Cloud Storage Providers Research Articles

Privacy-Preserving Proof of Storage for the Pay-As-You-Go Business Model

Proof of Storage (PoS) enables a cloud storage provider to prove that a client’s data is intact. However, existing PoS protocols are not designed for the pay-as-you-go business model in which payment is made based on both storage volume and duration. In this paper, we propose two PoS protocols suitable for the pay-as-you-go storage business model. The first is a time encapsulated Proof of Retrievability (PoR) protocol that ensures retrievability of the original file upon successful auditing by a client. Considering the large size of outsourced data, we then extend the protocol to a privacy-preserving public auditing protocol which allows a third party auditor to audit outsourced data on behalf of its clients without sacrificing the privacy of the data or the timestamp (i.e., time of storage). We formalize the definition, system model and security model of the proposed PoS system and prove the security of the proposed protocols by a sequence of games in the algebraic group model with a random oracle. We analyze the performance of the protocols both theoretically and experimentally and show that the protocols are practical.

Integrity Verification Mechanism of Sensor Data Based on Bilinear Map Accumulator

With the explosive growth in the number of IoT devices, ensuring the integrity of the massive data generated by these devices has become an important issue. Due to the limitation of hardware, most past data integrity verification schemes randomly select partial data blocks and then perform integrity validation on those blocks instead of examining the entire dataset. This will result in that unsampled data blocks cannot be detected even if they are tampered with. To solve this problem, we propose a new and effective integrity auditing mechanism of sensor data based on a bilinear map accumulator. Using the proposed approach will examine all the data blocks in the dataset, not just some of the data blocks, thus, eliminating the possibility of any cloud manipulation. Compared with other schemes, our proposed solution has been proved to be highly secure for all necessary security requirements, including tag forgery, data deletion, replacement, replay, and data leakage attacks. The solution reduces the computational and storage costs of cloud storage providers and verifiers, and also supports dynamic operations for data owners to insert, delete, and update data by using a tag index table (TIT). Compared with existing schemes based on RSA accumulator, our scheme has the advantages of fast verification and witness generation and no need to map data blocks to prime numbers. The new solution supports all the characteristics of a data integrity verification scheme.

Inline Deduplication Checking in cloud environment

Inline deduplication is a technique that can reduce the amount of storage space used in a cloud environment. It can also improve restore and backup times. However, it is not always effective due to the various factors that affect the effectiveness of this process. For instance, the type of data that is stored and the method that is used to perform deduplication are all important factors that affect the effectiveness of this solution. The goal of this paper is to provide an overview of the various aspects of inline deduplication and its effectiveness in improving the performance and reducing the cost of storage in a cloud-based environment. We then conduct a case study to demonstrate the efficiency of this process in an Amazon Web Services instance. Experiments were able to demonstrate that in cloud environments, the level of deduplication that is achieved can improve performance and reduce the amount of storage space that is used. In case study, the use of inline deduplication on Amazon Web Services led to a 60% reduction in the storage space usage. After conducting a comprehensive analysis of the various aspects of inline deduplication, we concluded that it is a standard feature that can be used by cloud storage providers to reduce their costs and improve the performance of their customers.

Third Party Risk Management

Every organization relies upon third party vendors for a multitude of business operations. Despite the requirements to rely upon third party vendors, only 52% of organizations have security standards for third party vendors (Matis, 2019, para. 2). Furthermore, a study surveying 608 information technology (IT) professionals indicated that 69% of the respondents either definitely suffered a security breach or possibly suffered a security breach due to vendor access within the year (Bomgar, 2019, p. 2). Finally, a staggering 94.3% of executives possess low to moderate confidence in their third-party risk management tools and technology (Deloitte, 2018, para. 3). These statistics are the direct result of complex business relationships, dynamic information technology exchanges, and a lack of awareness outside of those directly working within the information technology realm. Additionally, the lack of information technology personnel who aspire to upper echelons of business management contribute to the overall risk factors. In June of 2018, Universal Music Group became aware of a massive data breach that exposed file transfer protocol credentials, Amazon Web Services cryptographic keys, and internal passwords due to improper handling of a third-party cloud storage provider. The technical aspects of the breach reveal that a contractor working at the cloud storage provider administered an apache airflow server without password requirements (Cimpanu, 2018, para. 3). The damage has yet to be quantified and it is unclear how many customers this data breach has affected (Cyber GRX, 2019, para. 7). What the data breach represents is something far greater than another data breach amongst many but rather how devastating the effects a single lackadaisical contractor can have for an organization. The Target data breach is a similar example with many more secondary and tertiary effects caused by a single heating, venting, and air conditioning contractor. Risk is generally dealt with through the use of transferring, accepting, avoiding and mitigating (Cannon, 2014, p. 48). Risk transference is the most popular method of handling risk and results in the use of many third-party vendors for organizations (ISACA, 2016, p. 113). When opting to use third party vendors, an organization is choosing to transfer risk due to the inability or lack of feasibility for conducting the action on their own. Across the cyber domain, many organizations opt to place their data in cloud storage as this is scalable and affordable. However, cloud solutions are just as vulnerable to exploitation as an on-premises datacenter (Muncaster, 2019, para. 3). Perhaps the issue rests in the lack of education on vendor risk management. Cyber insurance is another method of transferring risk as the cost of the average data breach continues to grow each year. This paper will aim to underscore the importance of vendor risk management and options organizations have to address such risks.

