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检索条件"任意字段=Proceedings of the 5th ACM Conference on Data and Application Security and Privacy"

共 1522 条记录，以下是491-500 订阅

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DevSecOps Implementation for Continuous security in Financial Trading Software application Development 5

DevSecOps Implementation for Continuous Security in Financia...

引用

5th International conference on Advanced Research in Computing, ICARC 2025

作者： Dasanayake, S.D.L.V. Senanayake, Janaka Wijayanayake, W.M.J.I. University of Kelaniya Faculty of Science Department of Industrial Management Sri Lanka Robert Gordon University United Kingdom University of Kelaniya Sri Lanka

ISBN: (纸本)9798331530983

DevSecOps incorporates security into the DevOps workflow, ensuring robust protection throughout the software development lifecycle. this research addresses the security gaps in financial trading applications, where traditional methods often prioritize speed over security. Using the Design Science Research Methodology (DSRM), the study examines secure coding practices, regulatory compliance, and incident response strategies. Findings highlight the benefits of embedding automated security testing and continuous monitoring to enhance resilience against evolving threats. Tailored developer training addresses knowledge gaps specific to trading platforms, ensuring compliance with regulatory demands and safeguarding sensitive financial data. By accelerating deployment timelines while strengthening security and compliance, this study demonstrates the critical role of a DevSecOps model in creating scalable, secure, and resilient trading applications. © 2025 IEEE.

关键词： Software design

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Revolutionizing Artificial Intelligence applications with Blockchain Implementation

Revolutionizing Artificial Intelligence Applications with Bl...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),conference on

作者： Hasna Hajji Ourssoula Sikal Abdellah Zamma Mohamed El Khaili M2S2I Laboratory ENSET Hassan 2nd University of Casablanca Morocco M2S2I Laboratory ENSET ENSET Hassan 2nd University of Casablanca Morocco IESI Laboratory ENSET Hassan 2nd University of Casablanca Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Artificial Intelligence’s (AI) quick development has revolutionized several industries and brought new approaches to automation, data processing, and decision-making. However, obstacles related to data privacy issues, security threats, and model accountability have hindered the realization of its full potential. Blockchain technology, known for its immutable and decentralized nature, has emerged as a potentially viable solution for both problems at the same time. this article contributes an analysis of the interplay between Blockchain and Artificial Intelligence, underscoring their combined capacity to transform applications spanning several industries. We explore specific application scenarios where Blockchain enhances security measures, supports the development of reliable model training, and improves the administration of AI data. Additionally, we delineate the ethical, legal, and technical challenges associated with this integration. We offer perspectives on prospective research directions that could capitalize on this convergence to foster innovation. the findings of this study accentuate the transformative role of Blockchain in augmenting AI applications, ultimately establishing a foundation for a more secure, transparent, and efficient digital framework

关键词： Industries Ethics data privacy Decision making data processing data models Blockchains security Reliability Artificial intelligence

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7th International conference on Big data and Cloud Computing Challenges, ICBCC 2022

7th International Conference on Big Data and Cloud Computing...

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7th International conference on Big data and Cloud Computing Challenges, ICBCC 2022

ISBN: (纸本)9789819910502

the proceedings contain 24 papers. the special focus in this conference is on Big data and Cloud Computing Challenges. the topics include: Early Planning of Virtual Machines to Servers in Cloud Server Farms is an Approach for Energy-Efficient Resource Allocation;performance Analysis of Distributed Algorithms for Big data Classification;achieving Sustainability by Rectifying Challenges in IoT-Based Smart Cities;framework for Implementation of Smart Driver Assistance System Using Augmented Reality;ioT-Based Mental Health Monitoring System Using Machine Learning Stress Prediction Algorithm in Real-Time application;fish Feeder System Using Internet of things;an Efficient and Recoverable Symmetric data Aggregation Approach for Ensuring the Content privacy of Internet of things;Implementation and Comparative Analysis of Various Energy-Efficient Clustering Schemes in AODV;secure Web Gateway on Website in Cloud;adaptive End-To-End Network Slicing on 5G Networks;zero Trust Framework in Integrated Cloud Edge IoT Environment;o2Q: Deteriorating Inventory Model with Stock-Dependent Demand Under Trade Credit Policy;embedding (K9-C9)n into Certain Necklace Graphs;Lyrics Generation Using LSTM and RNN;design a Quantum Cryptography Algorithm and Evaluate the Risks of Quantum-Based Nano Computing;human Odor security Using E-nose;automated Road Surveillance System Using Machine Learning;an Artificial Intelligence-Based Technique to Optimize Hybrid Vehicle Using Renewable Energy Sources;stock Market Prediction Using Machine Learning Techniques: A Comparative Study;comparative Study on Different Intrusion Detection datasets Using Machine Learning and Deep Learning Algorithms;mitigating Postnatal Depression: A Big data Self-help therapy.

