Cloud Storage Providers Research Articles

Enhancing Cloud Data Deduplication with Dynamic Chunking and Public Blockchain

The majority of cloud service providers (CSPs) store and remove customer data according to certain principles. The majority of them have designed their cloud platform to have very high levels of consistency, speed, availability, and durability. Their systems are built with these performance characteristics in mind, and the requirement to ensure precise and rapid data deletion must be carefully balanced. In the public blockchain, this paper suggests employing the rapid content-defined Chunking algorithm for data duplication. Acute data is frequently outsourced by individuals and organizations to distant cloud servers since doing so greatly reduces the headache of maintaining infrastructure and software. However, because user data is transmitted to cloud storage providers and stored on a remote cloud, ownership and control rights are nonetheless separated. Users thus have significant challenges when attempting to confirm the integrity of private information. According to the experiment results, the suggested dynamic chunking has a fast processing time that is on par with fixed-length chunking and significantly improves deduplication processing capability.

EVALUATION OF DDOS INVASIONS

Cloud storage providers have widely integrated data deduplication techniques to manage the exponential growth of data. Various secure strategies for data deduplication have been developed to bolster the security of client data within shared storage environments. One critical area of focus is ensuring Re- encrypting deduplicated encrypted data in a safe and effective manner, which has garnered significant attention from researchers. However, recent investigations have uncovered vulnerabilities in the lightweight encrypted deduplication technique with rekeying awareness (REED), particularly susceptible to an assault via a stub-reserved. In response, We provide a reliable data deduplication method that uses effective re-encryption. leveraging Combined Win Big or Bust Transformation (CAONT) and segments that were chosen at random from the Sprout channel. Our approach is resilient protects sensitive data privacy and is resistant to the stub- reserved assault through one-way hash functions. Furthermore, our method minimizes computation overheads by requiring data owners to re-encrypt only a fraction of the package using CAONT, rather than the entire package. Through rigorous security analysis andexperiments, we validate the efficacy and safety of our re- encryption strategy. KEY WORDS: - Cloud storage, data deduplication, security, sensitive information, outsourced storage.

SECURITY OF DATA STORED IN CLOUD SERVICES

The main purpose of this study is to - examine the security issues of data stored in cloud services. The authors of the article discuss the main problems associated with an insecure and incorrectly configured cloud database, which can lead to leakage or distortion of information of Russian citizens and organizations. In the course of the study the authors come to the conclusion that in order to protect their data it is necessary to use cloud storage providers located on the territory of the Russian Federation (hereinafter referred to as RF), use a hidden storage system, regularly update and monitor the system to identify vulnerabilities and prevent possible attacks. In addition, ways to solve the problem and effectively protect information stored in cloud services, including at the legislative level, are proposed.

Cloud storage cost: a taxonomy and survey

Cloud service providers offer application providers with virtually infinite storage and computing resources, while providing cost-efficiency and various other quality of service (QoS) properties through a storage-as-a-service (StaaS) approach. Organizations also use multi-cloud or hybrid solutions by combining multiple public and/or private cloud service providers to avoid vendor lock-in, achieve high availability and performance, and optimise cost. Indeed cost is one of the important factors for organizations while adopting cloud storage; however, cloud storage providers offer complex pricing policies, including the actual storage cost and the cost related to additional services (e.g., network usage cost). In this article, we provide a detailed taxonomy of cloud storage cost and a taxonomy of other QoS elements, such as network performance, availability, and reliability. We also discuss various cost trade-offs, including storage and computation, storage and cache, and storage and network. Finally, we provide a cost comparison across different storage providers under different contexts and a set of user scenarios to demonstrate the complexity of cost structure and discuss existing literature for cloud storage selection and cost optimization. We aim that the work presented in this article will provide decision-makers and researchers focusing on cloud storage selection for data placement, cost modelling, and cost optimization with a better understanding and insights regarding the elements contributing to the storage cost and this complex problem domain.

