Vacuum filters

Wang, Minmei; Zhou, Mingxun; Shi, Shouqian; Qian, Chen

doi:10.14778/3364324.3364333

Cited by 44 publications

(4 citation statements)

References 35 publications

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“…The vacuum filter 36 is then applied to the encrypted data for storing and preserving records of the details related to the data. All hash values are stored in the vacuum filter along with the users' signatures that can be verified in the data integrity verification phase.…”

Section: Proposed Methodologymentioning

confidence: 99%

Blockchain assisted blind signature algorithm with data integrity verification scheme

Shrivastava,

Alam,

Alam

2024

Concurrency and Computation

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SummaryAs the demand for cloud storage systems increases, ensuring the security and integrity of cloud data becomes a challenge. Data uploaded to cloud systems are vulnerable to numerous sorts of assaults, which must be handled appropriately to avoid data tampering issues. In addition, quantum computers are expected to be introduced soon, which may face multiple security issues by destroying all traditional cryptosystems. This work introduces a quantum‐resistant blockchain centered data integrity verification system with the use of several techniques. Initially, the keys and signatures are generated by the users with the help of the lattice‐based blind signature algorithm (L_BSA), which is a combination of lattice cryptography and a blind signature algorithm. From the generated random keys, the most optimal key is then selected by the Puzzle Optimization Algorithm (POA), which is then made available to the encryption phase. Then, the upgraded Merkle tree‐assisted vacuum filter (Vac‐UMT) algorithm is executed to accomplish the encryption task. Then the data are converted into blocks using blockchain technology and uploaded to the cloud. When receiving the audit requests, the verification process is carried out, and the evidence report is generated for the users. The proposed work is simulated in JAVA and assessed with the UNSW‐NB15 dataset, and the outcomes demonstrated that the system is highly efficient and secure.

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Section: Proposed Methodologymentioning

confidence: 99%

Blockchain assisted blind signature algorithm with data integrity verification scheme

Shrivastava,

Alam,

Alam

2024

Concurrency and Computation

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“…In addition to the dynamic variants, there are many other typical variants of CF, including perfect CF [31] , adaptive CF [32] , simplified CF [33] , vertical CF [34] , and vacuum CF [35] . These variants improve the performance of CF in terms of the false alarm rate, theoretical guarantee, space efficiency, and query throughput, further expanding its application scope.…”

Section: Cf and Its Elastic Designmentioning

confidence: 99%

Jump Filter: A Dynamic Sketch for Big Data Governance

Fu¹,

Luo²,

Guo³

et al. 2023

International Journal of Software and Informatics

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With the rapid development of information technology, the volume of data maintains exponential growth, and the value of data is hard to mine. This brings significant challenges to the efficient management and control of each link in the data life cycle, such as data collection, cleaning, storage, and sharing. Sketch uses a hash table/matrix/bit vector to track the core characteristics of data, such as frequency, cardinality, and membership. This mechanism makes the sketch itself metadata, which has been widely used in sharing, transmission, update, and other scenarios. The rapid flow characteristic of big data has spawned dynamic sketches. The existing dynamic sketches have the advantage of expanding or shrinking the capacity with the size of the data stream by dynamically maintaining a list of probabilistic data structures in a chain or tree structure. However, there are problems with the excessive space overhead and time overhead increasing with the increase in the dataset cardinality. This paper designs a dynamic sketch for big data governance on the basis of the advanced jump consistent hash. This method can simultaneously achieve the space overhead that grows linearly with the dataset cardinality and the constant time overhead of data processing and analysis, effectively supporting the demanding big data processing and analysis tasks for big data governance. The validity and efficiency of the proposed method are verified by the comparison with traditional methods on various synthetic and natural datasets.

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“…Morton filter [20] introduces virtual buckets and divides logical buckets into memory-aligned blocks to realize higher throughput. Vacuum filter [21] confines the element insertion, deletion, and query within a chunk to achieve significant throughput improvements and memory access decrements.…”

Section: A the State-of-the-art Sketchesmentioning

confidence: 99%

Ark Filter: A General and Space-Efficient Sketch for Network Flow Analysis

Luo

et al. 2023

IEEE/ACM Trans. Networking

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Sketches are widely deployed to represent network flows to support complex flow analysis. Typical sketches usually employ hash functions to map elements into a hash table or bit array. Such sketches still suffer from potential weaknesses upon throughput, flexibility, and functionality. To this end, we propose Ark filter, a novel sketch that stores the element information with either of two candidate buckets indexed by the quotient or remainder between the fingerprint and filter length. In this way, no further hash calculations are required for future queries or reallocations. We further extend the Ark filter to enable capacity elasticity and more functionalities (such as frequency estimation and top-k query). Comprehensive experiments demonstrate that, compared with Cuckoo filter, Ark filter has 2.08×, 1.34×, and 1.68× throughput of deletion, insertion, and hybrid query, respectively; compared with Quotient filter, Ark filter has 4.55×, 1.74×, and 22.12× throughput of deletion, insertion, and hybrid query, respectively; compared with Bloom filter, Ark filter has 2.55× and 2.11× throughput of insertion and hybrid query, respectively.

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Vacuum filters

Cited by 44 publications

References 35 publications

Blockchain assisted blind signature algorithm with data integrity verification scheme

Blockchain assisted blind signature algorithm with data integrity verification scheme

Jump Filter: A Dynamic Sketch for Big Data Governance

Ark Filter: A General and Space-Efficient Sketch for Network Flow Analysis

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