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Grid data sharing scheme based on blockchain and hybrid encryption 5

Grid data sharing scheme based on blockchain and hybrid encr...

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5th International conference on Mechatronics and Computer Technology Engineering, MCTE 2022

作者： Yang, Mingjie Liu, Ning Wang, Dong Zhang, Chi Digitalization Division of State Grid Gansu Electric Power Company Gansu Lanzhou730050 China

ISBN: (纸本)9781510661073

Smart grid collects data in real-time to accomplish load balancing and power resource allocation. However, the power grid data faces the security risk of being leaked or tampered with when it is transmitted through open channels. Based on blockchain and hybrid encryption, a secure grid data sharing scheme with hidden policy is proposed. the grid data is encrypted using a hybrid encryption technology of symmetric encryption and attribute-based encryption, which ensures the confidentiality and privacy of the grid data. the multi-attribute authorization mechanism is used to prevent collusion attacks, and the policy is hidden to ensure that private information is leaked. Additionally, the verification token is stored on the blockchain to complete message integrity verification. the analysis results show that this scheme has higher computational efficiency and can achieve secure sharing of grid data. © 2022 SPIE.

关键词： Blockchain

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TOUR towards the security CHALLENGES of VIRTUALIZATION in CLOUD COMPUTING: A SURVEY 5

TOUR towards the SECURITY CHALLENGES of VIRTUALIZATION in CL...

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5th International conference on Trends in Electronics and Informatics, ICOEI 2021

作者： Avinash, Jinkani Pranay, Kanakatla Goud, Nerandla Rakesh Tanwar, Poonam Sharma, Shweta Mriirs Haryana Faridabad India

ISBN: (纸本)9781665415712

In general, the consumers benefit from cloud computing because of its scalability, performance, flexibility, and low infrastructure investment. Everyone is moving from traditional services towards various cloud services at minimal cost. Because of the benefits of virtualization and data storage, people are increasingly embracing them and posing some new security issues. Using virtualization is an advantage for consumers because security is one of the features that are taken care to lesser extent. this paper summarizes the need for virtualization along with its benefits and multiple security vulnerabilities are explained in detail by a diagram that illustrates about virtualization security issues that are virtual machine based, Hypervisor based and virtual machine based attacks. there are some recommendations to strengthen the security and privacy in virtualization. © 2021 IEEE.

关键词： Scalability

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Efficient and privacy-Preserving Range Queries over Outsourced Cloud

Efficient and Privacy-Preserving Range Queries over Outsourc...

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International conference on Communications, Information System and Computer Engineering (CISCE)

作者： Chuanling Chen Dawei Tian Lu Li Nanjing Tech University Nanjing China School of Information Engineering Yancheng Teachers University Yancheng China Suzhou Research Institute University of Science and Technology of China Suzhou China

With the development of cloud computing, database outsourcing has become a very popular network service today. Due to privacy concerns, sensitive data must be encrypted before outsourcing, which is a challenging task regarding the effective use of data. Considering that range query, as the most common and important query method in cloud computing, is widely used in a variety of scenarios and algorithms, it is necessary to design a range query scheme to protect the security of private data. In this paper, we use Yao's garbled circuit and secret sharing method to construct a corresponding security range judgment protocol based on the difference between leaf nodes and non-leaf nodes in R-tree index structure, and on this basis, a secure and efficient range query algorithm on cloud computing is proposed. We prove the security of the algorithm under the semi-honest model through theoretical analysis. Finally, a large number of experiments prove its effectiveness in real application scenarios.

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Significant Cloud Computing Service for Secured Heterogeneous data Storing and its Managing by Cloud Users 5

Significant Cloud Computing Service for Secured Heterogeneou...

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5th International conference on Trends in Electronics and Informatics, ICOEI 2021

作者： Panyam, Aditya Sharma Jakkula, Pradeep Kumar Neelakanta Rao, P. Mlr Institute of Technology Department of It Telangana Hyderabad India

ISBN: (纸本)9781665415712

SAAS (Storage as a service) is referred as a significant cloud computing (CC) services that support cloud users (CU) to overcome the bottleneck on constrained assets and extent storage without updating their gadgets. To guarantee the protection privacy of CU, the information is generally outsourced in encrypted format. Nevertheless, encrypted information might produce more storage waste in cloud and complicates the data exchange among authorized users. Even now, some problems exist with encrypted data and deduplication in cloud and storage management. Traditional deduplication methods focus on specific application scenarios, whereas in the cloud, reduplication will be completely controlled by servers or data owners. they might not flexibly fulfill the separate requests obtained from data owners, who rely on sensitivity level of data. In this manuscript, the proposed method flexibly provides the similar time through numerous Cloud service providers [CSPs]. the researchers assesse the execution with security examination, comparison execution. © 2021 IEEE.