Secure Cloud Storage Solution with “Seafile” & “NextCloud”: A Resilient Efficiency Assessment

Storage and file synchronization have become increasingly important services in our everyday lives. With cloud storage providers giving users access to file space in the cloud, one might wonder how efficient these cloud storage providers are with their encryption methods. There are many different cloud storage providers and programs to set up a cloud storage solution. This paper focuses on two secure cloud storage solutions, Seafile, and NextCloud, and determines the efficiency of these cloud storage solutions’ encryption methods. By determining the efficiency of these secure cloud storage providers’ encryption methods, it can help others determine which of these providers will fit their needs. To determine efficiency, the CPU, memory, and network usage of these cloud storage solutions will be measured at idle and when files are being uploaded to them. To measure the CPU, memory, and network usage, ‘dstat’ will be used to capture their usages and record them to a CSV file. It is expected that both cloud solutions will have better performance when they have files being uploaded to them with no encryption. However, with the encryption methods of both cloud solutions being lightweight, that was not the case.

User-Centric Cloud Framework for Enhanced Data Security by Applying UK Algorithm

Cloud storage is the technical boon which has become the realm of many companies like Amazon, Google, Microsoft, Drop box and many more. Remarkably all these companies are US based and thus eventually the personal data of every other nation is stacked on the Western companies. This leads the dependant country to a state of vulnerable. However if the dependant countries need to get autonomy they had to be provided with their own cloud storage which is impossible with the current mechanisms. With the facility of high computational devices and wide infrastructure and with the aid of secured encryption the cloud storage providers strongly protect the data of the users and enable their best service to the users. Also the cloud storage providers use the encryption algorithm in the provider infrastructure and data from user to provider infrastructure is done using the secured transmission. Finally the powerful infrastructure does the work to secure the data. This mechanism is certainly possible in the developed countries. But it is relatively impossible in the developing countries like India as it cannot afford the huge infrastructure to protect the public data. Even done, it might not result in generating profit because the subscription rate is comparatively lower in India than in developed countries. So to pursue the less profitable module is not suggestive and hence the reliability on western country cloud storage is over whelming. However to overcome this set back and to implement indigenous cloud storage this paper has attempted to implement the UK algorithm in user device environment through which mini and micro level cloud storage shall be developed resulting in the minimal cost of maintaining the cloud storage. In this case, cloud Storage provider do not need to have either the huge infrastructure nor the computational devices to process the data and no need of separate data transmission to secure the data as well. Employing the encryption algorithm in user environment helps to give full authority to the user on their data. The CS provider holds only encrypted data of the user and with low cost consumption this method is feasible even for the developing country like India.

SECURED ORGANIZATIONAL CLOUD STORAGE USING MESSAGE DIGEST ALGORITHM

The Secure Organizational Cloud Storage System is an advanced cloud storage platform designed specifically for organizations that prioritize data security. The platform provides a similar functionality to Google Drive, but with enhanced security features to ensure that sensitive information remains safe from cyber threats. With the Secure Organizational Cloud Storage System, organizations can store and manage their data in a centralized and secure location. Users can easily upload, share, and collaborate on files and documents, and can access them farom anywhere with an internet connection. Secure cloud storage is indispensable in today's data-driven world, providing the convenience of remote data access while mitigating the risks associated with cyber threats and data breaches. By implementing advanced encryption, access controls, data integrity checks and redundancy strategies, secure cloud storage systems offer a comprehensive solution to protect sensitive information in an increasingly interconnected digital ecosystem. This abstract serves as a concise introduction to the importance and key components of secure cloud storage. Cloud service and storage providers offer valuable IT solutions for businesses of all sizes. Originally thought of as more for personal use, cloud storage for business is following in the footsteps of many personal technologies adapted for business purposes. Cloud storage works by storing data on remote servers, where it can be maintained, managed, backed up and accessed remotely. Data stored in the cloud is accessible by any device at any time, as long as permissions are in place. Despite its accessibility, data stored via the cloud is extremely safe and secure. Many people reap the benefits of the cloud for personal reasons, but most businesses have yet to take the leap. Whether your current on-premises data storage seems sufficient, or you simply haven’t taken time to consider cloud storage, reviewing these advantages is a good place to start.

