Cryptographic ransomware encryption detection: Survey

The ransomware threat has loomed over our digital life since 1989. Criminals use this type of cyber at-tack to lock or encrypt victims' data, often coercing them to pay exorbitant amounts in ransom. The damage ransomware causes ranges from monetary losses paid for ransom at best to endangering human lives. Cryptographic ransomware, where attackers encrypt the victim's data, stands as the predominant ransomware variant. The primary characteristics of these attacks have remained the same since the first ransomware attack. For this reason, we consider this a key factor differentiating ransomware from other cyber attacks, making it vital in tackling the threat of cryptographic ransomware. This paper proposes a cyber kill chain that describes the modern crypto-ransomware attack. The survey focuses on the En-cryption phase as described in our proposed cyber kill chain and its detection techniques. We identify three main methods used in detecting encryption-related activities by ransomware, namely API and Sys-tem calls, I/O monitoring, and file system activities monitoring. Machine learning (ML) is a tool used in all three identified methodologies, and some of the issues within the ML domain related to this survey are also covered as part of their respective methodologies. The survey of selected proposals is conducted through the prism of those three methodologies, showcasing the importance of detecting ransomware during pre-encryption and encryption activities and the windows of opportunity to do so. We also ex-amine commercial crypto-ransomware protection and detection offerings and show the gap between aca-demic research and commercial applications. & COPY; 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )