ramesh, P.S. Sudha, I. Jagannathan, J. Pandiarajan, Rajkumar Ponmalar, A. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India Kalasalingam Academy Of Research and Education School of Computing Department of Information and Technology Krishnankoil Virudhunagar India R.M.K. Engineering College Tamilnadu Chennai India

ISBN: (纸本)9798350388602

With a steady increase in the adoption of cloud storage systems, the client's data are at risk of being leaked. There are several methods of encrypting data which are quite useful but they lack some of the features of today's sophisticated threats. The methodology used in this research propose an encryption framework known as Obfuscrypt to improve the issues of data privacy as well as confidentiality of data stored in cloud storage systems. Obfuscrypt uses conventional encryption strategies incorporated with obfuscation and post-quantum cryptographic algorithms to provide a complex security plan immune to classic and quantum approaches. Some of the proposed other innovations include the decentralised key management with multi-factor authentication and RBAC-ABE as the fine-grained access control techniques. These features make it possible for only the authorized personnel to be in a position to be in a position of decrypting and retrieving the stored data thereby minimizing the possibility of the data being accessed by unauthorized people. The work also considers the issue of performance efficiency of the cloud storage systems. Similar to other symmetric encryption programs, Obfuscrypt uses light encryption algorithms and brings in to play the hardware acceleration so that it may infuse lesser computational overhead in the process of encryption and decryption. As can be clearly seen from the results, the actual work proves that the proposed framework not only offers a higher level of security but does not affect the system performance to a great extent. Also, the study addresses the post-quantum cryptographic algorithm for making the system resistant to an attack that can be posed by quantum computing systems. With the help of these improved algorithms, Obfuscrypt guarantees the permanent data security in the world of constantly emerging cyber threats. © 2024 IEEE.

关键词： Data obfuscation

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RAT: A Refactoring-Aware Tool for Tracking Code History 24

RAT: A Refactoring-Aware Tool for Tracking Code History

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46th International Conference on software engineering: Companion, ICSE-Companion 2024

作者： Niu, Feifei Shao, Junqian Xu, Chaofan Mayr-Dorn, Christoph Assunção, Wesley K. G. Huang, Liguo Li, Chuanyi Ge, Jidong Luo, Bin Egyed, Alexander State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Institute for Software Systems Engineering Johannes Kepler University Linz Austria Department of Computer Science North Carolina State University North Carolina United States Department of Computer Science and Engineering Southern Methodist University DallasTX United States

ISBN: (纸本)9798400705021

History of code elements is essential for software maintenance tasks. However, code refactoring is one of the main causes that makes obtaining a consistent view on code evolution difficult as renaming or moving source code elements break such history. To this end, this paper presents RAT, a refactoring-aware tool for keeping track of code elements evolution across time, not just in terms of revisions but also in terms of refactoring. This is the first tool that enables fine-grained code element traceability of the whole repository. Empirical evaluation of leveraging our tool in three bug localization techniques relying on code history shows significant improvement in localization accuracy. Based on our findings, we believe that many of the state-of-the-art approaches using past source code data would benefit from our tool. Demo Tool: https://***/feifeiniu-se/RAT-Demo. Demo Video: https://***/VI-xwUaIPp4. © 2024 IEEE Computer Society. All rights reserved.

关键词： Rats

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Data Trading and Monetization: Challenges and Open Research Directions 23

Data Trading and Monetization: Challenges and Open Research ...

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Proceedings of the 7th International Conference on Future Networks and Distributed systems

作者： Qusai Ramadan Zeyd Boukhers Muath Alshaikh Christoph Lange Jan Jurjens Institute of Software Engineering University of Koblenz Germany Fraunhofer Institute for Applied Information Technology FIT Germany and University Hospital of Cologne Germany College of Computing and Informatics Saudi Electronic University Kingdom of Saudi Arabia Fraunhofer Institute for Applied Information Technology FIT Germany and RWTH Aachen University Germany University of Koblenz Germany and Fraunhofer-Institute for Software and Systems Engineering ISST Germany

ISBN: (纸本)9798400709036

Traditional data monetization approaches face challenges related to data protection and logistics. In response, digital data marketplaces have emerged as intermediaries simplifying data transactions. Despite the growing establishment and acceptance of digital data marketplaces, significant challenges hinder efficient data trading. As a result, few companies can derive tangible value from their data, leading to missed opportunities in understanding customers, pricing decisions, and fraud prevention. In this paper, we explore both technical and organizational challenges affecting data monetization. Moreover, we identify areas in need of further research, aiming to expand the boundaries of current knowledge by emphasizing where research is currently limited or lacking.

