| Title | Study on Systematic Ransomware Detection Techniques |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Lee, Sun-Jin, Shim, Hye-Yeon, Lee, Yu-Rim, Park, Tae-Rim, Park, So-Hyun, Lee, Il-Gu |
| Conference Name | 2021 23rd International Conference on Advanced Communication Technology (ICACT) |
| Keywords | composability, Computer crime, endpoint detection and response (EDR), feature extraction, Google rapid response, Internet of Things, Linux, Metrics, Open Source hids SECurity (OSSEC), open-source EDR, osquery, pubcrawl, ransomware, ransomware detection, Resiliency, Systematics, Tools |
| Abstract | Cyberattacks have been progressed in the fields of Internet of Things, and artificial intelligence technologies using the advanced persistent threat (APT) method recently. The damage caused by ransomware is rapidly spreading among APT attacks, and the range of the damages of individuals, corporations, public institutions, and even governments are increasing. The seriousness of the problem has increased because ransomware has been evolving into an intelligent ransomware attack that spreads over the network to infect multiple users simultaneously. This study used open source endpoint detection and response tools to build and test a framework environment that enables systematic ransomware detection at the network and system level. Experimental results demonstrate that the use of EDR tools can quickly extract ransomware attack features and respond to attacks. |
| DOI | 10.23919/ICACT51234.2021.9370472 |
| Citation Key | lee_study_2021 |
Study on Systematic Ransomware Detection Techniques