Database Security – Need In APA Format with no less than 1000 words No Plagiarism Need Plagiarism Report

Topic – Efficient Disaster Recovery for Database and at least 5 references

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DATABASE SECURITY

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DATABASE SECURITY

Efficient Disaster Recovery for Database

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Efficient disaster recovery techniques restore data to a usable state. Database systems and filing systems require recovery systems to handle data failure. According to Cooper et al, (2010) failures are events where systems do not perform as specified. System failure results from hardware faults such as power outages, software failures result from virus infection and also due to human error. A system error represents an incorrect state due to incorrect information keys. Systems require components and algorithms to operate efficiently by correcting resulting errors and restoring functions to a previous functional state (Alsirhani, Bodorik and Sampalli, 2017). Sometimes failures corrupt both the data and recovery data. Different recoveries are required for the recovery of the different failures in database and filing systems.

Efficient data recovery methods rely on a structured form of data recovery including data structure and availability of recovery data. The structure and organization of data enhances its manipulation for easier recovery. Recovery process must understand the interaction of data with the structure of recovery data. Different organizations are affected by unique failures based on the systems of recovery. Different techniques can be combined to handle the failures in data management (Cooper et al., 2010). While one technique can be successful in one dataset or organization, the system may not be applicable in other systems or organizations.

Databases use different types of recovery systems for data recovery. Recovery systems must have different qualities (Goel, 2013). A good recovery system must recover data to the correct state. A correct state is one that exists at some point before system failure. Recovery to a previous state allows the restoration of existing data files some of which may not have existed before. The state of recovery must be valid and consistent (Sharma et al., 2012). Finally, crash resistance allows system recovery to retrieve data in its original and consistent state.

Data recovery techniques ensure that can be retrieved, restarted and maintained consistently. After a system crash, experts run a salvation program to restore previous data. Salvation programs do not use recovery data but scans the database to determine the extent of damage. Files containing data from previous forms are backed up to restore files to a valid state (Sharma et al., 2012). Besides the main file, differential files are used to record alterations. These files are merged with the main files for purposes of auditing, crash resistance and recovery. Files are copied on multiple files and held differently. The files can be updated based on the need and urgency and further compared to ensure consistency (Sim-Tang, 2013). Data files are copied on archival storage through incremental dumping to create checkpoints for data update. Audit trails record sequential file actions used to restore files to their previous state before system failure. Finally, data recovery is enhanced through careful replacement, which avoids data updates.

Different techniques of data recovery must implement each other in different environments and organizations. Data recovery techniques are essential for crash resistance; ensure backing out, crash recovery and consistency of data. Salvation programs and audit trails are applied to enhance data consistency and safeguard against data loss.

References

Alsirhani, A., Bodorik, P., & Sampalli, S. (2017, September). Improving database security in cloud computing by fragmentation of data. In 2017 International Conference on Computer and Applications (ICCA) (pp. 43-49). IEEE.

Cooper, B. F., Silberstein, A., Tam, E., Ramakrishnan, R., & Sears, R. (2010, June). Benchmarking cloud serving systems with YCSB. In Proceedings of the 1st ACM symposium on Cloud computing (pp. 143-154).

Goel, A. (2013). U.S. Patent No. 8,560,879. Washington, DC: U.S. Patent and Trademark Office.

Sharma, S., Agiwal, P., Gaherwal, R., Mewada, S., & Sharma, P. (2012). Analysis of Recovery Techniques in Data Base Management System. Research Journal of Computer and Information Technology Sciences _____________________E-ISSN, 2320, 6527.

Sim-Tang, S. Y. (2013). U.S. Patent No. 8,364,648. Washington, DC: U.S. Patent and Trademark Office.