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Ȩ Ȩ > ¿¬±¸¹®Çå > ¿µ¹® ³í¹®Áö > TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)

TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) Verification Algorithm for the Duplicate Verification Data with Multiple Verifiers and Multiple Verification Challenges
¿µ¹®Á¦¸ñ(English Title) Verification Algorithm for the Duplicate Verification Data with Multiple Verifiers and Multiple Verification Challenges
ÀúÀÚ(Author) Guangwei Xu   Miaolin Lai   Xiangyang Feng   Qiubo Huang   Xin Luo   Li Li   Shan Li  
¿ø¹®¼ö·Ïó(Citation) VOL 15 NO. 02 PP. 0558 ~ 0579 (2021. 02)
Çѱ۳»¿ë
(Korean Abstract)
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(English Abstract)
The cloud storage provides flexible data storage services for data owners to remotely outsource their data, and reduces data storage operations and management costs for data owners. These outsourced data bring data security concerns to the data owner due to malicious deletion or corruption by the cloud service provider. Data integrity verification is an important way to check outsourced data integrity. However, the existing data verification schemes only consider the case that a verifier launches multiple data verification challenges, and neglect the verification overhead of multiple data verification challenges launched by multiple verifiers at a similar time. In this case, the duplicate data in multiple challenges are verified repeatedly so that verification resources are consumed in vain. We propose a duplicate data verification algorithm based on multiple verifiers and multiple challenges to reduce the verification overhead. The algorithm dynamically schedules the multiple verifiers¡¯ challenges based on verification time and the frequent itemsets of duplicate verification data in challenge sets by applying FP-Growth algorithm, and computes the batch proofs of frequent itemsets. Then the challenges are split into two parts, i.e., duplicate data and unique data according to the results of data extraction. Finally, the proofs of duplicate data and unique data are computed and combined to generate a complete proof of every original challenge. Theoretical analysis and experiment evaluation show that the algorithm reduces the verification cost and ensures the correctness of the data integrity verification by flexible batch data verification.
Å°¿öµå(Keyword) Cloud Storage   Data Integrity   Multiple Challenges   Frequent Itemsets  
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