关键词： Data Exchange

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Advanced Machine Learning Algorithms for 1Predictive Analytics in Healthcare to Enhance Patient Outcomes with Data-Driven Insights

Advanced Machine Learning Algorithms for 1Predictive Analyti...

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2024 IEEE International Conference on Recent Advances in Science and engineering Technology, ICRASET 2024

作者： Pandiarajan, Rajkumar Jagannathan, J. Ramesh, P.S. Ponmalar, A. Sudha School of Computing Kalasalingam Academy Of Research and Education Department of Information and Technology Krishnankoil Virudhunagar India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India R.M.K. Engineering College Tamilnadu Chennai India Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350388602

This research aims to explore the use of modern complex defensive machine learning algorithms in the provision of predictive analytics for health improvement. Incorporating electronic health records, medical image information, and genomic data the work proposes and assesses multiple machine learning models including deep learning, ensemble learning, and reinforcement learning. The main findings shown very high performance in disease prediction, in chronic illness and in the application of efficiency improvements in hospitals as a whole. Overall, such threats as data quality, data privacy, and model interpretability have been discussed in the research and emphasize the importance of the machine learning approach in healthcare. It is highlighted that further development and integration of the interdisciplinary approaches as well as the use of the transparent and interpretable artificial intelligence and machine learning models can be urgent to increase the acceptance among the healthcare staff. This paper enhances the literature on applying machine learning in healthcare systems adding to the repertoire of knowledge for improved patient care. © 2024 IEEE.

关键词： Electronic health record

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Advanced Multi-Spectral Image Processing Techniques for Enhanced Remote Sensing and Comprehensive Environmental Monitoring in Diverse Ecosystems

Advanced Multi-Spectral Image Processing Techniques for Enha...

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2024 IEEE International Conference on Recent Advances in Science and engineering Technology, ICRASET 2024

作者： Jagannathan, J. Ponmalar, A. Pandiarajan, Rajkumar Sudha, I. Ramesh, P.S. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India R.M.K. Engineering College Tamilnadu Chennai India School of Computing Kalasalingam Academy Of Research and Education Department of Information and Technology Krishnankoil Virudhunagar India Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350388602

The research is aimed at improvement of multi-spectral image analysis for remote sensing and monitoring the environment at various ecosystems. A combined spectral imagery encompasses several spectrums at a time compared to single spectral imagery that takes only one spectrum at an instance or at a given area to cover all these spectrums. The study employs digital high resolution satellite images and ground based data to quantify the vegetation vigour, water quality, soil characteristics and changes in land cover. Features, indexes, and classification routines are employed to process the data that is collected with the aid of avionics and other peripherals. This provincial level modelling highlights important gains in environmental status, which includes the general improvement in vegetation condition, water quality as well as physical properties of the soil in the province. This study focuses on the complementary possibilities of integration of multi-spectral imaging with other remote sensing technologies and the high performance of data processing. These techniques play significant roles if used to give current and comprehensive information in the management and conservation of the environment as highlighted in the study. © 2024 IEEE.

关键词： data analysis environmental monitoring image processing techniques machine learning Multi-spectral imaging remote sensing soil properties vegetation health water quality

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Big Data Bot with a Special Reference to Bioinformatics

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Computers, Materials & Continua 2023年第5期75卷 4155-4173页

作者： Ahmad M.Al-Omari Shefa M.Tawalbeh Yazan H.Akkam Mohammad Al-Tawalbeh Shima’a Younis Abdullah A.Mustafa Jonathan Arnold Biomedical Systems and Informatics Engineering Department Yarmouk UniversityIrbid21163Jordan Department of Medicinal Chemistry and Pharmacognosy Yarmouk UniversityIrbid21163Jordan Department of Electrical Computer and Software EngineeringUniversity of Ontario Institute of TechnologyOshawaL1H7K4Canada Department of Mechanical Engineering University of MosulMosul41001Iraq Genetics Department University of GeorgiaAthens30602GAUSA

