Data Security In Cloud Computing Research Articles

Enhancing Data Security and Accountability in Cloud Computing: A Decentralized Cloud Information Accountability Framework

Enhancing Data Security and Accountability in Cloud Computing: A Decentralized Cloud Information Accountability Framework

Data Security Issues in Intelligent Cloud Computing Systems

This project takes the intelligent cloud computing system as the main research object. It mainly uses the literature analysis method to explore the data security problems in the intelligent cloud computing system. By investigating the development background of intelligent cloud computing, the author summarizes the definition of cloud computing and the characteristics of cloud computing. The author also makes a specific analysis of the advantages of cloud computing, and concludes that cloud computing is possible through safe and reliable data, low demand for clients, shared cloud data and unlimited possibilities. These four points are the main reasons major enterprises choose cloud computing to replace traditional computing resources. In the topic, the author studied the data security problems in cloud computing from three aspects: the problems exposed in the development process of cloud computing, the effective measures to protect data security in cloud computing and predicting the future development trend of improving data security. The authors believe that future research should focus on a balance between network security issues in cloud computing and building a secure and reliable data system.

Analysis of Key Technologies for Data Security Protection Based on Cloud Computing

With the rapid development of cloud computing, more and more enterprises and institutions are migrating their data and business operations to the cloud. However, this shift has brought data security issues in cloud environments to the forefront. This paper primarily investigates the key technologies for data security protection in cloud computing environments. It begins by introducing the basic concepts and architecture of cloud computing and analyzing the fundamental concepts and threats related to data security protection. The paper then delves into critical technologies such as data encryption, access control, data storage and backup security, and data privacy protection, detailing the algorithmic principles and implementation methods of these technologies. Additionally, the paper explores the challenges faced by current cloud computing data security protection technologies and their corresponding solutions, analyzing the effectiveness of these technologies through practical case studies. Finally, the paper forecasts the future development trends of cloud computing data security technologies, particularly the potential impact of emerging technologies on data security protection. This research aims to provide theoretical and technical support for data security protection in cloud computing environments.

Enhanced Data Security and Storage Efficiency in Cloud Computing: A Survey of Data Compression and Encryption techniques

Enhanced Data Security and Storage Efficiency in Cloud Computing: A Survey of Data Compression and Encryption techniques

Review of Data Security and Privacy in Cloud Computing

Cloud computing, thus, ensure more healthy demand for cloud services, certain measures against threats in order to protect information must be taken. In essence, the current paper seeks to extend knowledge regarding the improvement of paradigms of cloud computing with particular focus on the aspect of certification of authentic users and protection of the contents that are hosted in these environments. It mentions a new approach in the context of the authentication method that was deployed for the purpose of the AAA certification is presented there along with the watermarking and this RSA algorithms to enhance the security of the cloud file-sharing. This concept is far more effective than the conventional access policies that are top down and cal beforehand for systematic risk avoidance; hence, it helps to minimize the chances of an organization being vulnerable to various risks by right management. Iturbide’s data loss prevention technique eliminates the probability of losing sensitive information to the rest of the world as well as other unauthorized persons or organizations regaining access to privileged keys while Shamir’s secret sharing algorithm- polynomial interpolation ensures that the generation of keys is not a time-consuming exercise. In order to address the issues of persistent security threats in cloud computing paradigm, the proposed model includes computation, encryption and access to improve the overall security of cloud environment. However, these measures have been implemented, some of them can offer the best security when it comes to the ever-evolving threat. To maintain the privacy of clients’ data in the CL reinforcement learning, the paper suggests the use of homomorphic encryption for privacy-preserving RL inference. Therefore – as a result of the work – the necessity of implementing the suggested security model for the cloud computing environments as well as protecting the data and enhancing the level of trust in cloud solutions is stated. Keywords - QoS (Quality of Service), Energy Efficiency, Ontology, AAA (Authentication, Authorization, and Accounting), RSA Algorithm, RSA Algorithm, ReDCIM (Reconfigurable Digital Computing-In-Memory) Processor, tableopencache, LSTM (Long Short-Term Memory)

The Next Frontier of Security: Homomorphic Encryption in Action

Abstract: Encryption is essential in preventing unauthorized access to sensitive data in light of the growing concerns about data security in cloud computing. Homomorphic encryption promises to enable secure calculations on encrypted data without the need for decryption, particularly for cloud-based operations. To evaluate the effectiveness and applicability of several homomorphic encryption algorithms for safe cloud computing, we compare and contrast them in this research paper. Partially homomorphic encryption (PHE), somewhat homomorphic encryption (SHE), and fully homomorphic encryption (FHE) are the three basic homomorphic encryption subtypes that we examine. The implications of this study can aid cloud service providers and organizations in selecting the most appropriate homomorphic encryption scheme based on their specific security requirements and performance considerations. The research contributes to the ongoing efforts to enhance data privacy in cloud computing environments, opening new possibilities for secure data processing in an increasingly connected digital world. The exploration of homomorphic encryption schemes in this study opens new avenues for research and development in the field of cryptographic techniques. As technology continues to evolve, so too must our approaches to safeguarding data. This research serves as a catalyst for further innovations in homomorphic encryption algorithms, enabling even more efficient and robust methods for secure data processing in cloud environments and beyond. The insights derived from this research paper not only empower cloud service providers and organizations to make informed decisions about selecting the most appropriate homomorphic encryption scheme but also contribute to the broader mission of fortifying data privacy and security in cloud computing.

