An Effective Hybrid Encryption Algorithm for Ensuring Cloud Data Security

Multi cloud storage is one of the most important services in cloud computing, used to store and access the data remotely. With the advancement in internet technology, the use of cloud computing has improved rapidly in many countries. Data security is considered as one of the most critical aspects in cloud computing due to the valuable and sensitive information stored in the cloud for the clients. To enhance the privacy and security of the information in the multi cloud, a robust technique is presented in this paper. The main focus of this study is to address the privacy and security risks of data in the multi cloud storage. The proposed technique is based on the cryptographic technique with dynamic file slicing method for securing data in multi cloud. Specifically, data is fragmented into many slices. The number of slices is defined by the data owner. The sliced files are encrypted with 3 DES (data encryption standard) and elliptical curve cryptography (ECC) algorithm. The performance of the proposed technique is evaluated using latency time. Efficacy of the technique is analyzed by varying the file size and format. Results reveal that the proposed technique outperforms the other methods. In addition to this, five prime security issues such as privacy, confidentiality, data integrity, malicious files and insider attacks are also examined and compared with the other existing models.

In order to protect the security and privacy of big data, the cloud storage service needs to enforce effective access control mechanism on user requests. Attribute-Based Encryption is a promising cryptographic access control technique to ensure the end-to-end security of data in cloud. However, the existing ABE researches mainly focus on the efficiency decryption, while the flexibility of policy, the communication cost, and the metadata management of ciphertexts are still challenging issues in the big data environment. In this paper, for the first time, we propose a new distributed, scalable and fine-grained access control scheme based on classification attributes for the cloud object storage. The classification attributes and threshold policies are integrated into an access structure, and then the objects are encrypted with the integrated access structure. The constant-size ciphertext components related to attributes can be managed as the corresponding metadata. As a result the encryption complexity and ciphertext storage are reduced. In addition, we present a new label-based access control model with multi-authorities to describe the detailed relationships of entities in our scheme. Besides, the proposed scheme is proved to be secure under l-BDHE assumption, and the system implementation demonstrates the practical feasibility and good performance.

Cryptography is a technique used today hiding any confidential information from the attack of an intruder. Today data communication mainly depends upon digital data communication, where prior requirement is data security, so that data should reach to the intended user. The protection of multimedia data, sensitive information like credit cards, banking transactions and social security numbers is becoming very important. The protection of these confidential data from unauthorized access can be done with many encryption techniques. So for providing data security many cryptography techniques are employed, such as symmetric and asymmetric techniques. In this review paper different asymmetric cryptography techniques, such as RSA (Rivest Shamir and Adleman), Diffie-Hellman, DSA (Digital Signature Algorithm), ECC (Elliptic curve cryptography) are analyzed. Also in this paper, a survey on existing work which uses different techniques for image encryption is done and a general introduction about cryptography is also given. This study extends the performance parameters used in encryption processes and analyzing on their security issues.

Most cloud users and officialdoms have a great interest in adoption and use cloud services like cloud storage to store their data on cloud environment. With the speedy growing in cloud computing technology, user's data security and privacy in cloud computing technology is the utmost dangerous issues because data owner stores their sensitive data onto remote cloud storage. However, successful retrieval of confidential data and computation on confidential data is hard to succeed by traditional cryptographic algorithm. Hence, to warrant the cloud security we are using the cryptographic algorithms that supports for computation over encrypted data. In this, Homomorphic cryptographic algorithm is one such technique that has interested homomorphic cryptographic algorithm used to secure user data in cloud server. It performs computation on cipher texts data can be operated directly without affecting the confidentiality of the encryption algorithms. We have established a framework for security of data on a cloud storage by using fully homomorphic cryptographic algorithm. Indeed, In this study, we have evaluated complexity of three homomorphic cryptographic algorithm those are SDC FHE, Paillier and RSA with encryption time, decryption time, throughput and memory usage