There are quintillions of data on deoxyribonucleic acid(DNA)and protein in publicly accessible data banks,and that number is expanding at an exponential *** scientific fields,such as bioinformatics and drug discovery,rely on such data;nevertheless,gathering and extracting data from these resources is a tough *** data should go through several processes,including mining,data processing,analysis,and *** study proposes software that extracts data from big data repositories automatically and with the particular ability to repeat data extraction phases as many times as needed without human *** software simulates the extraction of data from web-based(point-and-click)resources or graphical user interfaces that cannot be accessed using command-line *** software was evaluated by creating a novel database of 34 parameters for 1360 physicochemical properties of antimicrobial peptides(AMP)sequences(46240 hits)from various MARVIN software panels,which can be later utilized to develop novel ***,for machine learning research,the program was validated by extracting 10,000 protein tertiary structures from the Protein Data *** a result,data collection from the web will become faster and less expensive,with no need for manual data *** software is critical as a first step to preparing large datasets for subsequent stages of analysis,such as those using machine and deep-learning applications.

关键词： Bioinformatics big data data extraction bot drug design

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Don't Forget the Exception! : Considering Robustness Changes to Identify Design Problems 20

Don't Forget the Exception! : Considering Robustness Changes...

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20th IEEE/ACM International Conference on Mining software Repositories, MSR 2023

作者： Oliveira, Anderson Correia, Joao Sousa, Leonardo Assuncao, Wesley K. G. Coutinho, Daniel Garcia, Alessandro Oizumi, Willian Barbosa, Caio Uchoa, Anderson Pereira, Juliana Alves Informatics Department - Pontifical Catholic Rio de Janeiro Brazil Carnegie Mellon University Department of Electrical and Computer Engineering Pittsburgh United States Institute of Software Systems Engineering Linz Austria Itapajé Brazil

ISBN: (纸本)9798350311846

Modern programming languages, such as Java, use exception-handling mechanisms to guarantee the robustness of software systems. Although important, the quality of exception code is usually poor and neglected by developers. Indiscriminate robustness changes (e.g., the addition of empty catch blocks) can indicate design decisions that negatively impact the internal quality of software systems. As it is known in the literature, multiple occurrences of poor code structures, namely code smells, are strong indicators of design problems. Still, existing studies focus mainly on the correlation of maintainability smells with design problems. However, using only these smells may not be enough since developers need more context (e.g., system domain) to identify the problems in certain scenarios. Moreover, these studies do not explore how changes in the exceptional code of the methods combined with maintainability smells can give complementary evidence of design problems. By covering both regular and exception codes, the developer can have more context about the system and find complementary code smells that reinforce the presence of design problems. This work aims to leverage the identification of design problems by tracking poor robustness changes combined with maintainability smells. We investigated the correlation between robustness changes and maintainability smells on the commit history of more than 160k methods from different releases of 10 open-source software systems. We observed that maintainability smells can be worsened or even introduced when robustness changes are performed. This scenario mainly happened for the smells Feature Envy, Long Method, and Dispersed Coupling. We also analyzed the co-occurrence between robustness and maintainability smells. We identified that the empty catch block and catch throwable robustness smells were the ones that co-occurred the most with maintainability smells related to the Concern Overload and Misplaced Concern design problems. T

关键词： Maintainability

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Enhancing Healthcare Data Security in Cloud Computing systems through Advanced Homomorphic Encryption Techniques Integrated with Cuckoo Search Optimization Algorithm

Enhancing Healthcare Data Security in Cloud Computing System...