User Centered Data Security in Cloud Computing Using Steganography

User Centered Data Security in Cloud Computing Using Steganography

A Review of Encryption Algorithms for Enhancing Data Security in Cloud Computing

Cloud computing is one of the most rapidly evolving technologies today; it provides numerous advantages that increase its affordability and dependability for use in the company. This paper goes over the concepts of cloud computing, such as its characteristics, deployment model, and service model, discusses the various benefits of cloud computing, and highlights the most pressing issues and security concerns in cloud storage. As a consequence, that leads to a review of distinctive cryptography algorithms that meet the security requirements (CIA: confidentiality, integrity, and availability) that are used to secure communications in cloud computing situations. It also displays many algorithms depending on the previous studies, such as Blowfish, RSA, DES, AES, MD5, Feistel, SP, HIGHT, LED, Cybpher, PRESENT, RC6, Diamond2, mCrypton, SLIM, Klein, PUFFIN-2, SEA, CLEFIA, LBlock, TWINE, 2, ANU, ANU-II, NLBSIT, Piccolo, BORON, RECTANGLE, LICI, QTL, LOGIC, TRIVIUM, Fruit-v2, Fruit-80, A4, the Enocoro family, and Grain family, to make a comparison among them using many measurements. It found that modern and lightweight algorithms are more suitable for use in this field. Furthermore, the purpose of this paper is to make some suggestions for improving the safety and security of cloud computing technologies.

A paradigm shift in education: Prospects and recommendations for schools in 2030

The interest of this study is borne out of an attempt to investigate the drastic change that technology has brought to the instructional core. The future of schools is exponentially upgrading through the integration of sophisticated educational systems that appear to create a whole new trajectory for all education stakeholders. Instruction will be adaptive and assessment will be real-time. In this profound and complex scenario, current schools will no longer be the epicenters of knowledge as AI-powered educational tools will hegemonize and remarkably offer extraordinarily enticing adaptive learning opportunities through smart classrooms and other technological trends and patterns, such as Cloud Computing (connectivity and data security) and the Internet of Things (IoT) (intelligent whiteboards). Needless to say, technology enhanced learning will unequivocally become the pinnacle of education. Therefore, many educators will have to expand their instructional technology to rise to the occasion.

Machine learning-enhanced hybrid cryptography and image steganography algorithm for securing cloud data

Ensuring data security in cloud computing is crucial due to the growing reliance on cloud-based services. Hybrid cryptography and image steganography have emerged as robust techniques to enhance data confidentiality in the cloud. In this research paper, we propose a novel algorithm, “Machine Learning-Enhanced Hybrid Cryptography and Image Steganography,” integrating these methods to provide comprehensive data protection. The algorithm employs key generation, encryption, steganography, cloud storage, data retrieval, and machine learning-based attack detection to defend against advanced cyber threats. Our experimentation demonstrates the algorithm’s effectiveness in detecting DoS attacks, data breaches, and data leakage attempts using SVM, Neural Network, Isolation Forest, and Random Forest models. The proposed approach offers broad applicability, fortifying data security and fostering further advancements in cloud security research.

Cryptographic Solutions for Data Security in Cloud Computing:

Due to the recent explosion in the amount of data being created by various social media platforms, e-commerce websites, and other businesses, a paradigm shift from on-site data centers to the cloud is required. Concerns about privacy and secrecy have been a major obstacle to the mainstream adoption of cloud computing. The best approach to protect the confidentiality and privacy of cloud data is by using cryptographic techniques. Researchers have developed several cryptographic algorithms, but they all have lengthy, linear, predictable, memory-intensive execution times. The performance of the CPU, memory, run-time trend, and throughput of the three cryptographic schemes: Enhanced RSA (ERSA), Non-Deterministic Cryptographic Scheme (NCS), and Enhanced Homomorphic Scheme (EHS) are compared using RAsys. The experiment’s results demonstrated that NCS and EHS produced non-linear and non-deterministic run times. Again, NCS and EHS produced the lowest throughput and memory consumption for text and numeric data types when data sizes of 5n*102(KB(∈1,2,4,10,20,40) were processed. However, ERSA produced a run-time trend that was deterministic, linear, and predictable

An Approach of Privacy Preservation and Data Security in Cloud Computing for Secured Data Sharing

Introduction: Cloud computing has revolutionized how individuals and businesses engage with data and software, turning the internet into a powerful computing platform by centralizing resources. Despite its benefits, there's a challenge in safeguarding sensitive information stored externally. Cryptography faces threats, particularly chosen-ciphertext attacks aiming for secret keys or system information. While more common in public-key encryption, these attacks are less frequent in symmetrically coded systems. Security efforts include validating system resilience and continuous improvement, which are vital in countering evolving threats like adaptive chosen ciphertext attacks. Method: In the evaluation model, stringent measures emphasize robust encryption for system security. Despite the planning, no ciphertext attack guarantees success, necessitating adaptive security protocols. Adaptive attacks like CCA2 expose vulnerabilities, enabling attackers to manipulate ciphertexts persistently. Result: We observe an average gain of 65% for the decryption algorithm. Efforts focus on strengthening security. The flawed 32-bit key-based encryption in the modified Cramer-Shoup structure undergoes remediation. Conclusion: Conventional uncertainties validate resilience, emphasizing continuous evaluation and enhancement to counter evolving threats.

