Cloud File Research Articles

An Efficient Adaptive Load Balancing Scheme for Mitigating Reduction of Quality-Based DDOS Attack on Cloud File Storage Environment

Availability of cloud resources to the cloud users is considered as the serious challenge that pose security essentialities during the process of on-demand service provision. Moreover, a specific type of attack named Reduction of Quality (RoQ)-based DDoS attack is determined to be vulnerable in the cloud computing since it exploits the benefits of the embedded adaptive load balancing and admission control methods of the environment. In this paper, an Efficient Adaptive Load Balancing Scheme-based on Wilcoxon–Mann–Whitney Hypothesis Test (EALBS-WMW-HT) is proposed for mitigating Reduction of Quality-based DDoS attack in order to minimize its influence for enhancing the degree of availability to the cloud users. This proposed EALBS-HT scheme uses the merits of statistical testing on the traffic flow and contributes to the detection of RoQ-based DDoS attack such that they does not disturb the inherent load balancing process of the cloud environment. The experiments of the proposed EALBS-HT scheme revealed an excellent detection accuracy, true positive rate and true negative rate with minimized false negative rate studied on par with the baseline approaches considered for analysis.

Multidimensional: User with File Content and Server’s Status Based Authentication for Secure File Operations in Cloud

The popularity of data storage in cloud servers is getting more and more favoured in recent times. Its ease of storage, availability and synchronization of personalized cloud file storage using client applications made cloud storage more popular than ever. In cloud storage system, using a basic authentication method like username and password are still one of the most popular forms of authentication. However, the security ensure by such traditional authentication method is weak and vulnerable because the user name and password can be compromised by intruders or the user account can be left open by forgetting to logoff in public computers, leading to exposure of information to unauthorised users and hackers. In recent years, using a two-factor authentication has become a trend throughout network-based cloud services, online banking system and any form of services that requires user authentication. Here, in this paper a second layer authentication in the form of session key is used to ensure the authenticity of the activities of the user after user’s web-based account is logged-in successfully. The interesting and the critical contribution in this paper is the way the session key is generated and delivers to the authentic user. The key is generated by using the hash value of the file content, file size, file last modified, pseudo-random generated by the server using CPU temperature, clock speed, system time, and network packet timings, and user based 8 digit random position selection from a 32 digit Hex to mitigate against the attacker while performing vital file activities which may lead to data lost or data destruction or when user’s credentials are compromised.

Data Storage and Retrieval with Deduplication in Secured Cloud Storage

The Cloud Storage can be depicted as a service model where raw or processed data is stored, handled, and backed-up remotely while accessible to multiple users simultaneously over a network. Few of the ideal features of cloud storage is reliability, easy deployment, disaster recovery, security for data, accessibility and on top of that lesser overall storage costs which removes the hindrance of purchasing and maintaining the technologies for cloud storage. In this modern technology world, massive amount of data are produced in day to day life. So, it has become necessary to handle those big data on demand which is a challenging task for current data storage systems. The process of eliminating redundant copies of data thereby reducing the storage overhead is termed as Data Deduplication (DD). One of the ultimate aim of this research is to achieve ideal deduplication on secured data of client side. On the other hand as the client’s data are encrypted with different keys, the cross user deduplication is merely impossible as having a single key encryption among multiple user’s leads to an in secure system resulting in fragile to client’s expectations. The proposed research adapts Message Locked Encryption (MLE) technique that looks for redundant files in cloud before uploading the client’s file which eventually reduces the storage. Since the redundant files are swept, the network bandwidth is considerably reduced with respect to the redundant contents uploaded several times.