Users’ Payment Intention considering Privacy Protection in Cloud Storage: An Evolutionary Game‐Theoretic Approach

To solve the current privacy leakage problems of cloud storage services, research on users’ payment intention for cloud storage services with privacy protection is extremely important for improving the sustainable development of cloud storage services. An evolutionary game model between cloud storage users and providers that considers privacy is constructed. Then, the model’s evolutionary stability strategies via solving the replication dynamic equations are analyzed. Finally, simulation experiments are carried out for verifying and demonstrating the influence of model parameters. The results show that the evolutionary stable strategies are mainly affected by the privacy protection profit growth coefficient of both parties, input costs, free‐riding gains, and other factors. If the profit growth coefficient is very small, users will not choose to pay and providers will not choose to actively protect user information. As the profit growth coefficient increases, both parties will promote the development of privacy protection with a higher probability. The results are beneficial for cloud storage providers to increase the number of paid users and thus to achieve the sustainable development of cloud storage service.

Investigating the Adoption of Hybrid Encrypted Cloud Data Deduplication With Game Theory

Encrypted data deduplication, along with different preferences in data access control, brings the birth of hybrid encrypted cloud data deduplication (H-DEDU for short). However, whether H-DEDU can be successfully deployed in practice has not been seriously investigated. Obviously, the adoption of H-DEDU depends on whether it can bring economic benefits to all stakeholders. But existing economic models of cloud storage fail to support H-DEDU due to complicated interactions among stakeholders. In this article, we establish a formal economic model of H-DEDU by formulating the utilities of all involved stakeholders, i.e., data holders, data owners, and Cloud Storage Providers (CSPs). Then, we construct a multi-stage Stackelberg game, which consists of Holder Participation Game, Owner Online Game, and CSP Pricing Game, to capture the interactions among all system stakeholders. We further analyze the conditions of the existence of a sub-game perfect Nash Equilibrium and propose a gradient-based algorithm to help the stakeholders choose near-optimal strategies. Extensive experiments show the feasibility of the proposed algorithm in achieving the Nash Equilibrium of the Stackelberg game. Additionally, we investigate the effects of parameters related to CSP, data owners and data holders on H-DEDU adoption. Our study advises all stakeholders the best strategies to adopt H-DEDU.

Optimizing Information Leakage in Multicloud Storage Services

Many schemes have been recently advanced for storing data on multiple clouds. Distributing data over different cloud storage providers (CSPs) automatically provides users with a certain degree of information leakage control, for no single point of attack can leak all the information. However, unplanned distribution of data chunks can lead to high information disclosure even while using multiple clouds. In this paper, we study an important information leakage problem caused by unplanned data distribution in multicloud storage services. Then, we present StoreSim , an information leakage aware storage system in multicloud. StoreSim aims to store syntactically similar data on the same cloud, thus minimizing the user's information leakage across multiple clouds. We design an approximate algorithm to efficiently generate similarity-preserving signatures for data chunks based on MinHash and Bloom filter, and also design a function to compute the information leakage based on these signatures. Next, we present an effective storage plan generation algorithm based on clustering for distributing data chunks with minimal information leakage across multiple clouds. Finally, we evaluate our scheme using two real datasets from Wikipedia and GitHub . We show that our scheme can reduce the information leakage by up to 60 percent compared to unplanned placement. Furthermore, our analysis on system attackability demonstrates that our scheme makes attacks on information more complex.