关键词： Storage management

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Efficient privacy-Preserving Federated Learning For Electricity data 5

Efficient Privacy-Preserving Federated Learning For Electric...

引用

5th IEEE International conference on Energy Internet, ICEI 2021

作者： Wang, Xiaohui Liang, Xiao Zheng, Xiaokun Global Energy Interconnection Research Institute Co.Ltd Artificial Intelligence On Electric Power System State Grid Corporation Joint Laboratory Beijing China

ISBN: (纸本)9781665407342

data has become the core driving force for the development of digital economy. Electricity data is also known as weather vane of national economic operating status. there is a huge challenge in terms of mechanism, technology and security on sharing and application of energy data on a larger scale. Based on the characteristics of power data, this paper proposes an efficient model federated-training method with data privacy protected, realizing the security co-construction of analysis models. this approach is combined with federated learning and secret sharing technology, help breaking the barriers between government and power enterprises, as well as among differnet departments of power enterprises. In addition, this paper makes a detailed analysis on the security of the approach, which ensures that the data privacy can be guaranteed in the semi-honest and malicious model of no more than one server being corrupted. Finally, the proposed scheme is verified by experimental simulation, and the experimental results are compared with plaintext training. the results show that the proposed scheme still be highly efficient and practical even if the security computing technology is introduced on. © 2021 IEEE.

关键词： privacy-preserving techniques

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Multimodal emotion recognition based on multilevel acoustic and textual information 5

Multimodal emotion recognition based on multilevel acoustic ...

引用

5th International conference on Artificial Intelligence and Computer Science, AICS 2023

作者： Zhou, Ya Xing, Yuyi Huang, Guimin Guo, Qingkai Deng, Nanxiao School of Computer Science and Information Security Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guangxi Guilin541004 China

ISBN: (纸本)9781510668621

the study and application of multimodal emotion recognition have gained significant popularity in recent years, representing one of the challenging tasks in the field of affective computing. We propose a multimodal speech emotion recognition model that utilizes multiple acoustic and textual information layers. this model incorporates transcribed textual data to complement speech data and enable accurate emotion recognition. In the unimodal model, we employ AlexNet, BiGRU, and HuBERT to extract multi-layer acoustic feature information from speech, and the RoBERTa encoder to extract text features. Additionally, we perform fusion between speech and text by utilizing the co-attentive mechanism to extract complementary information across modalities and eliminate inter-modality noise. this process ultimately enhances the emotional representation of the target modality. Finally, the fused features are utilized to predict the emotion category. Our model achieved a weighted sentiment recognition accuracy of 77.41% and an unweighted accuracy of 78.66%. © 2023 SPIE.

关键词： Emotion Recognition

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Integrating Artificial Open Generative Artificial Intelligence into Software Supply Chain security

Integrating Artificial Open Generative Artificial Intelligen...

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data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), International conference on

作者： Vasileios Alevizos George A. Papakostas Akebu Simasiku Dimitra Malliarou Antonis Messinis Sabrina Edralin Clark Xu Zongliang Yue Karolinska Institutet Solna Sweden MLV Research Group Department of Informatics Democritus University of Thrace Kavala Greece Zambia University Ndola Zambia IntelliSolutions Athens Greece HEDNO SA Athens Greece University of Illinois Urbana-Champaign Illinois USA Mayo Clinic Artificial Intelligence & Discovery Minnesota USA Auburn University Harrison College of Pharmacy Alabama USA

ISBN: (数字)9798350368710

ISBN: (纸本)9798350368727

While new technologies emerge, human errors always looming. Software supply chain is increasingly complex and intertwined, the security of a service has become paramount to ensuring the integrity of products, safeguarding data privacy, and maintaining operational continuity. In this work, we conducted experiments on the promising open Large Language Models (LLMs) into two main software security challenges: source code language errors and deprecated code, with a focus on their potential to replace conventional static and dynamic security scanners that rely on predefined rules and patterns. Our findings suggest that while LLMs present some unexpected results, they also encounter significant limitations, particularly in memory complexity and the management of new and unfamiliar data patterns. Despite these challenges, the proactive application of LLMs, coupled with extensive security databases and continuous updates, holds the potential to fortify Software Supply Chain (SSC) processes against emerging threats.

关键词： Industries data privacy Generative AI databases Large language models Source coding Supply chains Memory management Software security

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