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| 1 | Request Merging Based Cross-User Deduplication for Cloud Storage with Resistance Against Appending Chunks Attack显示文摘Cross-user deduplication is an emerging technique to eliminate redundant uploading in cloud storage.Its deterministic response indicating the existence of data creates a side channel to attackers,which makes the privacy in the cloud at risk.Such kind of attack as well as further appending chunks attack,still cannot be well resisted in current solutions,thus is becoming a big obstacle in using this technique.We propose a secure cross-user deduplication,called Request merging based deduplication scheme(RMDS),which takes the lead to consider resistance against appending chunks attack in a lightweight way,let alone side channel attack.We utilize the proposed XOR based chunk-level server-side storage structure together with a request merging strategy to obfuscate attackers in minimized communication overhead.The experiment results show that,with security guaranteed,the proposed scheme is more efficient comparing with the state of the art. | TANG Xin ZHANG Yi ZHOU Linna LIU Dan HU Bingwei | 2021 | Chinese Journal of Electronics2021，30，2： | 3 |
| 2 | Threat Model and Defense Scheme for Side-Channel Attacks in Client-Side Deduplication显示文摘In cloud storage,client-side deduplication is widely used to reduce storage and communication costs.In client-side deduplication,if the cloud server detects that the user’s outsourced data have been stored,then clients will not need to reupload the data.However,the information on whether data need to be uploaded can be used as a side-channel,which can consequently be exploited by adversaries to compromise data privacy.In this paper,we propose a new threat model against side-channel attacks.Different from existing schemes,the adversary could learn the approximate ratio of stored chunks to unstored chunks in outsourced files,and this ratio will affect the probability that the adversary compromises the data privacy through side-channel attacks.Under this threat model,we design two defense schemes to minimize privacy leakage,both of which design interaction protocols between clients and the server during deduplication checks to reduce the probability that the adversary compromises data privacy.We analyze the security of our schemes,and evaluate their performances based on a real-world dataset.Compared with existing schemes,our schemes can better mitigate data privacy leakage and have a slightly lower communication cost. | Guanxiong Ha Hang Chen Chunfu Jia Mingyue Li | 2023 | Tsinghua Science and Technology2023，28，1： | 1 |
| 3 | Secured Data Storage Using Deduplication in Cloud Computing Based on Elliptic Curve Cryptography显示文摘The tremendous development of cloud computing with related technol-ogies is an unexpected one.However,centralized cloud storage faces few chal-lenges such as latency,storage,and packet drop in the network.Cloud storage gets more attention due to its huge data storage and ensures the security of secret information.Most of the developments in cloud storage have been positive except better cost model and effectiveness,but still data leakage in security are billion-dollar questions to consumers.Traditional data security techniques are usually based on cryptographic methods,but these approaches may not be able to with-stand an attack from the cloud server's interior.So,we suggest a model called multi-layer storage(MLS)based on security using elliptical curve cryptography(ECC).The suggested model focuses on the significance of cloud storage along with data protection and removing duplicates at the initial level.Based on divide and combine methodologies,the data are divided into three parts.Here,thefirst two portions of data are stored in the local system and fog nodes to secure the data using the encoding and decoding technique.The other part of the encrypted data is saved in the cloud.The viability of our model has been tested by research in terms of safety measures and test evaluation,and it is truly a powerful comple-ment to existing methods in cloud storage. | N.Niyaz Ahamed N.Duraipandian | 2022 | Computer Systems Science & Engineering2022，41，4： | 1 |
| 4 | Prefetch-aware fingerprint cache management for data deduplication systems显示文摘Data deduplication has been widely utilized in large-scale storage systems, particularly backup systems. Data deduplication systems typically divide data streams into chunks and identify redundant chunks by comparing chunk fingerprints. Maintaining all fingerprints in memory is not cost-effective because fingerprint indexes are typically very large. Many data deduplication systems maintain a fingerprint cache in memory and exploit fingerprint prefetching to accelerate the deduplication process. Although fingerprint prefetching can improve the performance of data deduplication systems by leveraging the locality of workloads, inaccurately prefetched fingerprints may pollute the cache by evicting useful fingerprints. We observed that most of the prefetched fingerprints in a wide variety of applications are never used or used only once, which severely limits the performance of data deduplication systems. We introduce a prefetch-aware fingerprint cache management scheme for data deduplication systems (PreCache) to alleviate prefetch-related cache pollution. We propose three prefetch-aware fingerprint cache replacement policies (PreCache-UNU, PreCache-UOO, and PreCache-MIX) to handle different types of cache pollution. Additionally, we propose an adaptive policy selector to select suitable policies for prefetch requests. We implement PreCache on two representative data deduplication systems (Block Locality Caching and SiLo) and evaluate its performance utilizing three real-world workloads (Kernel, MacOS, and Homes). The experimental results reveal that PreCache improves deduplication throughput by up to 32.22% based on a reduction of on-disk fingerprint index lookups and improvement of the deduplication ratio by mitigating prefetch-related fingerprint cache pollution. | Mei LI Hongjun ZHANG Yanjun WU Chen ZHAO | 2019 | Frontiers of Computer Science2019，13，3： | 1 |