Efficient and Enhanced Data Encryption in Cloud Computing

Cloud computing transforms the way information technology (IT) is consumed and managed, promisingimproved cost efficiencies, accelerated innovation, faster time-to-market, and the ability to scaleapplications on demand. However, as the shape of the cloud computing is emerging and developingrapidly both conceptually and in reality, the legal/contractual, economic, service quality,interoperability, security and privacy issues still pose significant challenges. In this project, we describevarious service and deployment models of cloud computing and identify major challenges. In particular,we discuss three critical challenges: security and privacy issues in cloud computing. Some solutionsto mitigate these challenges are also proposed along with a brief presentation on the future trendsin cloud computing deployment. The use of cloud computing has increased rapidly in many organizations.Cloud computing provides many benefits in terms of low cost and accessibility of data. Ensuring thesecurity of cloud computing is a major factor in the cloud computing environment, as users often storesensitive information with cloud storage providers but these providers may not be trusted.

Carp: A cost-aware relaxed protocol for encrypted data stores

Distributed data stores are critical to the success of applications in cloud. Massive volumes of user data are stored and processed with the support of underlying distributed data stores. With large amounts of data stored remotely in the cloud, security becomes a major concern. Authentication and access control are provided by cloud storage providers. But even with proper authentication and access control policies, storage systems are still vulnerable to attackers who have direct access to storage devices such as disks. Encryption makes it computational difficult to retrieve the original data even when the attackers have the access to the disks. However, there are many challenges in designing an encrypted distributed data store that is highly secure and cost-aware.In this paper, we show that security flexibility and cost efficiency can be achieved at the same time. We present Carp, a cost- aware relaxed protocol for encrypted data stores. Carp is a heuristic solution instead of an optimal one. The key idea is to reduce additional encryption operations for frequently accessed data. It is achieved by allowing data objects stay unencrypted for a short time period after the data are accessed. Reducing encryption operations eventually means reducing the computational cost and power consumption in the data store. Unlike conventional encrypted file systems which store data encryption keys on disks, we present a hybrid design of key generation and caching. Data encryption keys are generated for individual objects or a group of them using cryptographic hashing. We develop a prototype data store and conduct experiments. The experimental results show that Carp can reduce up to 20% encryption operations with high-level security.

Privacy Aware Data Deduplication for Side Channel in Cloud Storage

Cloud storage services enable individuals and organizations to outsource data storage to remote servers. Cloud storage providers generally adopt data deduplication, a technique for eliminating redundant data by keeping only a single copy of a file, thus saving a considerable amount of storage and bandwidth. However, an attacker can abuse deduplication protocols to steal information. For example, an attacker can perform the duplicate check to verify whether a file (e.g., a pay slip, with a specific name and salary amount) is already stored (by someone else), hence breaching the user privacy. In this paper, we propose $\mathsf{ZEUS}$ ZEUS ( ze ro-knowledge ded u plication re s ponse) framework. We develop $\mathsf{ZEUS}$ ZEUS and $\mathsf{ZEUS}$ ZEUS $^+$ + , two privacy-aware deduplication protocols: $\mathsf{ZEUS}$ ZEUS provides weaker privacy guarantees while being more efficient in the communication cost, while $\mathsf{ZEUS}$ ZEUS $^+$ + guarantees stronger privacy properties, at an increased communication cost. To the best of our knowledge, $\mathsf{ZEUS}$ ZEUS is the first solution which addresses two-side privacy by neither using any extra hardware nor depending on heuristically chosen parameters used by the existing solutions, thus reducing both cost and complexity of the cloud storage. In summary, through the evaluation on real datasets and comparison to existing solutions, our proposed framework demonstrates its capability of eliminating data deduplication-based side channel and at the same time keeping the deduplication benefits.

Enhancing Audit using Trace Logs Encrypted through User Secret Key Encryption Protocol in Multi Cloud Storage Management Application

Cloud computing is a technology for sharing the resources for on demand request and for processing the data . V V arious cloud storage providers (CSP) offers free and premium cloud storage spaces. Multi cloud storage management application provides a single unified interface to access all the connected storage spaces to obtain quick accessibility removing the effort and time involved in switching between CSPs to access data hosted in different CSPs. Authenticated accessibility ensures a secured environment but provision to audit the actions performed to verify the history of actions is required for auditing to ensure the data and application integrity. Observing and registering a Trace Log for each and every actions performed by each user will facilitate and assure the process of auditing. In order to secure the Trace Logs of each user from unauthorized access of other users, encryption can be employed using user specific secret key. This approach will ensure both security and authorization for the Trace Logs.

