TY  - JOUR
T1  - An Improved Protection Approach for Protecting from Ransomware Attacks
AU  - Guvçi, Ferhat
AU  - Şenol, Ahmet
PY  - 2023
DA  - August
DO  - 10.26650/JODA.1312412
JF  - Journal of Data Applications
JO  - JoDA
PB  - İstanbul Üniversitesi
WT  - DergiPark
SN  - 2980-3357
SP  - 69
EP  - 82
IS  - 1
LA  - en
AB  - Ransomware is a type of malicious software that has become a significant threat to the security and availability of computer systems and data. Ransomware has found a special place in the world of malware and is the subject of many scientific studies, as it is a malicious software designed to benefit the user directly by using sensitive data of individuals or institutions. This research provides an in-depth study of ransomware, including its history and evolution. The primary objective of this research is to analyze the impact of ransomware attacks on organizations and individuals and to evaluate the effectiveness of existing countermeasures and mitigation strategies. To achieve this objective, a comprehensive review of the literature and security provider sources on ransomware was conducted and data analyzed from real-world ransomware incidents. The findings indicated that ransomware attacks are becoming more sophisticated and complex, targeting a wide range of industries and geographical regions, which poses a significant financial and reputational risk to victims. Moreover, this research showed that traditional security measures such as antivirus software, firewalls, and backups may not be sufficient to prevent or recover from ransomware attacks. Instead, artificial intelligence applications and a multi-layered defense approach that combined technical, administrative, and legal measures is necessary to reduce the likelihood and impact of ransomware incidents. Overall, this article provides a valuable contribution to the understanding of ransomware threats and the development of effective countermeasures, and contributes to the literature especially on defense methods by explaining how to apply defense methods against ransomware attacks in light of field experience.
KW  - encryption
KW  - machine learning
KW  - malware
KW  - ransomware
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UR  - https://doi.org/10.26650/JODA.1312412
L1  - https://dergipark.org.tr/tr/download/article-file/3200507
ER  -