Online Pricing and Resource Scheduling for Profit Maximization of Cloud Storage Providers

Online Pricing and Resource Scheduling for Profit Maximization of Cloud Storage Providers

Ensuring Data Integrity And Security In Diverse Cloud Environments To Prevent Duplicacy.

Data deduplication is a valuable technique for compressing and minimizing data duplication during data transfers, especially in cloud environments. By eliminating redundant data, it optimizes transmission capacity and reduces memory usage. To ensure the integrity of sensitive data, encryption is applied throughout the deduplication process. The SHA algorithm is commonly used for storing text data during deduplication. It generates security bits by padding the text and computes a hash consisting of hexadecimal, string, and integer data. Hash-based deduplication involves hashing the entire file and treating the hash values of text data as unique identifiers. This allows clients to identify duplicate data within the cloud. The Proof-of-Work (PoW) algorithm is widely utilized in blockchain networks like Bitcoin and Ethereum. Its primary function is to verify transactions through a process called mining. Miners engage in competition to solve complex mathematical problems, and the first one to find a solution is granted the right to add a new block to the blockchain. PoW relies on cryptographic hashing, such as the SHA-256 hashing function, to validate and secure transactions. On the other hand, the Proof of Retrievability (PoR) algorithm finds application in cloud computing systems. It serves as a consensus mechanism, ensuring that cloud storage providers store and retrieve data accurately. PoR enables cloud providers to demonstrate to consumers that their files can be fully recovered. This algorithm incorporates cryptographic proofs that validate the integrity and availability of the stored data. In cloud storage, deduplication is often implemented using the Memory mapping technique (MPT). This allows multiple data owners to store the same data in a single copy, enhancing storage efficiency. To maintain data security, encryption is applied both before and during the deduplication process, ensuring that sensitive information remains protected. In summary, data deduplication is a powerful method for compressing data, minimizing duplication, and optimizing transmission capacity. With encryption techniques and hash-based identification, it provides secure and efficient deduplication in cloud environments, while memory deduplication and MPT support further enhance performance and storage efficiency.

Blockchain‐based data deduplication using novel content‐defined chunking algorithm in cloud environment

AbstractThe cloud environment is inherently dynamic as users are added immensely in a short duration. It is indeed difficult to manage such user profiles and associated data. Meanwhile, the cloud data expand at a twofold‐to‐threefold rate on average, making storage space management and data integrity maintenance a mandatory task but also risky. The main approaches for addressing these data maintenance challenges in a cloud context are deduplication and data protection. In order to manage storage space, finding and removing identical copies of the same data from the cloud are possible, resulting in a reduction in the amount of storage space needed. Furthermore, duplicate copies are considerably reduced in cloud storage owing to data deduplication. Here, a decentralized ledger public blockchain network is introduced to protect the Integrity of data stored in cloud storage. This research proposes data deduplication using speedy content‐defined Chunking (SpeedyCDC) algorithm in the public blockchain. Many people and businesses outsource sensitive data to remote cloud servers because it considerably eliminates the hassle of managing software and infrastructure. However, the ownership and control rights of users data are nonetheless divided because it is outsourced to cloud storage providers (CSPs) and kept on a distant cloud. As a result, users have a great deal of difficulty in verifying the Integrity of sensitive data. Analysis using datasets from Geospatial Information Systems (GIS) revealed that the throughput increased by 5%–6% over that of the fastCDC technique, which offered Integrity since a blockchain network secured it.