An Effectual Homomorphic Tag Based Block for Dynamic Provable Data Possession Framework Based on Block Tagging the Cloud File

Storing the data in cloud helps in satisfying the demand of data access at anyplace, anytime. In cloud storage, users authenticate whether the data has been stored to the cloud storage server correctly. In order to enhance the storage provision, an Effectual Homomorphic Tag based Block for Dynamic Provable Data Possession (EHTB-DPDP) framework has been designed. This framework checks for the data integrity in the cloud storage server. The existing PDP, DPDP schemes were analyzed and the drawbacks encountered in those systems have been reframed using the proposed methodology. The major benefit of the proposed EHTB-DPDP is that it offers an effectual dynamic provable data possession and data integrity. This scheme spotlights on the integrity of the remote data by reducing data storage space, so that users can retrieve data efficiently. This security enhancement is achieved by the block tagging methodology. In addition, converting the variable block size to the fixed block size using hash function is also investigated. The feasibility of the scheme is proved by aanlyzing the security and the performance

Rigorous Error Modeling for sUAS Acquired Image-Derived Point Clouds

The use of small unmanned aircraft systems to collect 3-D topographic data for a variety of geophysical applications has exploded in the last decade. These data are often produced from imagery using structure-from-motion (SfM) algorithms with or without ground control. While the accuracy of these data products has been assessed in a number of efforts, comparatively little focus has been placed on estimating spatially varying ground-space uncertainties in final data products using rigorous error propagation methodology and uncertainty estimation. Uncertainty estimates of the final 3-D products would provide users a more complete understanding of the quality of the products and therefore the applicability of the product. This paper illustrates an end-to-end workflow, using direct geopositioning and SfM techniques to create 3-D topographic point clouds with rigorously propagated accuracy estimates. Included is a method to quantify uncertainty in dense matching and incorporate those contributions into the final ground covariance. The uncertainty estimates are captured as metadata in the point cloud file using standard formats for exploitation. These estimates are critical to the downstream analysis, exploitation, and fusion of data sets; especially in scenarios where ground truth is not an option. The testing of this end-to-end process is described; data from a field campaign were processed without using mensurated control, and the resultant point clouds were compared to surveyed points to evaluate the predicted accuracy. Predicted accuracies bounded observed errors in the horizontal and vertical components. Future enhancements are also proposed.

Fine-grain watermarking for intellectual property protection

The current online digital world, consisting of thousands of newspapers, blogs, social media, and cloud file sharing services, is providing easy and unlimited access to a large treasure of text contents. Making copies of these text contents is simple and virtually costless. As a result, producers and owners of text content are interested in the protection of their intellectual property (IP) rights. Digital watermarking has become crucially important in the protection of digital contents. Out of all, text watermarking poses many challenges, since text is characterized by a low capacity to embed a watermark and allows only a restricted number of alternative syntactic and semantic permutations. This becomes even harder when authors want to protect not just a whole book or article, but each single sentence or paragraph, a problem well known to copyright law. In this paper, we present a fine-grain text watermarking method that protects even small portions of the digital content. The core method is based on homoglyph characters substitution for latin symbols and whitespaces. It allows to produce a watermarked version of the original text, preserving the anonymity of the users according to the right to privacy. In particular, the embedding and extraction algorithms allow to continuously protect the watermark through the whole document in a fine-grain fashion. It ensures visual indistinguishability and length preservation, meaning that it does not cause overhead to the original document, and it is robust to the copy and past of small excerpts of the text. We use a real dataset of 1.8 million New York articles to evaluate our method. We evaluate and compare the robustness against common attacks, and we propose a new measure for partial copy and paste robustness. The results show the effectiveness of our approach providing an average length of 101 characters needed to embed the watermark and allowing to protect paragraph-long excerpt or smaller the 94.5% of the times.

A versatile macro-based neurohistological image analysis suite for ImageJ focused on automated and standardized user interaction and reproducible data output