<p>Cloud computing has spread widely among different organizations due to its advantages, such as cost reduction, resource pooling, broad network access, and ease of administration. It increases the abilities of physical resources by optimizing shared use. Clients’ valuable items (data and applications) are moved outside of regulatory supervision in a shared environment where many clients are grouped together. However, this process poses security concerns, such as sensitive information theft and personally identifiable data leakage. Many researchers have contributed to reducing the problem of data security in cloud computing by developing a variety of technologies to secure cloud data, including encryption. In this study, a set of encryption algorithms (advance encryption standard (AES), data encryption standard (DES), Blowfish, Rivest-Shamir-Adleman (RSA) encryption, and international data encryption algorithm (IDEA) was compared in terms of security, data encipherment capacity, memory usage, and encipherment time to determine the optimal algorithm for securing cloud information from hackers. Results show that RSA and IDEA are less secure than AES, Blowfish, and DES). The AES algorithm encrypts a huge amount of data, takes the least encipherment time, and is faster than other algorithms, and the Blowfish algorithm requires the least amount of memory space.</p>

With the increasing popularity of network technology and information concepts, Big Data (BD) and cloud computing technologies have emerged and are widely used in all industries. BD technology can fully utilize the application value of information. Cloud computing can store a large amount of data, and improve data usage efficiency, so as to make full use of the value of data. At the same time, data security issues have become increasingly important. However, due to various factors, many users are faced with data breaches and privacy violations in the BD cloud computing environment. In this case, there are some data security risks, and the key issue is to consider how to avoid these risks. By analyzing the relationship and differences between BD and cloud computing, this article studied the issues and influencing factors of Artificial Intelligence (AI) data security in the BD cloud computing environment, and proposed corresponding optimization strategies, so as to improve data security and provide users with a brand new experience. Through comparison, it could be seen that the data processing speed and legal integrity after using the optimization strategy significantly improved. Among them, data processing speed increased by 7.2% and legal integrity increased by 10.4%. BD cloud computing could effectively improve AI data security performance.

Recently, there has been a significant increase in the number of Internet users. Thus, digital data has occupied the highest rank in our time, because most companies and governments adopt the total dependence for the transmission of their data transactions with customers and banking transactions over the World Wide Web. Therefore, total reliance on digital data needs to secure this data and preserve it from theft and modification in order to reach the intended user intact without distortion, and this is done by securing this data using encryption with its various techniques. There are many technologies that encrypt the data sent to the receiving party called encryption techniques. This research will examine the analysis of different encryption techniques, for example, symmetric cryptography technique and asymmetric cryptography techniques, Rivest Shamir and Adleman, Diffie-Hellman, Digital Signature Algorithm, (ECC) Elliptic curve cryptography, and how can employ them and explore the best methods of cryptography techniques that give complete confidential and transmitted data.

Cloud Computing is a way to deal with fabricate the breaking point or incorporate capacities effectively without placing assets into new system, planning new staff, or approving new programming. They have various potential purposes of intrigue and various attempt applications and data are moving to open or half and half cloud. However, regarding some business-fundamental applications, the affiliations, especially considerable attempts, still wouldn't move them to cloud. The market gauge the Cloud Computing shared is as yet far behind the one expected. From the clients' perspective, Cloud Computing security concerns, especially data security and security confirmation issues, remain the basic inhibitor for gathering of Cloud Computing organizations. In this paper, we present a diagram on data security and security protection issues related with Cloud Computing over all periods of data life cycle. Firstly,, we moreover focus a related works and after that we show unpretentious components of Cloud Computing security issues, and a short time later data security and insurance affirmation issues, and a while later we display some present courses of action in cloud. Finally, we look at future work about data security and security affirmation issues in cloud. Keywords: cloud computing; security deployment; privacy protection infrastructure.

