Ownership Of File Research Articles

Why Can’t I just use Dropbox? A comparison of cloud file storage platforms used for research

Objective: Many researchers use cloud file storage platforms such as Box and Google Drive as the sole data management platform for all of their research data throughout the course of their projects. Researchers have lost access to their preferred platforms due to changes in licensing agreements and cost to their institutions, leaving researchers to figure out a new system on their own. This paper describes differences between these platforms that affect research data workflows. Methods: We selected four commonly used cloud file storage vendors (Box, Dropbox, Google Drive, and Microsoft SharePoint/OneDrive) to assess. The authors read public user documentation for the platforms and identified several differences, such as maximum file size, that could affect research data workflows. For each difference, we recorded the specifics of each platform then narrowed the scope to features that vary across the platforms. Results: We identified three areas where cloud platforms differed in ways that affect data management: data stewardship, storage capacity, and file organization. Data stewardship is affected by variations in the platforms’ approaches to individual vs. group ownership of files and how user roles are defined and assigned. The platforms also differ in limits on total capacity, individual file size, total number of files, and the amount of data that can be moved in and out of the platform. Some of these limits vary by access method (e.g. API vs web interfaces). Finally many differences affect how data can be organized, such as number of files per folder, synchronization, and file sharing restrictions. Conclusions: Some research data workflows may be negatively affected by moving between cloud file storage platforms. Researchers will need assistance identifying differences between the platforms and modifying disrupted data workflows. 

SecDedup: Secure data deduplication with dynamic auditing in the cloud

In the era of big data, data explosion has brought challenges to cloud storage management. To improve cloud storage efficiency and save network communication bandwidth, cloud data deduplication has emerged as a research hotspot, especially in the field of encrypted cloud data storage. How to enhance the security of encrypted data deduplication by resisting various attacks on deduplication has become an important research issue. However, existing solutions suffer from security flaws and are vulnerable to a series of attacks, e.g., duplicate faking attacks, file ownership spoofing attacks, and file tampering attacks. Besides, dynamic data operation is rarely considered or audited. To solve the above problems, we propose a novel scheme, named SecDedup, to enhance the security of encrypted cloud data deduplication with dynamic auditing. SecDedup applies a homomorphic authenticator and designs a multi-functional data tag with optimized storage to support deduplication and auditing at the same time with security guarantee against various attacks as mentioned above. In particular, We embed multi-set hash functions into data tags to achieve dynamic data auditing. In addition, SecDedup supports batch auditing with optimized computational cost for multiple deduplication auditing tasks. We formally prove the correctness and security of SecDedup, showing that it can successfully achieve our design goals for resisting the above listed attacks. We also analyze and evaluate the performance of SecDedup in terms of computation, communication, and tag storage overheads by comparing them with existing works. The results show its effectiveness and scalability.

Dual Traceable Distributed Attribute-Based Searchable Encryption and Ownership Transfer

In this paper, we propose dual traceable distributed attribute based encryption with subset keyword search system (DT-DABE-SKS, abbreviated as DT) to simultaneously realize data source trace (secure provenance) and user trace (traitor trace) and flexible subset keyword search from polynomial interpolation. Leveraging non-interactive zero-knowledge proof technology, DT preserves privacy for both data providers and users in normal circumstances, but a trusted authority can disclose their real identities if necessary, such as the providers deceitfully uploading false data or users maliciously leaking secret attribute key. Next, we introduce the new conception of updatable and transferable message-lock encryption (UT-MLE) for block-level dynamic encrypted file update, where the owner does not have to download the whole ciphertext, decrypt, re-encrypt and upload for minor document modifications. In addition, the owner is permitted to transfer file ownership to other system customers with efficient computation in an authenticated manner. A nontrivial integration of DT and UT-MLE lead to the distributed ABSE with ownership transfer system (DTOT) to enjoy the above merits. We formally define DT, UT-MLE, and their security model. Then, the instantiations of DT and UT-MLE, and the formal security proof are presented. Comprehensive comparison and experimental analysis based on real dataset affirm their feasibility.

Privacy-Enhanced Data Deduplication Computational Intelligence Technique for Secure Healthcare Applications

A significant number of cloud storage environments are already implementing deduplication technology. Due to the nature of the cloud environment, a storage server capable of accommodating large-capacity storage is required. As storage capacity increases, additional storage solutions are required. By leveraging deduplication, you can fundamentally solve the cost problem. However, deduplication poses privacy concerns due to the structure itself. In this paper, we point out the privacy infringement problem and propose a new deduplication technique to solve it. In the proposed technique, since the user’s map structure and files are not stored on the server, the file uploader list cannot be obtained through the server’s meta-information analysis, so the user’s privacy is maintained. In addition, the personal identification number (PIN) can be used to solve the file ownership problem and provides advantages such as safety against insider breaches and sniffing attacks. The proposed mechanism required an additional time of approximately 100 ms to add a IDRef to distinguish user-file during typical deduplication, and for smaller file sizes, the time required for additional operations is similar to the operation time, but relatively less time as the file’s capacity grows.