BackgroundThe development and increasing adoption of advanced microscopy imaging technologies, including high resolution, multi-dimensional digital photography and multiple fluorescence channel acquisition, as well as the availability of inexpensive terabyte-capacity storage, have enabled research laboratories to pursue neurohistological imaging experiments involving multiple neurochemical probes and experimental conditions covering a variety of brain regions. Analyzing and processing the resulting datasets, composed of hundreds of micrographs, presents challenges in ensuring accuracy and reproducibility under demanding time and training constraints. New methodThe ‘Custom Macros’ plugin suite for ImageJ automates and systematizes user interaction in neurohistological image analysis tasks, including region selection and thresholding, point/object counts, area measurement, batch filter processing, and data review. Written in the accessible ImageJ macro language, the plugin implements a user login-based data storage framework and facilitates inter-laboratory collaboration over cloud file server clients. ResultsA macro-based interface approach integrates dozens of novel operations, software interactions, algorithm calls, and background tasks into individual shortcut commands. Every completed procedure generates image, region, and calibrated measurement records that are saved in a standardized folder structure. Comparisons with existing methodsPlugin installation adds startup access to a persistent interface layer of extensive and streamlined functionality that is generalizable to a variety of neurohistological contexts, thus providing an efficient and reliable alternative to the use of analysis software in an unstructured, provisional manner that necessitates repeated menu and plugin interaction. ConclusionsOur free/open-source software provides researchers a straightforward solution to addressing daunting usability and data oversight issues, ultimately making efficient, accessible, and reproducible image analysis methodology attainable for many laboratories.

Characterization and modeling of power line corridor elements from LiDAR point clouds

As the electric companies need to assure the reliability of their services, power line management gains importance during the last years. Many of them rely on LiDAR scanning of their assets to obtain the status of their power line corridors and determine possible risks. In this paper, a novel sevenfold staged pipeline is introduced to classify pylon and wire points and model the conductors. Wire points are subdivided into three categories: shield, common conductor and chain. Pylons of two different types are taken into account: suspension and anchor. For the first case, insulator strains are also identified and separated. Wire points are segmented as individual conductors and a 3D-wise model based on the catenary equation is generated for each conductor using particle swarm optimization. Tests have been conducted on a set with 25 point cloud files to assess the accuracy and correctness of the results given by the proposed pipeline.

Enabling Identity-Based Integrity Auditing and Data Sharing With Sensitive Information Hiding for Secure Cloud Storage

With cloud storage services, users can remotely store their data to the cloud and realize the data sharing with others. Remote data integrity auditing is proposed to guarantee the integrity of the data stored in the cloud. In some common cloud storage systems such as the electronic health records system, the cloud file might contain some sensitive information. The sensitive information should not be exposed to others when the cloud file is shared. Encrypting the whole shared file can realize the sensitive information hiding, but will make this shared file unable to be used by others. How to realize data sharing with sensitive information hiding in remote data integrity auditing still has not been explored up to now. In order to address this problem, we propose a remote data integrity auditing scheme that realizes data sharing with sensitive information hiding in this paper. In this scheme, a sanitizer is used to sanitize the data blocks corresponding to the sensitive information of the file and transforms these data blocks’ signatures into valid ones for the sanitized file. These signatures are used to verify the integrity of the sanitized file in the phase of integrity auditing. As a result, our scheme makes the file stored in the cloud able to be shared and used by others on the condition that the sensitive information is hidden, while the remote data integrity auditing is still able to be efficiently executed. Meanwhile, the proposed scheme is based on identity-based cryptography, which simplifies the complicated certificate management. The security analysis and the performance evaluation show that the proposed scheme is secure and efficient.

A security ensemble framework for securing the file in cloud computing environments

Scalability and on-demand features of cloud computing have revolutionised IT industry in a large scale. Cloud service providers takes the entire burdens of computing, especially managing resources and file storage. Securing the file stored in cloud storage from internal and external attacks has become a primary concern for cloud storage providers as well as cloud users. In this paper, the threats involved in file storage and a secure way of protecting the stored files using a novel ensemble of security strategies is presented. This proposed strategy helps service providers as well as users to secure the file in cloud storage more efficiently.

A security ensemble framework for securing the file in cloud computing environments

Scalability and on-demand features of cloud computing have revolutionised IT industry in a large scale. Cloud service providers takes the entire burdens of computing, especially managing resources and file storage. Securing the file stored in cloud storage from internal and external attacks has become a primary concern for cloud storage providers as well as cloud users. In this paper, the threats involved in file storage and a secure way of protecting the stored files using a novel ensemble of security strategies is presented. This proposed strategy helps service providers as well as users to secure the file in cloud storage more efficiently.

