CryptoLock (and Drop It): Stopping Ransomware Attacks on User Data
By Nolen Scaife, Henry Carter, Patrick Traynor, Kevin R. B. Butler. IEEE International Conference on Distributed Computing Systems, 2016
446 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing
View Paper: https://www.semanticscholar.org/paper/6bd33530e5dcd90f367748bf88ba1ff337b7caf4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Alessandro Barenghi
- Naima Kaabouch
- Stefano Zanero
- Chaminda T. E. R. Hewage
- Imtiaz A. Khan
- Zainab Alkhalil
- Liqaa F. Nawaf
- Andrea Continella
In Computer Networks and Communications
In Signal Processing
- Naima Kaabouch
- Stefano Zanero
- Chaminda T. E. R. Hewage
- Imtiaz A. Khan
- Zainab Alkhalil
- Liqaa F. Nawaf
- Fatima Salahdine
Citations in the corpus
- ShieldFS: a self-healing, ransomware-aware filesystem (2016, methodology): “[14] published two ransomware detection approaches, respectively UNVEIL and CryptoDrop.”
- Phishing Attacks: A Recent Comprehensive Study and a New Anatomy (2021, background): “…that user education is not effective as security is not the main goal for users and users do not have a motivation to educate themselves about phishing (Scaife et al., 2016), while others con fi rm that user education could be effective if designed properly (Evers, 2006; Whitman and Mattord, 2012).”
- Social Engineering Attacks: A Survey (2019, background): “In [64], the authors proposed an early warning detection system called CryptoDrop that is able to alert the employee in case of suspicious activity on the user data.”