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2024 IEEE International Conference on Recent Advances in Science and engineering Technology, ICRASET 2024

作者： Sudha, I. Ramesh, P.S. Ponmalar, A. Jagannathan, J. Pandiarajan, Rajkumar Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India R.M.K. Engineering College Tamilnadu Chennai India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India Kalasalingam Academy of Research and Education School of Computing Department of Information and Technology Krishnankoil Virudhunagar India

ISBN: (纸本)9798350388602

The studies in this research are focused on the mix of homomorphic encryption mechanisms and the Cuckoo Search Optimization Algorithm to promote the security of the healthcare data in the cloud computing system. I have observed that cloud solutions are now at the center of the contemporary health care systems, and security of patient's data remains a top priority. Earlier used encryption techniques, though secure if implemented, have problems in the way that data is to be processed first it has to be decrypted and then made ready for use - it is in this phase that data can be easily hacked into. Homomorphic encryption provides solution to this issue since it enables one to perform computations on encrypted data while maintaining its confidentiality. However, it takes a lot of computation which presents a lot of problems even in terms of simple performance. The Cuckoo Search Algorithm, a new nature-inspired metaheuristic, is incorporated into the encryption process to provide further optimization, whilst preserving the security benefits of the algorithm. The use of the proposed methodology takes place employing Python and its deployment at the cloud platform with elaborated dataset containing anonymized records extracted from electronic health records. The outcome proves that there are great enhancements in encryption and decryption time, computational complexity, and capacity, and thereby making the system appropriate for real-world healthcare solutions. This research offers a strong base for protection of healthcare data in cloud and is useful for the enhancement of adaptive, comprehensive and secure cloud computing systems. © 2024 IEEE.

关键词： Electronic health record

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CASKA-CRT: Chinese Remainder Theorem Empowered Certificateless Aggregate Signcryption Scheme with Key Agreement in IoVs

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-16页

作者： Hou, Yingzhe Cao, Yue Xiong, Hu Sun, Zhili Mumtaz, Shahid Tian, Daxin School of Cyber Science and Engineering Wuhan University Wuhan China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Institute of Communication Systems University of Surrey Guildford U.K Department of Applied Informatics Silesian University of Technology Akademicka Gliwice Poland State Key Laboratory of Vehicle-Infrastructure Integrated ITS the State Key Laboratory of Intelligent Transportation System and the School of Transportation Science and Engineering Beihang University Beijing China

To enhance the privacy of messages in Internet of Vehicles (IoVs), it is critical to preserve the communication security between Road Side Unit (RSU) and numerous vehicles. The primitive of signcryption is introduced to guarantee the confidentiality, integrity and unforgeability of transmitted messages. Nevertheless, the existing signcryption schemes fail to achieve a balance between security and efficiency. In this paper, we construct a Chinese remainder theorem (CRT) empowered certificateless aggregate signcryption scheme with key agreement (CASKA-CRT). As the vehicle joins and leaves dynamically, the proposed scheme can ensure the dynamic security via one modulo division operation. Besides, the certificateless aggregate signcryption and key agreement mechanisms are embedded. The former idea can both address the certificate management and key escrow problems, while the latter technology can create authentication as a premise of secure communication. Based on this construction, the hash-to-group operation and bilinear pairing are avoided, to realize a faster verification with the increased number of messages. Moreover, the security of proposed scheme is proved under the random oracle model. Finally, the performance analysis demonstrates the advantage of CASKA-CRT in terms of security and reliability over related works. IEEE

关键词： Public key cryptography

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Integrating Open-Source VoNR in 5G SA Private Networks: An Experimental Evaluation 32

Integrating Open-Source VoNR in 5G SA Private Networks: An E...

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32nd International Conference on software, Telecommunications and Computer Networks, SoftCOM 2024

作者： Modroiu, Elena-Ramona Mwangama, Joyce Corici, Marius Magedanz, Thomas University of Cape Town Electrical Engineering Cape Town South Africa Technische Universität Berlin Next Generation Networks Dept Berlin Germany Fraunhofer Fokus Institute Software-based Networks Dept Berlin Germany

ISBN: (纸本)9789532901382

With the standardization of the 5th Generation of mobile networks, private 5 G networks are poised to support new industry verticals significantly. For small and medium-sized companies, affordability is crucial for the adoption and deployment of these solutions. Open-source projects that implement components of the 5 G system are likely to play a key role in reducing the entry barrier for private 5 G network solutions. This research paper presents the world's first voice-over-5G prototype using only open-source projects, successfully implemented at Technische Universität Berlin, along with initial performance measurements. © 2024 University of Split, FESB.

关键词： 5G mobile communication systems

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