Performance Analysis of Homomorphic Cryptosystem on Data Security in Cloud Computing

<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>

<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>

All the organization wants to implement the same security parameters as they are already using with their internal data/resources. It is mandatory to understand and find the data protection challenges before outsourcing the data security in cloud computing. In present research we are discussing about the impact of security in cloud computing including all the challenges associated with it.

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.

The security issues in the cloud have been well studied. The data security has much importance in point of data owner. There are number of approaches presented earlier towards performance in data security in cloud. To overcome the issues, a class based multi stage encryption algorithm is presented in this paper. The method classifies the data into number of classes and different encryption scheme is used for different classes in different levels. Similarly, the user has been authenticated for their access and they have been classified into different categories. According to the user profile, the method restricts the access of user and based on the same, the method defines security measures. A system defined encryption methodology is used for encrypting the data. Moreover, the user has been returned with other encryption methods which can be decrypted by the user using their own key provided by the system. The proposed algorithm improves the performance of security and improves the data security.

WITHDRAWN: Efficient Secure Aware Scheduling Model for Enhancing Security and Workflow Model in Cloud Computing

In the distributed systems security of data is a vital functionality, sharing of information in cloud storage is a provident technique. Nowadays, the main challenges is data security in cloud computing. To overcome this problem we proposed a novel Dynamic Privacy Aggregate Key Re-Encryption (DPAK-RE) algorithm. The DPAK-RE algorithm provides security to sharing the information in the cloud. We describe a secure data sharing with other users in cloud storage. Data corner is authorized to the admittance approach related with individual information that is to be stored within jurisdiction. The authenticate users can aggregate several groups of top-secret keys and makes them as enfold together a solitary key and potential of entire keys being aggregated. This aggregate key is Re-encrypted and generates the personal key as a constant key size. This Personal key provides more secure of the privacy information for data sharing in cloud storage. The execution investigation and the security confirmation demonstrate that the proposed scheme can accomplish more effective and secure information sharing in a cloud environment.

A key component of data security in cloud computing systems is encryption. Encryption might not be enough, though, to shield sensitive data from hostile intrusions. One such attack is the keyword guessing attack, in which an attacker uses a variety of techniques to attempt to decipher a term from the encrypted data. In this research, we suggest a system for encryption against a cloud computing keyword guessing attack. To achieve improved data security, the framework combines encryption methods with a safe keyword retrieval system. The framework that is being developed takes into account the difficulties that come with storing and retrieving encrypted data in cloud environments. Our test findings demonstrate that the suggested framework successfully thwarts keyword guessing attacks while preserving the data's confidentiality and integrity.

Cloud computing is one of the result of rapid growth of computing technology which has now affect the very way by which organizations and individuals uses IT resources such as application, storage, etc. by providing shared virtual versions of such resources which comes with the benefit of reducing the cost of hardware and software installation, but the concerns of organizations lies within the security and privacy of their data at rest on the cloud storage, among such concerns are the unauthorized usage by possible malicious insider within the cloud provider organisation and other cloud users. Despite the fact that service providers used many mechanisms to protect unauthorized access to data stored in their cloud storage, but there is no any mechanism to protect unauthorized access to the client’s data by the cloud service administrator. In this work we show how a steganography which is a technique of concealing the existence of a data inside a cover medium can be used to improve the security of data in the cloud by using additional layer of security that is user centric. However, the application of the proposed technique is implemented using a particular case study.

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.

ABSTRACTTo protect user privacy and data security in cloud computing, a secure k‐nearest neighbor computation‐enhanced scheme on encrypted database has been proposed by Wong, Cheung, Kao and Mamoulis. The scheme is proven resistant to the known‐plaintext attack. We show that contrary to claims, the enhanced asymmetric scalar‐product‐preserving encryption cannot resist known‐plaintext attack by directly solving a secret key from a set of known plaintext–ciphertext pairs. Copyright © 2014 John Wiley & Sons, Ltd.

Data replication-based cloud data access control mechanism plays a major role in real-time cloud computing environment due to high computational cost and memory. Hybrid data replication models play a vital role in the cloud-based applications for data recovery and security. Machine learning tools and techniques play an essential role in the medical field and cloud computing applications. Most of the traditional machine learning models use static data partitioning and replication methods in order to recover patterns from multiple virtual machines in cloud computing environment. In this work, a hybrid data replication and multi-user data access mechanism is developed to provide strong data recovery and security in cloud computing environment. In this work, a machine learning based patterns are used for data partitioning and security in the cloud server for cloud data security. Experimental results show that the hybrid data replication model has better data replication time and storage space than the conventional data replication models in cloud computing environment.KeywordsData replicationData partitioningCloud computingData accessMedical patterns

Cloud security is an evolving sub-domain of computer and network security. Cloud platform utilizes third-party data centers model. An example of cloud platform as a service (PaaS) is Heroku. It supports several programming languages that are used for web application deployment model. Heroku is based on a managed container system, with integrated data services and a powerful ecosystem, for deploying and running modern apps. One essential issue in cloud computing is data security, which is handled using cryptography methods. A possible method to encrypt data is Advanced Encryption Standard (AES). In this paper, we implement Heroku as a cloud platform, then we implement AES for data security in Heroku. The performance evaluation shows that AES cryptography can be used for data security. Moreover, delay calculation of data encryption shows that larger size of data increases the data delay time for encrypting data.

Cloud computing is defined as the management and provision of resources, software, applications, and information as services over the internet. Numerous organizations are adopting cloud services because of the economy and technology changes. Over the past year, cloud computing has made life easier for other people or organizations by allowing people to have access to information from anywhere in the world through the internet. However, cloud computing introduces a series of security concerns, which data security is a major concern. Data security is basically linked with any security in the cloud. If the network or infrastructure security is compromised, the possibility there is a possibility of data being affected. Data security has three important principles that are Confidentiality, Integrity, and Availability (CIA) that needs to always be maintained. Understanding the security concerns in cloud computing is an important requirement for those who are planning to move to the cloud solution. Thus, this paper aims to investigate and develop a hybrid data security framework to mitigate data security challenges in the cloud, focusing on legal frameworks such as POPIA and GDPR. A survey was conducted to investigate which techniques are more effective in protecting data and the evaluation ensured that CIA triads are covered. The limitation on the existing techniques is that they address only one principle or two, but not all three at the same time. The best technique among the others will be used integrated when designing the proposed framework in order to address CIA. Having more than one security technique to address data security will improve the security in the cloud and will also bring more business to cloud service providers when customers see the security in data enhanced.

This article critically examines the increasing reliance on cloud computing for data storage and processing, with a focus on the associated security and privacy challenges, especially when handling sensitive data. It explores homomorphic encryption (HE), particularly fully homomorphic encryption (FHE), as a promising solution for enabling computations on encrypted data without compromising confidentiality. Through a systematic literature review of studies published between 2017 and 2024, the article evaluates various homomorphic encryption algorithms, assessing their effectiveness in encryption and decryption, as well as performance metrics such as execution time, communication overhead, and energy consumption. The findings identify FHE as a widely researched technique, yet highlight significant challenges, including high computational overhead and complexity, which limit its suitability for real-time applications. The article underscores the need for continued research to enhance the efficiency of HE algorithms and calls for collaborative efforts among academia, industry, and regulators to establish robust frameworks for data privacy and security in cloud computing environments.