Multiple security policies for classified data items in replicated DRTDBS


연구 분야: Databases



학회: International Journal of Data Science and Analytics


초록

Dealing with security requirements in fixed budgets and strict time limits is becoming increasingly complex, time-consuming, and resource-intensive. In addition, the system becomes more complicated when protecting the replicated distributed real-time database system (RDRTDBS) under many security guidelines. Vital structures, military, government, and financial institutions face immense pressure to secure their databases from unauthorized access. Such specifications mandate a rigorous security scan of each device before they are deemed appropriate for use. In the current paper, we demonstrate that performance and security requirements can be achieved simultaneously. We introduce PASS, a performance-aware security-satisfied replication protocol for data replica sites. Our proposed solution (i.e., PASS) is heuristic rather than optimal. Our main concept is to minimize the number of encryption operations for the least important or rarely accessed data items. PASS reduces the number of encryption operations by categorizing data items into three categories: (i) most secure, (ii) medium secure, and (iii) least secure. The most secure and medium secure data items are protected by the key generated from our proposed algorithm and the existing algorithm, respectively. In contrast, the Least Secure data items are kept unencrypted, and no encryption operation is performed to secure such data items. Effectively minimizing encryption operations implies a reduction in computation and power consumption at data replica sites. Unlike traditional encrypted RDRTDBS that stores data encryption keys on disks and encrypts all data items, we present a hybrid key generation method that encrypts only the important data items. Based on the experimental results, we conclude that PASS reduces the number of encryption operations and provides high-level protection in RDRTDBS.


Author Profile
Pratik Shrivastava

School of Computer Science Engineering and Technology Bennett University Greater Noida UP 201310 India

Andorra

📄 논문 정보

발행 연도 2023년
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출판 국가 Andorra
사이트 Springer
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