Despite the promising application of cloud computing within government organisations, determining the barriers to the successful implementation of cloud computing remains a major challenge. Often, government organisations face formidable barriers to fully adopting cloud computing functions. These barriers include organisational culture issues, a weak application of service-level agreements (SLAs), compliance issues, interoperability and integration issues, the lack of an organisational strategy, cost calculation methods, cloud service availability, and cloud data security and privacy, as well as insufficient trust in providers. Tackling these barriers while meeting the specifications of government cloud computing involves architectural requirements and mechanisms. In addition, the nature of cloud ecosystem operation and its alignment with appropriate strategies are known to be complex, also considering the growing desire for governance solutions. Although researchers and organisations have recognised cloud computing obstacles prior to the cloud implementation stage, fewer efforts have been made to investigate cloud barriers in-depth during and after cloud implementation projects or when introducing governance solutions. This might partly be attributable to inadequate enterprise requirements for addressing cloud barriers, the complexity of government cloud specifications, and the lack of involvement by cloud stakeholders, such as providers and consumers. Thus, the aim of this dissertation is to develop a governance method consisting of the generation and testing of architectural requirements to overcome dominant cloud barriers and improve cloud computing functionalities in the implementation stage. To achieve this, the roles of related cloud providers and consumers have been investigated. The study was guided by activities of The Open Group Architecture Framework (TOGAF) Architecture Development Method (ADM) to design related architectural requirements that would provide best practices for the development of the governance method. Using a sequential, exploratory mixed method, multiple qualitative case studies on the role of cloud providers were conducted to explore which and how architectural requirements are suitable and applicable for addressing the identified cloud barriers. Afterwards, a quantitative survey study was performed to examine and validate the findings from the qualitative phase and to discover the role of cloud consumers in tackling cloud barriers. The utilisation of dual perspectives, from cloud providers and consumers, to design and measure the suitability and applicability of the architectural requirements is a substantial theoretical contribution in the field of enterprise information systems and cloud governance. Both cloud providers and consumers in the selected research context balanced their roles in the composition of cloud ecosystem projects, reducing complexity and enabling cooperative solutions for handling cloud barriers with different levels of emphasis and prioritisation. The results of this thesis provide significant guidance in eliciting architectural requirements as well as in their successful contribution to addressing the 10 identified cloud barriers in the selected context. Seeking a cloud provider’s perspective through multiple case studies resulted in 24 confirmed, newly emerged architectural requirements and 48 sub-requirements for best practices to support Information Technology (IT) managers and practitioners during the implementation of government cloud projects. From the point of view of the cloud service consumer, statistical evidence showed that the architectural requirements proved to be relevant and applicable and resulted in the validation of only eight important cloud constructs with a scale of 36 architectural requirements. The results at the governance level also produced a clear method that can enhance the realisation of value when business/IT strategies and EA governance practices both take place in cloud projects. The governance method also consists of a set of architectural requirements to support managing and controlling cloud computing implementation projects with related stakeholders and change management initiatives. The architectural requirements have been modelled via the ArchiMate 3.0 modelling language as unique and beneficial contributions for the enhancement of enterprise architecture practices. This thesis thereby introduces a novel cloud governance method with clear mechanisms and practices to serve as crucial resources for related organisations, decision-makers, business practitioners and researchers.

Even though cloud computing has advanced over the years, the two major challenges currently faced by cloud computing are data security and trusted computing. In cloud computing applications, blockchain technology can enhance data security and trusted computing when paired with virtual machine agents and mobile agent technologies. A decentralized new framework for distributed computing is blockchain. A potential area of study is the integration of blockchain technology with cloud computing, leveraging the former's security mechanisms to enhance the latter's secure computing and storage capabilities. The usage of the proposed framework builds on the inherent security features of blockchain technology in an effort to secure data and information integrity, confidentiality and authentication in cloud environments. Through the introduction of distributed virtual machine agents, the framework increases the scalability and effectiveness of data protection mechanisms for virtual data environments that can be used to store information protected by cloud security measures. Thus, the proposed study substantiates the applicability and efficiency of the existing and emerging problems of cloud data security and this approach develops satisfactory data protection solutions.

