Data Recovery Using Brute Force Algorithm: A Review

Year : 2024 | Volume : 15 | Issue : 03 | Page : 10 16
    By

    Shifa Thamkin S.,

  • Raksha H.M.,

  • Mohammed Rafi,

  1. Student, Department of Computer Science and Engineering, University BDT College of Engineering, Davangere, Karnataka, India
  2. Student, Department of Computer Science and Engineering, University BDT College of Engineering, Davangere, Karnataka, India
  3. Professor, Department of Computer Science and Engineering, University BDT College of Engineering, Davangere, Karnataka, India

Abstract

This article delves into the intriguing field of data recovery, with a particular emphasis on the brute force approach, a powerful yet frequently underappreciated method. We begin by exploring the evolution of data recovery techniques since the 1970s and 1980s, examining traditional methods used to retrieve lost or corrupted data. Following this historical perspective, the article provides a brief overview of various methodologies employed in data recovery, including techniques that leverage brute force. Brute force approaches, while often time-consuming, can be highly effective in recovering lost data, particularly when other methods fall short. The article further compares brute force techniques with more modern data recovery methods, such as those utilizing machine learning algorithms, to highlight their relative strengths and weaknesses. In addition, we discuss potential future advancements in the field, focusing on improving computational efficiency and integrating brute force methods with emerging technologies like quantum computing and parallel processing. These advancements hold the promise of making data recovery faster and more accurate, thus broadening the application of brute force in critical situations. Ultimately, this article aims to provide a comprehensive overview of data recovery techniques, with a forward-looking perspective on how brute force may evolve in the context of technological progress.

Keywords: Data recovery, brute force, time complexity, space complexity, corrupted data, machine learning, quantum computing

[This article belongs to Journal of Computer Technology & Applications ]

How to cite this article:
Shifa Thamkin S., Raksha H.M., Mohammed Rafi. Data Recovery Using Brute Force Algorithm: A Review. Journal of Computer Technology & Applications. 2024; 15(03):10-16.
How to cite this URL:
Shifa Thamkin S., Raksha H.M., Mohammed Rafi. Data Recovery Using Brute Force Algorithm: A Review. Journal of Computer Technology & Applications. 2024; 15(03):10-16. Available from: https://journals.stmjournals.com/jocta/article=2024/view=177278


References

  1. GeeksforGeeks. (2024). What is data recovery? [online] Available from: https://www.geeksforgeeks.org/what-is-data-recovery/.
  2. Boulos D, Zemljic N. (2024). Data recovery. [online] Available from: www.cs.toronto.edu/~arnold/427/15s/csc427/indepth/dataRecovery/DataRecovery_writeup.pdf.
  3. File carving. Infosec. Infosecinstitute.com. [online] Available from: https://www.infosecinstitute.com/resources/digital-forensics/file-carving/. 2018.
  4. Alkhwaja I, Albugami M, Alkhwaja A, Alghamdi M, Abahussain H, Alfawaz F, Almurayh A, Min-Allah N. Password cracking with brute force algorithm and dictionary attack using parallel programming. Appl Sci. 2023;13:5979. DOI: 10.3390/app13105979.
  5. Fields-data-recovery. (2021). How to recover lost data: A step-by-step guide. Fields-data-recovery.
    [online] Available from: https://www.fields-data-recovery.com/blog/how-to-recover-lost-data-a-step-by-step-guide.
  6. Garry. (2023). How do you create a data recovery plan? – Darwin’s Data. [online] Available from: https://darwinsdata.com/how-do-you-create-a-data-recovery-plan/.
  7. Stallings W. Cryptography and Network Security Principles and Practice, 7th edition. Global edition. SPi Global. Pearson. Malaysia. [online] Available from: https://www.cs.vsb.cz/ochodkova/
    courses/kpb/cryptography-and-network-security_-principles-and-practice-7th-global-edition.pdf.
  8. Schneier B. Applied Cryptography: Protocols, Algorithms, and Source Code in C. John Wiley & Sons: Chichester, UK; 2007.
  9. Garfinkel SL. Carving contiguous and fragmented files with fast object validation. Digital Investigation. 2007;4:2–12. DOI: 10.1016/j.diin.2007.06.017.
  10. Richard III GG, Roussev V. Scalpel: A frugal, high performance file carver. InDFRWS; 2005.
  11. Whitney L. How an 8-character password could be cracked in just a few minutes. TechRepublic. [online] Available from: https://www.techrepublic.com/article/how-an-8-character-password-could-be-cracked-in-less-than-an-hour/. 2023.
  12. Datar M, Muthukrishnan S. Estimating rarity and similarity over data stream windows. In: Algorithms—ESA 2002. Proceedings: 10th Annual European Symposium Rome, Italy. Vol. 10. Springer: Berlin, Heidelberg; 2002. pp. 323–35.
  13. Kelseyk. (2023). Best Password Practices to Defend Against Modern Cracking Attacks. Specops Software. [online] Available from: https://specopssoft.com/blog/best-password-practices-to-defend-against-modern-cracking-attacks/
  14. Scalpel – A frugal, high performance file carver – Dfrws. Dfrws. [online] Available from: https://dfrws.org/presentation/scalpel-a-frugal-high-performance-file-carver/. 2019.
  15. Carvey H, Altheide C. Digital Forensics with Open Source Tools. Elsevier: Amsterdam; 2011.
  16. Data corruption: Causes, effects & prevention DataCore. DataCore software. [online] Available from: https://www.datacore.com/glossary/data-corruption/. 2024.
  17. Carrier B. File System Forensic Analysis. Addison-Wesley Professional: Pearson, USA Education, Inc.; 2005. ISBN: 0-32-126817-2.
  18. Kent K, Chevalier S, Grance T, Dang H. Guide to integrating forensic techniques into incident response recommendations of the National Institute of Standards and Technology. National Institute of Standards and Technology. [online] Available from: https://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-86.pdf. 2006.
  19. Böhme R, Freiling FC. On metrics and measurements. In: Dependability Metrics; 2008. pp. 7–13. DOI: 10.1007/978-3-540-68947-8_2.
  20. Goodrich MT, Tamassia R. Algorithm Design: Foundations, Analysis, and Internet Examples. John Wiley & Sons: Chichester, UK; 2001.
  21. Ramkumar V, Balaji SB, Sasidharan B, Vajha M, Krishnan MN, Kumar PV. Codes for distributed storage. Foundations and Trends® in Communications and Information Theory. 2022;19:547–813. DOI: 10.1561/0100000115.
Regular Issue Subscription Review Article
Volume 15
Issue 03
Received 14/08/2024
Accepted 23/09/2024
Published 07/10/2024
474

Login


My IP

PlumX Metrics