A secured cloud storage auditing with empirical outsourcing of key updates

Cloud computing is promising and considered next generation technology for computing. The current cloud storage auditing models require the client to update his secret keys in each time period which bring in local burdens to the client. The aim of the project is to make the key updates transpicuous to the client and present a new model for auditing cloud storage with provable outsourcing of updated keys. In this model, the key updates are sent to a third party auditor (TPA) who reduces the local burden on the client. In addition, the TPA will audit whether the files in cloud are stored correctly by a challenge-response protocol between the cloud and TPA at regular time. The proposed paradigm permits the client to authenticate the validity of the encrypted secret key produced by the TPA for uploading data to the cloud.

A secured cloud storage auditing with empirical outsourcing of key updates

Cloud computing is promising and considered next generation technology for computing. The current cloud storage auditing models require the client to update his secret keys in each time period which bring in local burdens to the client. The aim of the project is to make the key updates transpicuous to the client and present a new model for auditing cloud storage with provable outsourcing of updated keys. In this model, the key updates are sent to a third party auditor (TPA) who reduces the local burden on the client. In addition, the TPA will audit whether the files in cloud are stored correctly by a challenge-response protocol between the cloud and TPA at regular time. The proposed paradigm permits the client to authenticate the validity of the encrypted secret key produced by the TPA for uploading data to the cloud.

Design and Implementation of the Cloud File Management Service System Based on LAN

The number of digital files is growing up in the age of information. Effective management of file becomes increasingly important. This paper proposes a cloud file management service based on local area network. It solves the problems of traditional file transmission and file storage in local area network. It solves the security issue and multi-user management. This cloud file management service is also scalable and easy to use. Based on this service, many network applications can be developed furtherly, including office automation, teaching system, experiment platform, graduation milestone project or thesis management system, and email system.

Algorithm for generating personalized external fixation model based on STL file

Objective To study the generating algorithm of personalized external fixation model based on STL file, so as to realize the fabrication of personalized external fixation through 3D scanning, model generation and 3D printing. Compared with the traditional plaster fixation, the external fixation obtained by the proposed method has the advantages of good adhesion to the external surface of the limb, good gas permeability and light weight. Methods In order to generate a personalized external fixation model, the key generating algorithms of the model were studied. The point cloud file of the residual limb was obtained by a 3D scanner, and then was converted into an STL format file. The triangular patches were processed by cutting, offsetting, triangulating and hollowing to create an external fixation model with good gas permeability and conformable surface that is fully fitted with the body surface. Finally, the external fixation was fabricated by 3D printing. Results Using the improved point offset algorithm, the problem of severe distortion of the point offset at the plane and sharp corners was solved. Using the tangent sort method, the points on the contour ring were sorted clockwise to obtain a triangular profile. The hollowing of the model was achieved by using the typical three-dimensional cutting tool mathematical model and the STL file space intersection method. Conclusions The improved model generating algorithm was validated based on a wrist case, and the personalized external fixed fixation model with conformable surface was obtained. It is proved that the proposed model generating algorithm is effective and practical. Key words: STL files; Cutting; Offsetting; Hollowing; External fixation

A Multimedia File Cloud Storage System to Support Data Deduplication and Logical Expansion

A Multimedia File Cloud Storage System to Support Data Deduplication and Logical Expansion

A hybrid data replication strategy with fuzzy-based deletion for heterogeneous cloud data centers

At present, huge cloud-based applications have put forward higher requests for data center storage. In a large-scale Cloud environment, data replication provides an appropriate solution for managing data files, which improves data reliability and availability. In this paper, we propose a data replication algorithm called hybrid replication strategy (HRS) that is applied into replica placement, selection, and replacement steps. HRS has three main phases and is suitable for replicating data files in cloud. In the first phase, it selects the best site (i.e., that is the most central site with high number of access) for storing new replica to reduce access time. In the second phase, HRS considers the best replica node for users based on different parameters such as CPU process capability, network transmission capability, I/O capability of disks, load, and network latency. In the third phase, the replacement decision is made in order to provide better response time. HRS can ascertain the importance of valuable replicas on the basis of a fuzzy inference system with three input parameters (i.e., number of accesses, cost, and the last time the replica was accessed). The new replication policy is simulated using the CloudSim toolkit package. Our proposed mechanism replicates the data over the cloud nodes reasonably well and is easily implementable in a real environment. Experiment results prove that HRS can significantly enhance availability, performance and load balance for data-intensive applications. In addition, it stands good without increasing additional overheads.