| 5 | Updatable block-level deduplication of encrypted data with efficient auditing in cloud storage显示文摘Updatable block-level message-locked encryption(MLE) can efficiently update encrypted data, and public auditing can verify the integrity of cloud storage data by utilizing a third party auditor(TPA). However, there are seldom schemes supporting both updatable block-level deduplication and public auditing. In this paper, an updatable block-level deduplication scheme with efficient auditing is proposed based on a tree-based authenticated structure. In the proposed scheme, the cloud server(CS) can perform block-level deduplication, and the TPA achieves integrity auditing tasks. When a data block is updated, the ciphertext and auditing tags could be updated efficiently. The security analysis demonstrates that the proposed scheme can achieve privacy under chosen distribution attacks in secure deduplication and resist uncheatable chosen distribution attacks(UNC-CDA) in proof of ownership(PoW). Furthermore, the integrity auditing process is proven secure under adaptive chosen-message attacks. Compared with previous relevant schemes, the proposed scheme achieves better functionality and higher efficiency. | Dang Qianlong Xie Ying Li Donghao Hu Gongcheng | 2019 | The Journal of China Universities of Posts and Telecommunications2019，26，3： | 1 |
| 6 | SRSC: Improving Restore Performance for Deduplication-Based Storage Systems显示文摘Modern backup systems exploit data deduplication technology to save stor-age space whereas suffering from the fragmentation problem caused by deduplication.Fragmentation degrades the restore performance because of restoring the chunks thatare scattered all over different containers. To improve the restore performance, thestate-of-the-art History Aware Rewriting Algorithm(HAR) is proposed to collect frag-mented chunks in the last backup and rewrite them in the next backup. However, dueto rewriting fragmented chunks in the next backup, HAR fails to eliminate internalfragmentation caused by self-referenced chunks(that exist more than two times in abackup) in the current backup, thus degrading the restore performance. In this paper,we propose Selectively Rewriting Self-Referenced Chunks(SRSC), a scheme that de-signs a buffer to simulate a restore cache, identify internal fragmentation in the cacheand selectively rewrite them. Our experimental results based on two real-world datas-ets show that SRSC improves the restore performance by 45% with an acceptable sac-rifice of the deduplication ratio. | ZUO Chunxue WANG Fang TANG Xiaolan ZHANG Yucheng FENG Dan | 2019 | ZTE Communications2019，17，2： | 0 |
| 7 | Practices of backuping homomorphically encrypted databases显示文摘Ideal homomorphic encryption is theoretically achievable but impractical in reality due to tremendous computing overhead. Homomorphically encrypted databases, such as CryptDB, leverage replication with partially homomorphic encryption schemes to support different SQL queries over encrypted data directly. These databases reach a balance between security and efficiency, but incur considerable storage overhead, especially when making backups. Unfortunately, general data compression techniques relying on data similarity exhibit inefficiency on encrypted data. We present CryptZip, a backup and recovery system that could highly reduce the backup storage cost of encrypted databases. The key idea is to leverage the metadata information of encryption schemes and selectively backup one or several columns among semantically redundant columns. The experimental results show that CryptZip could reduce up to 90.5% backup storage cost on TPC-C benchmark. | Sa WANG Yiwen SHAO Yungang BAO | 2019 | Frontiers of Computer Science2019，13，2： | 0 |
| 8 | Hash-Indexing Block-Based Deduplication Algorithm for Reducing Storage in the Cloud显示文摘Cloud storage is essential for managing user data to store and retrieve from the distributed data centre.The storage service is distributed as pay a service for accessing the size to collect the data.Due to the massive amount of data stored in the data centre containing similar information and file structures remaining in multi-copy,duplication leads to increase storage space.The potential deduplication system doesn’t make efficient data reduction because of inaccuracy in finding similar data analysis.It creates a complex nature to increase the storage consumption under cost.To resolve this problem,this paper proposes an efficient storage reduction called Hash-Indexing Block-based Deduplication(HIBD)based on Segmented Bind Linkage(SBL)Methods for reducing storage in a cloud