Peer-to-Peer Sharing of Subscription Services: A Non-Discriminatory Approach to Price Discrimination with Resale

Resale of used products may shrink the new-product market and create the cannibalization problem. This problem is exacerbated in the digital goods market because copies of digital goods can be perfect substitutes of the original. Many digital goods/service producers take advantage of technology (e.g., digital rights management or DRM) to restrict resale of their digital products. In this paper, we posit that resale of digital goods may not necessarily be a concern. Instead, product resale can be an effective tool of managing heterogeneous demand---thanks to the traceability of resale and the control over usage allowance. Specifically, we consider a digital goods/service seller, e.g., an e-book platform, a telecommunication carrier or a cloud storage provider, who offers a contract to a group of heterogeneous customers at a fixed price for a specific amount of usage allowance. Instead of implementing restrictive barriers to sharing, in this contract subscribers are allowed to share their allowances with others in a peer-to-peer resale market at a transaction cost that is determined by the seller. We characterize the optimal terms of the sharing contract and quantify its performance. We find that the seller's optimal strategy is to facilitate reselling by imposing zero transaction cost. The sharing contract achieves the same outcome as a two-part tariff, in which subscribers pay first an entry fee for the access to the service and then a marginal rate of usage. Not only do they yield identical revenue, they also achieve the same market coverage and result in the same demand and individual surplus for customers of the same type. Therefore, the sharing contract is effectively a vehicle of price discrimination. This finding also challenges a conventional belief that the success of price discrimination has to be relying on the prevention of reselling. Our result demonstrates that resale is not necessarily detrimental to price discrimination: resale is instead a necessary condition for price discrimination if the digital goods/service contract can be written on terms of price and usage allowance.

Optimizing Data Placement for Cost Effective and High Available Multi-Cloud Storage

With the advent of big data age, data volume has been changed from trillionbyte to petabyte with incredible speed. Owing to the fact that cloud storage offers the vision of a virtually infinite pool of storage resources, data can be stored and accessed with high scalability and availability. But a single cloud-based data storage has risks like vendor lock-in, privacy leakage, and unavailability. Multi-cloud storage can mitigate these risks with geographically located cloud storage providers. In this storage scheme, one important challenge is how to place a user's data cost-effectively with high availability. In this paper, an architecture for multi-cloud storage is presented. Next, a multi-objective optimization problem is defined to minimize total cost and maximize data availability simultaneously, which can be solved by an approach based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions called the Pareto-optimal set. Then, a method is proposed which is based on the entropy method to determine the most suitable solution for users who cannot choose one from the Pareto-optimal set directly. Finally, the performance of the proposed algorithm is validated by extensive experiments based on real-world multiple cloud storage scenarios.

Secure the Data by using Image Compression in Multi-Cloud Storage

Cloud storage providers are in ability for trust the data available and accessible that makes physical condition to be secure and running. Organizations bargain storage capacity from the providers to store user data, business, or request data. Clients desires to furnish their data to public cloud servers (PCSs). Recently got security troubles take to solve and aid more client’s improvement their records in multi-cloud Storage. The customers allow saving information in the cloud the use of services supplied by using more than one cloud storage companies (CSPs). It is a hopeful method to enlarge the degree of records availability and confidentiality, as all at once these distinctive CSPs are out of provider at the identical time or collude with each other to extract records of a user. This suggest a survey on the viable protection merits by means of creating use of multiple wonderful clouds at the identical time. In addition, this advice work as merging and splitting standards at some point of storage in cloud environment. In file access, personal keys produced the use of digital key generator. 3DES encryption algorithm generates key in a cipher text format to the users. Towards facts confidentiality, this advocate an assured facts hiding and spitting picture technique in cloud storage. In propose work, essential purpose will be photo compression with mutable statistics hiding approach whilst storing in the real cloud for data hiding & photo compression via the use of Discrete Wavelet Transform (DWT) algorithm.

Cloud storage security assessment through equilibrium analysis

With ever greater amounts of data stored in cloud servers, data security and privacy issues have become increasingly important. Public cloud storage providers are semi-trustworthy because they may not have adequate security mechanisms to protect user data from being stolen or misused. Therefore, it is crucial for cloud users to evaluate the security of cloud storage providers. However, existing security assessment methods mainly focus on external security risks without considering the trustworthiness of cloud providers. In addition, the widely used third-party mediators are assumed to be trusted and we are not aware of any work that considers the security of these mediators. This study fills these gaps by assessing the security of public cloud storage providers and third-party mediators through equilibrium analysis. More specifically, we conduct evaluations on a series of game models between public cloud storage providers and users to thoroughly analyze the security of different service scenarios. Using our proposed security assessment, users can determine the risk of whether their privacy data is likely to be hacked by the cloud service providers; the cloud service providers can also decide on strategies to make their services more trustworthy. An experimental study of 32 users verified our method and indicated its potential for real service improvement.