Bidirectional and Malleable Proof-of-Ownership for Large File in Cloud Storage

Cloud storage is a cost-effective platform to accommodate massive data at low cost. However, advances of cloud services propel data generation, which pushes storage servers to its limit. Deduplication is a popular technique enjoyed by most current cloud servers, which detects and deletes redundant data to save storage and bandwidth. For security concerns, proof-of-ownership (PoW) can be used to guarantee ownership of data such that no malicious user could pass deduplication easily or utilize such mechanism for malicious purposes. Generally, PoW is implemented in static data archive where the data file is supposed to be read-only. However, to satisfy users’ needs for dynamical manipulation on data and support real-time data services, it is required to devise efficient PoW for dynamic archive. Inspired by malleable signature, which offers authentication even after its committed message changes, we propose the notion of bidirectional and malleable proof-of-ownership ( <inline-formula><tex-math notation="LaTeX">$\sf {BM\mbox{-}PoW}$</tex-math></inline-formula> ) for the above challenge. Our proposed <inline-formula><tex-math notation="LaTeX">$\sf {BM\mbox{-}PoW}$</tex-math></inline-formula> consists of bidirectional PoW ( <inline-formula><tex-math notation="LaTeX">${\mbox{B-PoW}}$</tex-math></inline-formula> ), malleable PoW ( <inline-formula><tex-math notation="LaTeX">${\mbox{M-PoW}}$</tex-math></inline-formula> ) and dispute arbitration protocol <inline-formula><tex-math notation="LaTeX">$\sf {DAP}$</tex-math></inline-formula> . While our <inline-formula><tex-math notation="LaTeX">${\mbox{B-PoW}}$</tex-math></inline-formula> is proposed for a static setting, the <inline-formula><tex-math notation="LaTeX">${\mbox{M-PoW}}$</tex-math></inline-formula> caters specifically for dynamic manipulation of data. In addition, our proposed arbitration protocol <inline-formula><tex-math notation="LaTeX">$\sf {DAP}$</tex-math></inline-formula> achieves accountable redaction which can arbitrate the originality of file ownership. We provide the security analysis of our proposal, and performance evaluation that suggests our proposed <inline-formula><tex-math notation="LaTeX">${\mbox{B-PoW}}$</tex-math></inline-formula> is secure and efficient for large file in static data archive. In addition, our proposed <inline-formula><tex-math notation="LaTeX">${\mbox{M-PoW}}$</tex-math></inline-formula> achieves acceptable performance under dynamic setting where data is supposed to be outsourced first and updated later in dynamic data archive.

Examining the stability of logging statements

Logging statements (embedded in the source code) produce logs that assist in understanding system behavior, monitoring choke-points and debugging. Prior work showcases the importance of logging statements in operating, understanding and improving software systems. The wide dependence on logs has lead to a new market of log processing and management tools. However, logs are often unstable, i.e., the logging statements that generate logs are often changed without the consideration of other stakeholders, causing sudden failures of log processing tools and increasing the maintenance costs of such tools. We examine the stability of logging statements in four open source applications namely: Liferay, ActiveMQ, Camel and CloudStack. We find that 20–45% of their logging statements change throughout their lifetime. The median number of days between the introduction of a logging statement and the first change to that statement is between 1 and 17 in our studied applications. These numbers show that in order to reduce maintenance effort, developers of log processing tools must be careful when selecting the logging statements on which their tools depend. In order to effectively mitigate the issues that are caused by unstable logging statements, we make an important first step towards determining whether a logging statement is likely to remain unchanged in the future. First, we use a random forest classifier to determine whether a just-introduced logging statement will change in the future, based solely on metrics that are calculated when it is introduced. Second, we examine whether a long-lived logging statement is likely to change based on its change history. We leverage Cox proportional hazards models (Cox models) to determine the change risk of long-lived logging statements in the source code. Through our case study on four open source applications, we show that our random forest classifier achieves a 83–91% precision, a 65–85% recall and a 0.95–0.96 AUC. We find that file ownership, developer experience, log density and SLOC are important metrics in our studied projects for determining the stability of logging statements in both our random forest classifiers and Cox models. Developers can use our approach to determine the risk of a logging statement changing in their own projects, to construct more robust log processing tools, by ensuring that these tools depend on logs that are generated by more stable logging statements.