Similarity-based deduplication and secure auditing in IoT decentralized storage

Data storage is becoming more difficult due to the network technology’s rapid development, especially with the significant advancement in Internet of Things (IoT). To solve this problem, various cloud storage-based deduplication schemes have been extensively studied to alleviate the storage burden of local IoT devices. However, recent evidence has revealed the deficiencies of these centralized data management schemes related to poor adaptability and lack of resistance to the single point of failure. Most existing deduplication approaches only perform deduplication on the same data, lacking consideration of the IoT data similarity characteristics. Also, these approaches keep only one copy of all data stored on the cloud server, making them valid only if the cloud storage provider is fully trustable, and the applicability of the solution is significantly reduced. What is important, outsourcing storage takes away control of data from their owners, security audits thus should also be considered in secure data storage research. To tackle these issues, we propose a similarity-based deduplication and secure auditing in the IoT decentralized storage scheme. Specifically, our scheme utilizes a novel similarity-based deduplication method based on the multi-server storage model to achieve efficient space saving while protecting data security. Furthermore, the proposed scheme ensures the integrity and availability of data by introducing similarity-based proofs of data ownership and similarity-based data integrity auditing. On this basis, our scheme further adopts a similarity-based secure auditing mechanism to achieve decentralized public auditing without the third-party auditor, in which the audit results of outsourced data are shared on blockchain to avoid repetitive audit tasks. We verify the correctness and effectiveness of our proposed scheme through rigorous theoretical analysis and extensive experimental results.

Smart contract-based integrity audit method for IoT

With the widespread adoption of Internet of Things (IoT) technology, a large amount of private data has been generated. Due to the limited computing and storage resources of IoT devices, enterprises and individuals choose to use a cloud storage provider (CSP) to manage their data. However, they lose the actual control of the data, and hence users need to verify the integrity of the data in the cloud. As a result, reducing the computational overhead of integrity auditing tasks for massive amounts of data and optimizing the distribution of benefits among the participants have become the key to the healthy development of IoT technologies. This paper proposes an integrity auditing method based on smart contracts. First, we construct a noninteractive auditing model based on a chaotic system so that the third-party auditor (TPA) can complete the auditing task without challenging the CSP. Second, we proposed a new construction method for audit trees that can quickly generate the verification tag of the root node. Finally, we design a smart contract-based auditing algorithm on the blockchain, which can simultaneously verify the behaviour of the CSP and the TPA to achieve fair payments. The theoretical analysis shows that our scheme can effectively prevent the TPA from falsifying audit results and prevent collusion between the TPA and the CSP. The experimental results show that our scheme has higher audit efficiency.

A lightweight encrypted deduplication scheme supporting backup

Data deduplication technology is frequently used by many cloud service providers to handle the exponential growth in data. To protect their data privacy, users frequently encrypt their data before uploading it to a cloud storage provider. Therefore, efficient encrypted deduplication technology has been widely studied. Although cloud storage provides convenience for users, it also has the problem of high data concentration. Once an accident occurs in the data center, the impact is enormous. Therefore, it is necessary to back up the ciphertext data after deduplication. In this paper, we propose an efficient encrypted data deduplication technology that supports backup. Our scheme uses a one-way hash chain to verify the legitimacy of a user’s identity. It updates the user’s ownership of the data using the user’s index table. In this paper, we use the XOR operation to re-encrypt data to obtain backup ciphertext, reducing computational complexity. In LEDB, the user can extract the key from the data label. Therefore, the user does not need to manage the key separately. In addition, LEDB supports a two-level deduplication mechanism, which can not only ensure transmission security but also reduce network transmission bandwidth. Finally, LEDB allows the user to determine the integrity of the data before decrypting the ciphertext. Security analysis and experimental results show that our scheme is secure and efficient for data encryption and decryption.

