The existing methods of ransomware detection have limitations. To be specific, static analysis is not effective to obfuscated binaries, while dynamic analysis is usually restricted to a certain platform and often takes tens of minutes. In this paper, we propose a block-level monitoring system to detect potentially malicious cryptographic operations. We carry out statistical analysis to find heuristic rules to distinguish between normal and encrypted blocks. In order to apply the heuristic rule to the filesystem without kernel modification, we adopt Filesystem in Userspace (FUSE) and define our filesystem Rcryptect for real-time detection of cryptographic function. We demonstrate the protection of well-known ransomware and show that various cryptographic functions can be detected with about 13% overhead.

Grover’s search algorithm allows a quantum adversary to find a$k$-bit secret key of a block cipher by making O($2^{k/2}$) block cipher queries. Resistance of a block cipher to such an attack is evaluated by quantum resources required to implement Grover’s oracle for the target cipher. The quantum resources are typically estimated by the$\textit {T}$-depth of its circuit implementation and the number of qubits used by the circuit (width). Since the AES S-box is the only component which requires$\textit {T}$-gates in a quantum implementation of AES, recent research has put its focus on efficient implementation of the AES S-box. However, any efficient implementation with low$\textit {T}$-depth will not be practical in the real world without considering qubit consumption of the implementation. In this work, we propose three methods of trade-off between time and space for the quantum implementation of the AES S-box. In particular, one of our methods turns out to use the smallest number of qubits among the existing methods, significantly reducing its$\textit {T}$-depth.