environment.Initially,preprocessing is done using the sparse augmentation technique.Further,the preprocessed files are segmented into blocks to make Hash-Index.The block of the contents is compared with other files through Semantic Content Source Deduplication(SCSD),which identifies the similar content presence between the file.Based on the content presence count,the Distance Vector Weightage Correlation(DVWC)estimates the document similarity weight,and related files are grouped into a cluster.Finally,the segmented bind linkage compares the document to find duplicate content in the cluster using similarity weight based on the coefficient match case.This implementation helps identify the data redundancy efficiently and reduces the service cost in distributed cloud storage. | D.Viji S.Revathy | 2023 | Computer Systems Science & Engineering2023，46，7： | 0 |
| 9 | Differentially Authorized Deduplication System Based on Blockchain显示文摘In architecture of cloud storage, the deduplication technology encrypted with theconvergent key is one of the important data compression technologies, which effectively improvesthe utilization of space and bandwidth. To further refine the usage scenarios for varioususer permissions and enhance user’s data security, we propose a blockchain-based differentialauthorized deduplication system. The proposed system optimizes the traditionalProof of Vote (PoV) consensus algorithm and simplifies the existing differential authorizationprocess to realize credible management and dynamic update of authority. Based on thedecentralized property of blockchain, we overcome the centralized single point fault problemof traditional differentially authorized deduplication system. Besides, the operations oflegitimate users are recorded in blocks to ensure the traceability of behaviors. | ZHAO Tian LI Hui YANG Xin WANG Han ZENG Ming GUO Haisheng WANG Dezheng | 2021 | ZTE Communications2021，19，2： | 0 |
| 10 | Health Data Deduplication Using Window Chunking-Signature Encryption in Cloud显示文摘Due to the development of technology in medicine,millions of health-related data such as scanning the images are generated.It is a great challenge to store the data and handle a massive volume of data.Healthcare data is stored in the cloud-fog storage environments.This cloud-Fog based health model allows the users to get health-related data from different sources,and duplicated informa-tion is also available in the background.Therefore,it requires an additional sto-rage area,increase in data acquisition time,and insecure data replication in the environment.This paper is proposed to eliminate the de-duplication data using a window size chunking algorithm with a biased sampling-based bloomfilter and provide the health data security using the Advanced Signature-Based Encryp-tion(ASE)algorithm in the Fog-Cloud Environment(WCA-BF+ASE).This WCA-BF+ASE eliminates the duplicate copy of the data and minimizes its sto-rage space and maintenance cost.The data is also stored in an efficient and in a highly secured manner.The security level in the cloud storage environment Win-dows Chunking Algorithm(WSCA)has got 86.5%,two thresholds two divisors(TTTD)80%,Ordinal in Python(ORD)84.4%,Boom Filter(BF)82%,and the proposed work has got better security storage of 97%.And also,after applying the de-duplication process,the proposed method WCA-BF+ASE has required only less storage space for variousfile sizes of 10 KB for 200,400 MB has taken only 22 KB,and 600 MB has required 35 KB,800 MB has consumed only 38 KB,1000 MB has taken 40 KB of storage spaces. | G.Neelamegam P.Marikkannu | 2023 | Intelligent Automation & Soft Computing2023，，4： | 0 |
| 11 | High Security for De-Duplicated Big Data Using Optimal SIMON Cipher显示文摘Cloud computing offers internet location-based affordable,scalable,and independent services.Cloud computing is a promising and a cost-effective approach that supports big data analytics and advanced applications in the event of forced business continuity events,for instance,pandemic situations.To handle massive information,clusters of servers are required to assist the equipment which enables streamlining the widespread quantity of data,with elevated velocity and modified configurations.Data deduplication model enables cloud users to efficiently manage their cloud storage space by getting rid of redundant data stored in the server.Data deduplication also saves network bandwidth.In this paper,a new cloud-based big data security technique utilizing dual encryption is proposed.The clustering model is utilized to analyze the Deduplication process hash function.Multi kernel Fuzzy C means(MKFCM)was used which helps cluster the data stored in cloud,on the basis of confidence data encryption procedure.The confidence finest data is implemented in homomorphic encryption data wherein the Optimal SIMON Cipher(OSC)technique is used.This security process involving dual encryption with the optimization model develops the productivity mechanism.In this paper,the excellence of the technique was confirmed by comparing the proposed technique with other encryption and clustering techniques.The results proved that the proposed technique achieved maximum accuracy and minimum encryption time. | A.Muthumari J.Banumathi S.Rajasekaran P.Vijayakarthik K.Shankar Irina V.Pustokhina Denis A.Pustokhin | 2021 | Computers, Materials & Continua2021，，5： | 0 |
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