The integration of cloud computing and data security systems is vital for the operational success and competitiveness of fintech startups. Cloud computing enables these startups to scale quickly, manage resources efficiently, and reduce infrastructure costs, making it an indispensable tool for businesses in the rapidly evolving fintech sector. However, with the benefits come significant challenges, particularly in data protection and cybersecurity. As fintech services handle sensitive financial data, ensuring robust security measures such as encryption, access controls, and continuous monitoring is crucial to maintaining user trust. Furthermore, regulatory compliance, both local and global, adds complexity to the data protection strategies of fintech companies. This research explores the key factors that drive cloud adoption in fintech, the security challenges associated with cloud environments, and the strategies implemented by startups to address these challenges. Interviews with IT managers from Indonesian fintech startups reveal that while cloud computing offers scalability and cost-effectiveness, issues like compliance with local regulations and the protection of sensitive data remain major concerns. The research suggests that fintech startups should invest in both cloud infrastructure and advanced cybersecurity measures to protect their operations and customer data. Additionally, creating a comprehensive roadmap for regulatory compliance and fostering partnerships with cybersecurity firms will help mitigate risks and ensure long-term success. The findings highlight the importance of integrating cloud computing with effective security strategies to navigate the complex regulatory and security landscape of the fintech industry.

<span lang="EN-US">Cloud Computing is the ability to improve the utility or train new human resources without investing in new infrastructure, or add capabilities to existence without the latest software licensing. It expanded the capabilities of Information Technology (IT). From the past few years, cloud computing has developed from a good business concept in the best rising sectors of the IT industry. But more information on individuals and companies was put in the cloud, and concerns began to think about how secure the cloud environment was. Despite cloud surrounding structures, enterprise users still do not want to expand their business in the cloud. Security reduces the growth of cloud computing and continues to spread the market with complexity with data privacy and data protection. The security of cloud computing has constantly been an significant aspect of improved quality of service from cloud service providers. Data storage in the cloud has a problem related to data security. However, cloud computing construct many new security challenges which have not been well examine. In order to ensure that the user's data in the cloud is secure, we have proposed an effective mechanism with a distinctive feature of data integrity and privacy. This paper focusing on problems relating to the cloud data storage techniques and security in virtual environment. We recommend a method for providing data storage and security in cloud using public key Cryptosystem, which uses the concept of the modified RSA algorithm to provide better security for the data stored in the cloud. </span>

Cloud computing relies on sharing computing resources. With high availability and accessibility of resources, cloud computing is under the threat of major cyber-attacks. To detect attacks and preserve security in cloud environment, having an efficient intrusion detection system (IDS) is required. In this article, an effective and efficient IDS is proposed to maintain high level security of data in cloud. The authors have incorporated Reinforcement Learning Automata with their proposed IDS while detecting and classifying attacks. Using learning automata an effective rule set is generated with the proposed algorithm from vast training set to improve the learning process at reduced computation cost and time. After which, the proposed reinforcement learning algorithm helps in classification of attacks accurately using the reinforcement signal. This proposed model was experimented with NSL-KDD as well as KDD 10% dataset and have proved its robustness by detecting attacks more accurately being an IDS.

Cloud storage is a useful service of cloud computing which allows users to upload their data in the cloud and share it with others. Although, this new service is affordable and practical, but it is associated with several privacy and security challenges. Nowadays, Attribute Based Encryption (ABE) is widely used to provide secure data sharing in the distributed environment such as cloud computing. Unfortunately, most of the existing ABE schemes are not suitable for resource- constraint cloud systems, because they use expensive bilinear pairing operation and thus they cause a very high encryption and decryption computation overhead. In this paper, we propose an efficient no-pairing and revocable ABE data sharing scheme based on Elliptic Curve Cryptography (ECC) for cloud storage systems. Moreover, a comprehensive security and performance analysis shows that our scheme is both secure and efficient.

OTP(One Time Password) is for user authentication of Internet banking and users should carry their security card or OTP generator to use OTP. If they lost their security card or OTP generator, there is at risk for OTP leak. This paper suggests a new User Authentication Framework using personal health information from diverse technology of u-Health. It will cover the problem of OTP loss and illegal reproduction A User Authentication Framework is worthy of use because it uses various combinations of user`s physical condition which is inconstant. This protocol is also safe from leaking information due to encryption of reliable institutes. Users don`t need to bring their OTP generator or card when they use bank, shopping mall, and game site where existing OTP is used.