Data deduplication, an efficient approach to data reduction, has gained increasing attention and popularity in large-scale storage systems due the explosive growth of digital data. It eliminates redundant at file or subfile level identifies duplicate content by its cryptographically secure hash signature (i.e., collision-resistant fingerprint), which is shown be much more computationally than traditional compression approaches systems. In this paper, we first review background key features...

Nowadays, many customers and enterprises backup their data to cloud storage that performs deduplication save space network bandwidth. Hence, how perform secure becomes a critical challenge for storage. According our analysis, the state-of-the-art methods are not suitable cross-user finegrained deduplication. They either suffer brute-force attacks can recover files falling into known set, or incur large computation (time) overheads. Moreover, existing approaches of convergent key management...

Data deduplication, a space-efficient and bandwidth-saving technology, plays an important role in bandwidth-efficient data transmission various data-intensive network cloud applications. Rabin-based MAXP-based Content-Defined Chunking (CDC) algorithms, while robust finding suitable cut-points for chunk-level redundancy elimination, face the key challenges of (1) low chunking throughput that renders stage deduplication performance bottleneck (2) large chunk-size variance decreases efficiency....

Content-Defined Chunking (CDC) has been playing a key role in data deduplication systems recently due to its high redundancy detection ability. However, existing CDC-based approaches introduce heavy CPU overhead because they declare the chunk cut-points by computing and judging rolling hashes of stream byte byte. In this article, we propose FastCDC, Fast efficient approach, for deduplication-based storage systems. The idea behind FastCDC is combined use five techniques, namely, gear based...

Chunk-level deduplication plays an important role in backup storage systems. Existing Content-Defined Chunking (CDC) algorithms, while robust finding suitable chunk boundaries, face the key challenges of (1) low chunking throughput that renders stage a serious performance bottleneck, (2) large size variance decreases efficiency, and (3) being unable to find proper boundaries low-entropy strings thus failing deduplicate these strings. To address challenges, this paper proposes new CDC...

As an emerging memory technology to build the future main systems, Phase Change Memory (PCM) can increase capacity in a cost-effective and power-efficient way. However, PCM is facing security threats for its limited write endurance: malicious adversary could wear out cells cause whole system fail within short period of time. To address this issue, several wear-leveling schemes have been proposed evenly distribute traffic security-aware manner. In work, we present new type timing attacknamed...

Data deduplication is able to effectively identify and eliminate redundant data only maintain a single copy of files chunks. Hence, it widely used in distributed storage systems cloud save the users' network bandwidth for uploading files. However, occurrence can be easily identified by monitoring analyzing traffic, which leads risk user privacy leakage. An attacker carry out very dangerous side channel attack, i.e., learn-the-remaining-information (LRI) reveal information exploiting traffic...

Live migration of virtual machines (VM) is one the key characteristics virtualization for load balancing, system maintenance, power management, etc., in data centers or clusters. In order to reduce transferred and shorten time, compression techniques have been widely used accelerate VM migration. However, different approaches ratios speeds. Because there a trade-off between transmission, performance improvements obtained from are differentiated, vary with network bandwidth. Besides, window...

Quantitative analysis of professional basketball become an attractive field for experienced data analysts, and the recent availability high-resolution datasets pushes data-driven analytics to a higher degree. We present qualitative discussion on quantitative basketball. propose discuss dimensions, levels granularity, types tasks in review key literature past two decades map them into proposed framework, with evolutionary perspective emphasis advances. A list questions around that could be...

With the rapid expansion of Internet Things (IoT), relevant files are stored and transmitted at network edge by employing data deduplication to eliminate redundant for best accessibility. Although improves storage efficiency, it decreases security strength performance. Existing schemes usually adopt message-locked encryption (MLE) encrypt data, which is vulnerable brute-force attacks. Meanwhile, these utilize proof-of-ownership (PoW) prevent duplicate-faking attacks, while they suffer from...

Chunk-level deduplication, while robust in removing duplicate chunks, introduces chunk fragmentation which decreases restore performance. Rewriting algorithms are proposed to reduce the and accelerate speed. Delta compression can remove redundant data between non-duplicate but similar chunks cannot be eliminated by chunk-level deduplication. Some applications use delta as a complement for deduplication attain extra space bandwidth savings. However, we observe that new type of stemming from...

Data compression is widely used in storage systems to reduce redundant data and thus save space. One challenge facing the traditional approaches limitation of windows size, which fails redundancy globally. In this paper, we present DEC, a Deduplication-Enhanced Compression approach that effectively combines deduplication compressors increase ratio efficiency. Specifically, make full use (1) accelerate reduction by fast but global (2) exploit locality compress similar chunks clustering are...

Data deduplication is able to effectively identify and eliminate redundant data only maintain a single copy of files chunks. Hence, it widely used in cloud storage systems save space network bandwidth. However, the occurrence can be easily identified by monitoring analyzing traffic, which leads risk user privacy leakage. The attacker carry out very dangerous side channel attack, i.e., learn-the-remaining-information (LRI) reveal users' information exploiting traffic deduplication. Existing...

Data deduplication [3] is able to effectively identify and eliminate redundant data only maintain a single copy of files chunks. Hence, it widely used in cloud storage systems save the users' network bandwidth for uploading data. However, occurrence can be easily identified by monitoring analyzing traffic, which leads risk user privacy leakage. The attacker carry out very dangerous side channel attack, i.e., learn-the-remaining-information (LRI) reveal information exploiting traffic [1]. In...