An integrated group decision-making technique under interval-valued probabilistic linguistic T-spherical fuzzy information and its application to the selection of cloud storage provider

<abstract> <p>Cloud storage is crucial in today's digital era due to its accessibility, scalability, cost savings, collaboration and enhanced security features. The selection of a reliable cloud storage provider is a significant multi-attribute group decision-making (MAGDM) problem that involves intrinsic relationships among the various alternatives, attributes and decision DMs. Due to the uncertain and incomplete nature of the evaluation data for cloud storage providers, i.e., quality of service and user feedback, the identification of appropriate cloud storage providers with accurate service ranking remains an open research challenge. To address the above-mentioned challenge, this work proposes the concept of interval-valued probabilistic linguistic T-spherical fuzzy set (IVPLt-SFS). Then, some basic operations and a score function are defined to compare two or more IVPLt-SF numbers (IVPLt-SFNs). For information fusion, two aggregation operators for IVPLt-SFN are also developed. Next, an extended TOPSIS method-based group decision-making technique under interval-valued probabilistic linguistic T-spherical fuzzy information is established to solve the MAGDM problem. Finally, a numerical example is given to illustrate the practicability and usefulness of the designed approach and its suitability as a decision-making tool for selecting a cloud storage provider. Comparative and sensitivity analysis confirmed that this paper enriches the theory and methodology of the selection problem of cloud storage provider and MAGDM analysis.</p> </abstract>

VeriDedup: A Verifiable Cloud Data Deduplication Scheme With Integrity and Duplication Proof

Data deduplication is a technique to eliminate duplicate data in order to save storage space and enlarge upload bandwidth, which has been applied by cloud storage systems. However, a cloud storage provider (CSP) may tamper user data or cheat users to pay unused storage for duplicate data that are only stored once. Although previous solutions adopt message-locked encryption along with Proof of Retrievability (PoR) to check the integrity of deduplicated encrypted data, they ignore proving the correctness of duplication check during data upload and require the same file to be derived into same verification tags, which suffers from brute-force attacks and restricts users from flexibly creating their own individual verification tags. In this paper, we propose a verifiable deduplication scheme called VeriDedup to address the above problems. It can guarantee the correctness of duplication check and support flexible tag generation for integrity check over encrypted data deduplication in an integrative way. Concretely, we propose a novel Tag-flexible Deduplication-supported Integrity Check Protocol (TDICP) based on Private Information Retrieval (PIR) by introducing a novel verification tag called <inline-formula><tex-math notation="LaTeX">${note\ set}$</tex-math></inline-formula> , which allows multiple users holding the same file to generate their individual verification tags and still supports tag deduplication at the CSP. Furthermore, we make the first attempt to guarantee the correctness of data duplication check by introducing a novel User Determined Duplication Check Protocol (UDDCP) based on Private Set Intersection (PSI), which can resist a CSP from providing a fake duplication check result to users. Security analysis shows the correctness and soundness of our scheme. Simulation studies based on real data show the efficacy and efficiency of our proposed scheme and its significant advantages over prior arts.

CIA: A Collaborative Integrity Auditing Scheme for Cloud Data With Multi-Replica on Multi-Cloud Storage Providers

The emergence of cloud storage has solved many pain points of the traditional storage model. However, the issue of cloud storage data integrity - whether the cloud storage provider has kept the data intact - has raised concerns about cloud storage. Integrity auditing of cloud storage data allows users to know the integrity of the outsourced data without downloading it in its entirety. However it is not enough to know its integrity. Multi-replicas, as a common means of redundancy, improves the reliability of cloud storage data. And storing multi-replicas on multi-cloud storage providers (CSPs) enhances this feature. In a multi-replica multi-CSPs scenario, if the independence of CSPs is given full play and auditing is performed among CSPs, not only the introduction of third party auditor (TPA) can be eliminated, but also the tag generation, which is a huge computational overhead, can be removed. Inspired by this, in this paper we propose a new model for remote data integrity auditing: CIA (Collaborative Integrity Auditing). In addition to the reduction in computational overhead, the proposed scheme provides unprecedented support for free data blocking. The proposed scheme employs only hash functions in the calculation, which has a negligible computational overhead compared to the traditional bilinear pairing-based schemes. Theoretical analysis and experimental results show that the proposed scheme provides high efficiency and flexibility with security assurance, and can be used as a lightweight alternative to traditional remote data integrity auditing schemes in multi-replica multi-CSP scenarios.