An architecture for synchronising cloud file storage and organisation repositories

ABSTRACTCloud computing providers have disseminated dynamic storage provisioning delivered to end users as on-demand services. Although cloud file storage and sharing has become popular among home users, the access requirements, performance expectations and usage characteristics are different for organisations, and were not originally considered by popular applications and tools for synchronising files between cloud providers and local repositories. Moreover, multisite organisations traditionally have legacy file storage and wide-area networking solutions to support their business systems. Typically, the file repositories are replicated between sites using private communication links. The combination of legacy storage solutions interconnected through private links with cloud-based file storage is a challenging task. In this context, this paper introduces Cloud4NetOrg, a client architecture for cloud file storage and multisite repository synchronisation. We implemented prototypes of this architecture that interact with two popular cloud file services (DropBox and OneDrive), and the experimental results indicate a promising application in collaborative environments with several LANs. Indeed, Cloud4NetOrg decreases the synchronisation time and the total data transferred from/to cloud repositories by using the organisation repositories as a hierarchical cache system.Cloud4NetOrg is proposed for geographically distributed organisations composed of dynamic and temporary collaborative groups. The interaction between employees is based on file sharing. Commonly, sites are interconnected by a private network and have an internal data storage repository. A single site can have multiple subnetworks to interconnect the collaborative groups. In addition, home-office users collaborate through the Internet, usually using size-limited storage devices.

Leakage resilient ID-based proxy re-encryption scheme for access control in fog computing

In fog computing, fog-devices are usually physically close to end-devices, and have a high speed connection with cloud servers. They provide good access control service for end-devices to cloud, if an ID-based proxy re-encryption scheme is deployed on them. Each file stored on a cloud server is encrypted using a symmetric key, and these keys are encrypted by a public master key which is stored in a fog-device. If an end-device want to access a file in cloud, then the fog-device re-encrypts these encapsulated symmetric keys from the master key to the key of the end-device. However, due to the geographic dispersion of fog-devices, they are apt to be attacked by side channel attacks. In this work, we propose a leakage resilient ID-based proxy re-encryption scheme in auxiliary input model. It can resist the continuous leakage of secret keys caused by side channel attacks. We implement our scheme over two platforms, and the results show that our scheme is feasible in practice.

Fuzzy Based Implementation of Multi - Keyword Ranked Search over Encrypted Cloud Data in Secure Cloud Environment

Cloud computing enables the paradigm of data outsourcing. However, to protect data privacy, sensitive cloud data have to be encrypted before outsourced to the commercial public cloud, which makes effective data utilization service is a challenging task. Even though searchable encryption techniques allow users to securely search over encrypted data through keywords, they support only Boolean search and are not yet sufficient to meet the effective data utilization need that is inherently demanded by large number of users and huge amount of data files in cloud. Hence it is necessary to allow multiple keywords in the search request and return documents in the order of their relevance to the keywords. The works on searchable encryption focused on single keyword search or Boolean keyword search and the result produced by them are rarely sorted. An effective method proposed for this challenging problem is privacy-preserving search over encrypted cloud data. This method establishes a set of strict privacy requirements for such a secure cloud data utilization system through MRSE. Among various multi-keyword semantics, this method chooses the efficient similarity measure of “coordinate matching”. Then according to Top K Query method the sorted results are produced. The privacy is preserved by the chunk of data stored in a various server’s. Then further improvisation is taken to introduce low overhead on computation and communication in future.