Evaluation of P2P and cloud computing as platform for exhaustive key search on block ciphers
- Authors
- Yoon, JunWeon; Hong, TaeYoung; Choi, JangWon; Park, ChanYeol; Kim, KiBong; Yu, HeonChang
- Issue Date
- 11월-2018
- Publisher
- SPRINGER
- Keywords
- P2P computing; Cloud computing; Virtualization; Block cipher; DES
- Citation
- PEER-TO-PEER NETWORKING AND APPLICATIONS, v.11, no.6, pp.1206 - 1216
- Indexed
- SCIE
SCOPUS
- Journal Title
- PEER-TO-PEER NETWORKING AND APPLICATIONS
- Volume
- 11
- Number
- 6
- Start Page
- 1206
- End Page
- 1216
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/72016
- DOI
- 10.1007/s12083-018-0641-5
- ISSN
- 1936-6442
- Abstract
- Over the years, parallel computing models have been proposed to solve large-scale application problems. P2P and cloud computing are well-known distributed computing models and have the advantage of running and implementing the parallel computing. Applying the advantages of both models can enhance the benefits of parallel computing. In this paper, we analyze the efficiency of key search algorithm by combining P2P and cloud computing. For our experiment, we apply the key search algorithm in the field of cryptography. The length of the key, which is stable criterion of cryptographic algorithm, is judged according to the amount of exhaustive key search. And the key space required for the whole investigation is easy to divide and is very appropriate for parallel calculation of P2P environment. In addition, cloud computing can provide the fitting environment to meet the various user requirements using virtualization technology. We conduct the following two performance experiments with P2P and cloud computing. First, we propose the method to guarantee the performance in P2P environment based on virtualization. Next, we simulate the performance of the suggested encryption method in the aforementioned system environment. Results reveal effectiveness and validity of the proposed system environment, which can also provide both scalability and flexibility.
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Collections - Graduate School > Department of Computer Science and Engineering > 1. Journal Articles
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