Dynamic Volume-Hiding Encrypted Multi-Maps with Applications to Searchable Encryption

We study encrypted storage schemes where a client outsources data to an untrusted third-party server (such as a cloud storage provider) while maintaining the ability to privately query and dynamically update the data. We focus on encrypted multi-maps (EMMs), a structured encryption (STE) scheme that stores pairs of label and value tuples. EMMs allow queries on labels and return the associated value tuple. As responses are variable-length, EMMs are subject to volume leakage attacks introduced by Kellaris et al. [CCS'16]. To prevent these attacks, volume-hiding EMMs were introduced by Kamara and Moataz [Eurocrypt'19] that hide the label volumes (i.e., the value tuple lengths). As our main contribution, we present the first fully dynamic volume-hiding EMMs that are both asymptotically and concretely efficient. Furthermore, they are simultaneously forward and backward private which are the de-facto standard security notions for dynamic STE schemes. Additionally, we implement our schemes to showcase their concrete efficiency. Our experimental evaluations show that our constructions are able to add dynamicity with minimal to no additional cost compared to the prior best static volume-hiding schemes of Patel et al. [CCS'19].

A forensic analysis of rclone and rclone's prospects for digital forensic investigations of cloud storage

Organizations and end users are moving their data into the cloud and trust Cloud Storage Providers (CSP) such as pCloud, Dropbox, or Backblaze. Given their popularity, it is likely that forensic examiners encounter one or more online storage types that they will have to acquire and analyze during an investigation. To access cloud storage, CSPs provide web-interfaces, proprietary software solutions (e.g., Dropbox client for Windows) as well as APIs allowing third-party access. One of these third-party applications is rclone which is an open-source tool to access many common CSPs through a command line interface. In this article, we look at rclone from two perspectives: First, we perform a forensic analysis on rclone and discuss aspects such as password recovery of the configuration file, encryption, and JA3 fingerprints. Second, we discuss rclone as a prospect to be a forensic tool which includes its read-only mount feature and sample cases. Under the circumstances tested, rclone is suitable for forensic practitioners as it is open-source, documented, and includes some essential functionality frequently needed but practitioners need to be aware of the caveats.

Implementing Security in Fog Computing

Abstract: In Fog computing, services can be hosted at end devices such as set-top-boxes or access points. The infrastructure of this new distributed computing allows applications to run as close as possible to sensed actionable and massive data, coming out of people, processes and thing. Such Fog computing concept, actually a Cloud computing close to the ‘ground’, creates automated response that drives the value. As the data generation rates are increasing, it is a tedious task for cloud storage providers to provide efficient storage. Cloud storage providers use different techniques to improve storage efficiency and one of leading technique employed by them is de-duplication. Data once deployed to cloud servers, its beyond the security premises of the data owner, thus most of them prefer to outsource their in an encrypted format. We also propose efficient approach for encryption for providing security on fog computing.

Secure File Storage on Cloud Using Hybrid Cryptography

Cloud is used in various fields like industry, military, college, etc. for various services and storage of huge amount of data. Data stored in this cloud can be accessed or retrieved on the users request without direct access to the server computer. The rapidly increased use of cloud computing within the many organization and IT industries provides new software with low cost. Cloud computing is useful in terms of low cost and accessibility of knowledge. Cloud computing gives lot of advantages with low cost and of knowledge accessibility through Internet. Ensuring the safety of cloud computing may be a major think about the cloud computing environment, as users often store sensitive information with cloud storage providers, but these providers could be untrusted. So, sharing data in a secure manner while preserving data from an untrusted cloud remains a challenging issue. Our approach ensures the safety and privacy of client sensitive information by storing data across single cloud, using AES, triple DES and Blowfish algorithm.