Results 11 to 20 of about 2,945,918 (205)

A Method for Neutralizing Entropy Measurement-Based Ransomware Detection Technologies Using Encoding Algorithms [PDF]

Entropy, 2022
Ransomware consists of malicious codes that restrict users from accessing their own files while demanding a ransom payment. Since the advent of ransomware, new and variant ransomwares have caused critical damage around the world, thus prompting the study
Jaehyuk Lee, Kyungroul Lee
doaj   +2 more sources

E2E-RDS: Efficient End-to-End Ransomware Detection System Based on Static-Based ML and Vision-Based DL Approaches [PDF]

Sensors, 2023
Nowadays, ransomware is considered one of the most critical cyber-malware categories. In recent years various malware detection and classification approaches have been proposed to analyze and explore malicious software precisely.
Iman Almomani, Aala Alkhayer, Walid El-Shafai   +2 more
doaj   +2 more sources

Behaviour Based Ransomware Detection [PDF]

EPiC Series in Computing, 2019
Ransomware is an ever-increasing threat in the world of cyber security targeting vulnerable users and companies, but what is lacking is an easier way to group, and devise practical and easy solutions which every day users can utilise.In this paper we look at the different characteristics of ransomware, and present preventative techniques to tackle ...
Christopher Jun-Wen Chew, Vimal Kumar 0001   +1 more
openaire   +4 more sources

A Machine Learning-Based Ransomware Detection Method for Attackers’ Neutralization Techniques Using Format-Preserving Encryption [PDF]

Sensors
Ransomware, a type of malware that first appeared in 1989, encrypts user files and demands money for decryption, causing increasing global damage. To reduce the impact of ransomware, various file-based detection technologies are being developed; however,
Jaehyuk Lee, Jinwook Kim, Hanjo Jeong, Kyungroul Lee   +3 more
doaj   +2 more sources

Cryptographic ransomware encryption detection: Survey [PDF]

Computers & Security, 2023
The ransomware threat has loomed over our digital life since 1989. Criminals use this type of cyber attack 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.
Kenan Begovic, Abdulaziz Al-Ali 0001, Qutaibah M. Malluhi   +2 more
openaire   +6 more sources

Ransomware Detection Model Based on Adaptive Graph Neural Network Learning

Applied Sciences
Ransomware is a type of malicious software that encrypts or locks user files and demands a high ransom. It has become a major threat to cyberspace security, especially as it continues to be developed and updated at exponential rates. Ransomware detection
Jun Li, Gengyu Yang, Yanhua Shao
doaj   +2 more sources

Blockchain security for ransomware detection [PDF]

CoRR
This manuscript was submitted to the journal TELKOMNIKA (https://www.scopus.com/sourceid/21100256101). Title: "Interpretable machine learning for ransomware detection". Status: Under review. Dataset and code available at Mike Nkongolo Wa Nkongolo (2023). UGRansome dataset. Kaggle. https://www.kaggle.com/dsv/7172543 [Accessed 23 July 2024].
Elodie Ngoie Mutombo, Mike Wa Nkongolo
core   +5 more sources

Ransomware: stages, detection and evasion [PDF]

, 2021
Ransomware attacks has been increasing lately with companies suffer monetarily, wasted business opportunity and wasted time. Big companies are now targeted as they are more profitable for ransomware threat actor.
Yus Kamalrul, Mohamed Yunus, Syahrulanuar, Ngah   +1 more
core   +1 more source

Adaptive secure malware efficient machine learning algorithm for healthcare data

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed, Abdullah Lakhan, Dilovan Asaad Zebari, Karrar Hameed Abdulkareem, Jan Nedoma, Radek Martinek, Usman Tariq, Majed Alhaisoni, Prayag Tiwari   +8 more
wiley   +1 more source

User privacy prevention model using supervised federated learning‐based block chain approach for internet of Medical Things

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract This research focuses on addressing the privacy issues in healthcare advancement monitoring with the rapid establishment of the decentralised communication system in the Internet of Medical Things (IoMT). An integrated blockchain homomorphic encryption standard with an in‐build supervised learning‐based smart contract is designed to improvise ...
Chandramohan Dhasarathan, Mohammad Kamrul Hasan, Shayla Islam, Salwani Abdullah, Shailesh Khapre, Dalbir Singh, Abdulaziz A. Alsulami, Ali Alqahtani   +7 more
wiley   +1 more source