Enhancing Data Security in Cloud Computing Using Blockchain

As cloud computing continues to proliferate, ensuring data security within cloud environments becomes increasingly critical. This paper explores the integration of blockchain technology as a means to enhance data security in cloud computing. Blockchain, with its decentralized and immutable ledger system, offers unique capabilities that address key security challenges such as data privacy, integrity, identity management, and compliance. Through a comprehensive analysis of blockchain's potential applications and integration strategies, this paper provides insights into how blockchain can bolster data security in cloud computing environments. Case studies and real-world implementations highlight successful integration efforts by major cloud service providers such as IBM, Microsoft, and Amazon. Additionally, this paper discusses the challenges and limitations associated with blockchain integration and explores future directions and emerging trends in the intersection of blockchain and cloud security. By leveraging blockchain technology, organizations can enhance their security posture in the cloud, ensuring the confidentiality, integrity, and availability of their sensitive data.

Enriched Cloud Computing Data Security through a Triple Level Encryption Model for Healthcare Systems

Enriched Cloud Computing Data Security through a Triple Level Encryption Model for Healthcare Systems

Securing Cloud Environment Using Hybrid (Adaptive Public Key) Model

Although data security has always been important, it is now even more so given the significance of cloud computing and the enormous amounts of complex data it holds. In cloud computing, having data accessible at all times is vital, as is collecting and preserving data without loss or corruption. The use of appropriate algorithms is one of the most important aspects of security. These protocols protect data by limiting unauthorized access. In order to ensure the security of your data, you need to conduct research on the security risks associated with public clouds. The purpose of this document is to provide an in-depth review of public clouds and the security issues associated with them. In order to review the literature review that provides an in-depth understanding of cloud storage and security issues, it is necessary to overcome several obstacles. As a result, based on an analysis of cloud architecture, we provide the data security model that can be applied to cloud computing. Our cloud computing data security model is now better. Lastly, the work can be done in a direction that benefits from faster encryption times and increased data secrecy by utilising machine learning and authentication technologies for safe cloud storage.

Adaptive Artificial Bee Colony Algorithm-Based Enhancement of Data Security in Cloud Computing

Adaptive Artificial Bee Colony Algorithm-Based Enhancement of Data Security in Cloud Computing

Enhancing Data Security in Cloud Computing: A Comparative Analysis of Encryption Techniques

Enhancing Data Security in Cloud Computing: A Comparative Analysis of Encryption Techniques

Securing Health Data in Mobile Cloud Computing by a Modular Encryption Approach

Abstract: In the dynamic field of healthcare informatics, this research review explores health data security in mobile cloud computing, emphasizing modular encryption standards. In this paper, an exploration of advanced security methodologies within the Mobile Cloud Computing landscape is presented. The study examines three distinct encryption strategies – Symmetric Key Encryption, Public Key Infrastructure, and Homomorphic Encryption – each strategically employing the Modular Encryption Standard. The findings underscore the versatility of these methods in fortifying health information security within mobile environments, providing an understanding of their implementation nuances and comparative advantages. The literature critically assesses protocols, authentication methods, and vulnerabilities in healthcare contexts, extending its analysis to incorporate emerging technologies.

RSA and AES Based Hybrid Encryption Technique for Enhancing Data Security in Cloud Computing

Cloud computing security has become the most crucial problem in its growth. Encryption has been developed as a solution and plays a vital role in the security of information systems in cloud computing. Many methods are required to secure the shared data. The advanced internet, networking firms, health information, and cloud applications have significantly increased our data every minute. The current work focuses on cryptography to protect sensitive data exchanged between personal users, companies, organizations, or in the cloud applications and others during data transfer across the network. Firstly, data sent from the sender to the network receiver must be encrypted using the cryptographic algorithm. Secondly, the recipient shows the original data using the decryption technique. In this paper, we have proposed a model to use a hybrid encryption and decryption process based on AES-128 and the RSA algorithm. Furthermore, we used the HMAC algorithm to ensure the integrity and authenticity of data. Our experiment work has been done to explain the time required and throughput for encryption and decryption of three encrypting algorithms, AES, RSA, and hybrid algorithms, based on different data sizes, and their efficiency is compared. The results of the experiments show that the hybrid algorithm is better in terms of security.

Beyond Encryption: A Multidimensional approach to Data Security in Cloud Computing and the Impact of AI/ML

Beyond Encryption: A Multidimensional approach to Data Security in Cloud Computing and the Impact of AI/ML