Results 81 to 90 of about 2,335 (206)
Ransomware Detection Techniques: A Comparative Study [PDF]
openThis work compares different state of the art techniques for detecting ransomware, introducing a novel ransomware database to make confrontation ...
UMBRELLA, GIULIO
core
Water Environment Research, Volume 98, Issue 6, June 2026.This study presents an integrated framework linking six foundational elements of water resources management: watershed modeling, surrogate modeling, optimization, artificial intelligence, decision support systems, and monitoring. The synthesis highlights how connecting these traditionally separate domains fosters smarter, adaptive, and data‐driven ...
Hoda S. Razavi +5 more
wiley +1 more source
Ransomware Detection Using Machine Learning: A Review, Research Limitations and Future Directions
IEEE AccessRansomware attacks are on the rise in terms of both frequency and impact. The shift to remote work due to the COVID-19 pandemic has led more people to work online, prompting companies to adapt quickly.
Jamil Ispahany +3 more
doaj +1 more source
The dynamics of criminal collaboration: Multiplex ties in mafia networks
Criminology, Volume 64, Issue 2, Page 284-312, May 2026.Abstract This study examines how social embeddedness and multiplex relationships shape criminal collaboration within organized crime networks. Drawing on data from three major investigations into the ‘Ndrangheta, we analyze how kinship, clan affiliation, leadership, and prior interactions influence participation in meetings and phone calls.
Francesco Calderoni +2 more
wiley +1 more source
Comprehensive performance benchmarking and comparative analysis of active ransomware threats
Ransomware remains one of the most pervasive and disruptive cyber threats, with modern variants employing advanced techniques such as high-speed multithreaded encryption, obfuscation, and intermittent encryption to reduce detection opportunities and ...
Davies, Simon R., Macfarlane, Richard
core +1 more source
Graph-contrast ransomware detection (GCRD) with advanced feature selection and deep learning
Discover ComputingRansomware attacks represent a more potent and upcoming cybersecurity threat and traditional detection strategies have been ineffective against new and polymorphic ransomware variants.
Suneeta Satpathy, Pratik Kumar Swain
doaj +1 more source
InformationCybersecurity is normally defined as protecting systems against all kinds of cyberattacks; however, due to the rapid and permanent expansion of technology and digital transformation, the threats are also increasing. One of those new threats is ransomware,
Latifa Albshaier +2 more
doaj +1 more source
Visualizing Portable Executable Headers for Ransomware Detection: A Deep Learning-Based Approach [PDF]
Journal of Universal Computer ScienceIn recent years, the rapid evolution of ransomware has led to the development of numerous techniques designed to evade traditional malware detection methods.
Tien Quang Dam +5 more
doaj +3 more sources
Ransomware detection with Machine Learning algorithms using file segments and statistics [PDF]
openThe growing danger posed by ransomware has been a significant concern for both the public and private sectors. The emergence of new strains of this malware has outpaced the development of effective defense mechanisms.
MIOTTO, EMANUELE
core
Differential Area Analysis for Ransomware Attack Detection within Mixed File Datasets
, 2021 The threat from ransomware continues to grow both in the number of affected victims as well as the cost incurred by the people and organisations impacted in a successful attack.
Buchanan, William J +2 more
core +1 more source