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  Authors

Arun Tyagi

  Keywords

LockBit Black; Ransomware; Malware; Attack Signatures; Analysis

  Abstract


This paper focuses on analyzing the LockBit Black ransomware, a recent and potent threat that has particularly targeted the healthcare sector. As ransomware continues to evolve and combine various malicious functionalities, it becomes crucial to detect its patterns of infection and persistence methods to prevent data, system, and network contamination. By identifying these infections early, containment can be achieved, and further spread can be avoided. The paper discusses reports and data leaks highlighting LockBit Black's significant contributions to attacks. The method chapter explores different approaches to detecting ransomware, such as static, dynamic, and network-based methods. The paper then describes the specific approach taken in this study, including the tools utilized. The results and discussion section presents the creation of two sandbox environments for manual analysis and the corresponding findings. Additionally, the paper introduces five free online malware analysis platforms, whose reports were compared with the manual results. The IoCs (Indicators of Compromise) identified during the analysis are provided, enabling other researchers to create signatures for early detection, prevention, and the recording of forensic evidence. This study aims to analyze LockBit Black ransomware comprehensively and identify its footprints to serve as a valuable resource.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2309316

  Paper ID - 243609

  Author type - Indian Author

  Page Number(s) - c703-c717

  Pubished in - Volume 11 | Issue 9 | September 2023

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.36146

  No Of Downloads - 135

  Author Country - India, 382305, Gandhinagar, Gandhinagar, 382305, Science and Technology

  Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Published Paper PDF : - http://www.ijcrt.org/papers/IJCRT2309316

  Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRT2309316

  Published Paper PDF Downlaod: - download.php?file=IJCRT2309316

  Cite this article

Arun Tyagi,   "Analysis Of Lockbit Black Ransomware To Identify Its Static, Dynamic And Network Footprints For Generating Its Detection Signatures", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 9, pp.c703-c717, September 2023, Available at :http://www.ijcrt.org/papers/IJCRT2309316.pdf

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