An Authorized ClouDedup in Hybrid Cloud using Triple Data Encryption Standard

Nowadays, data deduplication has become more essential for cloud storage providers because of continuous increase in number of users and their data file size. The users are allowed to access server anytime and anywhere to upload/download their data file. Whenever data is retrieving, it leads to several problems associated to the confidentiality and privacy. For protection of data security, we proposed an efficient technique called ClouDedup which assures file deduplication. To secure the confidentiality of critical data while supporting ClouDedup checker, we proposed a triple data encryption standard (TDES) technique to encrypt the data prior to uploading the data file in cloud storage. The privilege level of user is verified with data to assure whether he is an authorized user or not. The analysis of security demonstrates that our proposed security method is safe and secure. We prove that our proposed ClouDedup method has minimal overhead compared to normal operations. The process aims to use authorized ClouDedup checker with a triple data encryption standard (TDES) technique to minimize duplication copies of data in hybrid cloud storage and conducted test experiments using our prototype.

Cloud Data Storage using Attribute based Encryption with Verifiable Outsourcing Auditor Security Schemes

Cloud storage services turned out to be continuously elegant. Owing to the implication of security, a few cloud storage secret composing schemes are anticipated to monitor data from those that don't approach. Every single such plan accepted that cloud storage providers region unit safe and can't be hacked; at the same time, in pursue, a few experts may drive cloud storage providers to uncover client insider facts or confidential data on the cloud, hence by and large going around storage mystery composing schemes. Amid this paper, we tend to bless our style for a pristine cloud storage mystery composing subject that permits cloud storage providers to make persuading false client privileged insights to protect client security. Since coercers can't reveal whenever acquired insider facts zone unit genuine or not, the cloud storage providers ensure that client security keeps on being immovably secured. The vast majority of the anticipated schemes expect cloud storage service providers or dependable outsiders taking care of key administration square measure solid and can't be hacked; nonetheless, in pursue, a few substances would conceivably capture interchanges among clients and cloud storage providers at that point urge storage providers to unfasten client privileged insights by misuse government control or diverse proposes that. All through this case, scrambled information square measure thought to be known and storage provider's square measure asked for to unfasten client insider facts

Distributed Personal Cloud Storage without Third Parties

We present the “It's My Data file system” (IMDfs), a personal, version-tracking, distributed file system that allows users to take custody of their cross-device data management needs, without depending on cloud storage providers. Such a system may be desirable to privacy-conscious users, who worry about the increasing number of cloud storage incidents involving data leakage and corruption, or simply want to synchronize their devices without depending on third parties. IMDfs provides a global, unified view of a user's distributed data collection from any device, user-controlled replication of data across devices, transparent remote access, and support for non-restrictive conflict management. IMDfs achieves all this without sacrificing fault-tolerance or performance and with modest storage overhead. We present the design, implementation, and detailed performance evaluation of IMDfs using benchmarks and traces from real workloads, and we demonstrate that: 1) IMDfs, as a local file system, has reasonable overhead compared with a FUSE loopback file system and Wayback, a local versioning file system, and 2) IMDfs, as a network file system, outperforms NFS and Ori, a state-of-the-art file system for cross-device data management.

Encryption Technique to Optimize Information Leakage in Multi Cloud Storage Services

Multicloud is one such aspect which is considered as the vision of the future. It includes distribution of data for the user automatically by means of cloud storage providers (CSPs) which in turn provides a considerable degree of control over information leakage. Due to the process of unplanned distribution of data chunks will result in disposing the crucial information while using multiple clouds. A storage system named Storesim is introduced in Multicloud to store syntactically relevant data on the assigned cloud, thereby limiting the intensity of leakage of information across those clouds. During this survey it has been identified that few CSP’s of some Multicloud services got compromised under coercion. In this paper, we made use of the Ultramodern Encryption Standard (UES) into storesim thereby avoiding unauthorized access to the information present in the Multicloud ensuring better level of security to CSP’s implicating reduced information leakage

CloudDBGuard: A framework for encrypted data storage in NoSQL wide column stores

Nowadays, cloud storage providers are widely used for outsourcing data. These remote cloud servers are not trustworthy when storing sensitive data. In this article we focus on the use case of storing data in a cloud database using a particular sub-category of NoSQL databases — so-called wide column stores. Unfortunately security was not a primary concern of the NoSQL systems designers. Using encryption before outsourcing the data can provide security. Conventional encryption however limits the options for interaction because the encrypted data lacks properties of the plaintext data that the database systems rely on. Various schemes have been proposed for property-preserving encryption in order to overcome these issues, allowing a database to process queries over encrypted data. In this article we comprehensively present details of our framework CloudDBGuard that allows using property-preserving encryption in unmodified wide column stores. It hides the complexity of the encryption and decryption process and allows various adjustments on specific use cases in order to achieve a maximum of security, functionality and performance.