An efficient confidentiality-preserving Proof of Ownership for deduplication

Data storage in the cloud is becoming widespread. Deduplication is a key mechanism to decrease the operating costs cloud providers face, due to the reduction of replicated data storage. Nonetheless, deduplication must deal with several security threats such as honest-but-curious servers or malicious users who may try to take ownership of files they are not entitled to. Unfortunately, state-of-the-art solutions present weaknesses such as not coping with honest-but-curious servers, deployment problems, or lacking a sound security analysis. In this paper we present a novel Proof of Ownership scheme that uses convergent encryption and requires neither trusted third parties nor complex key management. The experimental evaluation highlights the efficiency and feasibility of our proposal that is proven to be secure under the random oracle model in the bounded leakage setting.

An empirical study of the effect of file editing patterns on software quality

ABSTRACTDevelopers might follow different file editing patterns when handling change requests. Existing research has warned the community about the potential negative impacts of some file editing patterns on software quality. However, very few studies have provided quantitative evidence to support these claims. In this paper, we propose four metrics to identify four file editing patterns: concurrent editing pattern, parallel editing pattern, extended editing pattern, and interrupted editing pattern. Our empirical study on three open source projects shows that 90% (i.e. 1935 out of 2140) of files exhibit at least one file editing pattern. More specifically (1) files that are edited concurrently by many developers are 1.8 times more likely to experience future bugs than files that are not concurrently edited; (2) files edited in parallel with too many other files by the same developer are 2.9 times more likely to exhibit future bugs than files individually edited; (3) files edited over an extended period of time are 1.9 times more likely to experience future bugs than other files; and (4) files edited with long interruptions have 2.0 times more future bugs than other files. We also observe that the likelihood of future bugs in files experiencing all the four file editing patterns is 3.9 times higher than in files that are never involved in any of the four patterns. We further investigate factors impacting the occurrence of these file editing patterns along three dimensions: the ownership of files, the type of change requests in which the files were involved, and the initial code quality of the files. Results show that a file with a major owner is 0.6 times less likely to exhibit the concurrent editing pattern than files without major owners. Files with bad code quality (e.g. high McCabe's complexity, high coupling between objects, and lack of cohesion) are more likely to experience the four editing patterns. By ensuring a clear ownership and improving code quality, the negative impact of the four patterns could be reduced. Overall, our findings could be used by software development teams to warn developers about risky file editing patterns. Copyright © 2014 John Wiley &amp; Sons, Ltd.

Provable ownership of files in deduplication cloud storage

AbstractWith the rapid adoption of cloud storage services, a great deal of data is being stored at remote servers, so a new technology, client‐side deduplication, which stores only a single copy of repeating data, is proposed to identify the client's deduplication and save the bandwidth of uploading copies of existing files to the server. It was recently found, however, that this promising technology is vulnerable to a new kind of attack in which by learning just a small piece of information about the file, namely its hash value, an attacker is able to obtain the entire file from the server. In this paper, to solve this problem, we propose a cryptographically secure and efficient scheme for a client to prove to the server his ownership on the basis of actual possession of the entire original file instead of only partial information about it. Our scheme utilizes the technique of spot checking in which the client only needs to access small portions of the original file, dynamic coefficients and randomly chosen indices of the original files. Our extensive security analysis shows that the proposed scheme can generate provable ownership of the file and maintain high detection probability of client misbehavior. Both performance analysis and simulation results demonstrate that our proposed scheme is much more efficient than the existing schemes, especially in reducing the burden of the client. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Media analyses based on Microsoft ® NTFS file ownership

The ever-increasing size of digital media presents a continuous challenge to digital investigators who must rapidly assess computer media to find and identify evidence. To meet this challenge, methods must continuously be sought to expedite the examination process. This paper investigates using the file ownership property as an analytical tool focusing on activity by individuals associated with the computer. Research centered on the New Technology File System (NTFS), which is the default file system in Microsoft ® Windows Operating System (OS). This was done because Microsoft ®'s worldwide market penetration makes Windows ® and NTFS the most likely OS and file system to be encountered in digital forensic examinations. Significantly, digital forensic software now allows examination of NTFS file attributes and properties including the ownership property. The paper outlines potential limitations regarding interpreting ownership findings, and suggests areas for further research. Overall, file ownership is seen as a potentially viable new digital forensic tool.