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Evaluation of live forensic techniques in ransomware attack mitigation
- Source :
- Forensic Science International: Digital Investigation. 33:300979
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- Memory was captured from a system infected by ransomware and its contents was examined using live forensic tools, with the intent of identifying the symmetric encryption keys being used. NotPetya, Bad Rabbit and Phobos hybrid ransomware samples were tested during the investigation. If keys were discovered, the following two steps were also performed. Firstly, a timeline was manually created by combining data from multiple sources to illustrate the ransomware's behaviour as well as showing when the encryption keys were present in memory and how long they remained there. Secondly, an attempt was made to decrypt the files encrypted by the ransomware using the found keys. In all cases, the investigation was able to confirm that it was possible to identify the encryption keys used. A description of how these found keys were then used to successfully decrypt files that had been encrypted during the execution of the ransomware is also given. The resulting generated timelines provided a excellent way to visualise the behaviour of the ransomware and the encryption key management practices it employed, and from a forensic investigation and possible mitigation point of view, when the encryption keys are in memory.<br />11 pages, 10 figures
- Subjects :
- FOS: Computer and information sciences
Computer Science - Cryptography and Security
Computer science
E.3
Cyber-security
Encryption
Computer security
computer.software_genre
Pathology and Forensic Medicine
K.6.5
Centre for Distributed Computing, Networking and Security
Ransomware
Point (typography)
business.industry
AI and Technologies
Computer Science Applications
Medical Laboratory Technology
Symmetric-key algorithm
Key (cryptography)
Live Forensics, Ransomware
business
Cryptography and Security (cs.CR)
Law
computer
Information Systems
Subjects
Details
- ISSN :
- 26662817
- Volume :
- 33
- Database :
- OpenAIRE
- Journal :
- Forensic Science International: Digital Investigation
- Accession number :
- edsair.doi.dedup.....5cd7eb1abaded5c9ff908610b1989bd3
- Full Text :
- https://doi.org/10.1016/j.fsidi.2020.300979