Results 31 to 40 of about 11,522 (181)

A cyber-kill-chain based taxonomy of crypto-ransomware features [PDF]

, 2019
In spite of being just a few years old, ransomware is quickly becoming a serious threat to our digital infrastructures, data and services. Majority of ransomware families are requesting for a ransom payment to restore a custodian access or decrypt data ...
Benedetto, L, Bianchi, G, Conti, M, Dargahi, T, Dehghantanha, A, Nikkhah Bahrami, P   +5 more
core   +2 more sources

A multilabel fuzzy relevance clustering system for malware attack attribution in the edge layer of cyber-physical networks [PDF]

, 2020
The rapid increase in the number of malicious programs has made malware forensics a daunting task and caused users’ systems to become in danger. Timely identification of malware characteristics including its origin and the malware sample family would ...
Alaeiyan, M, Conti, M, Dargahi, T, Dehghantanha, A, Parsa, S   +4 more
core   +2 more sources

A fine-tuning of decision tree classifier for ransomware detection based on memory data [PDF]

International Journal of Data and Network Science
Ransomware has evolved into a pervasive and extremely disruptive cybersecurity threat, causing substantial operational and financial damage to individuals and businesses.
Mosleh M. Abualhaj, Mahran Al-Zyoud, Mohammad O. Hiari, Yousef Alrabanah, Mohammed Anbar, Amal Amer, Ali Al-Allawee   +6 more
doaj   +1 more source

Android Ransomware Detection From Traffic Analysis Using Metaheuristic Feature Selection

IEEE Access, 2022
Among the prevalent cyberattacks on Android devices, a ransomware attack is the most common and damaging. Although there are many solutions for detecting Android ransomware attacks, existing solutions have limited detection accuracy and high ...
Md. Sakir Hossain, Naim Hasan, Md. Abdus Samad, Hossain Md. Shakhawat, Joydeep Karmoker, Foysol Ahmed, K. F. M. Nafiz Fuad, Kwonhue Choi   +7 more
doaj   +1 more source

Investing in Prevention or Paying for Recovery - Attitudes to Cyber Risk [PDF]

, 2019
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Broadly speaking an individual can invest time and effort to avoid becoming victim to a cyber attack and/or
A Cartwright, A Kharraz, A Laszka, A Tversky, A Tversky, AC Johnston, B Johnson, C Starmer, D Kahneman, E Field, EU Weber, G Hull, H Rosoff, M Dufwenberg, O Poulsen, R Richardson, SL Pfleeger, T O’Donoghue, TA Homonoff, U Fischbacher   +19 more
core   +2 more sources

A Survey on Ransomware Malware and Ransomware Detection Techniques

International Journal for Research in Applied Science and Engineering Technology, 2022
Abstract: is a kind of malignant programming (malware) that takes steps to distribute or hinders admittance to information or a PC framework, for the most part by scrambling it, until the casualty pays a payoff expense to the assailant. As a rule, the payoff request accompanies a cutoff time.
openaire   +1 more source

To pay or not: game theoretic models of ransomware [PDF]

, 2019
Ransomware is a type of malware that encrypts files and demands a ransom from victims. It can be viewed as a form of kidnapping in which the criminal takes control of the victim’s files with the objective of financial gain. In this article, we review and
August, Baddeley, Barlyn, Brandt, Caporusso, Cohen, Cusack, Danielson, Dutton, Gaibulloev, Hadlington, Hernandez-Castro, Hernandez-Castro, Huang, Huang, Iqbal, Jarvis, Kalaimannan, Kharraz, Lapan, Laszka, Lee, Liao, Mansfield-Devine, Muthoo, Nax, Paquet-Clouston, Pfleeger, Rashid, Sandler, Sandler, Sandler, Santifort, Schelling, Selten, Shahin, Spagnuolo, Wilson, Young   +38 more
core   +1 more source

Ransomware Detection using Process Memory

International Conference on Cyber Warfare and Security, 2022
Ransomware attacks have increased significantly in recent years, causing great destruction and damage to critical systems and business operations. Attackers are unfailingly finding innovative ways to bypass detection mechanisms, which encouraged the adoption of artificial intelligence.
Singh, Avinash, Ikuesan, Richard Adeyemi, Venter, Hein   +2 more
openaire   +3 more sources

Crypto-Ransomware Detection Through a Honeyfile-Based Approach with R-Locker

Mathematics
Ransomware is a group of malware that aims to make computing resources unavailable, demanding a ransom amount to return control back to users. Ransomware can be classified into two types: crypto-ransomware and locker ransomware. Crypto-ransomware employs
Xiang Fang, Eric Song, Cheng Ning, Huseyn Huseynov, Tarek Saadawi   +4 more
doaj   +1 more source

Hybrid-Based Analysis Impact on Ransomware Detection for Android Systems

Applied Sciences, 2021
Android ransomware is one of the most threatening attacks that is increasing at an alarming rate. Ransomware attacks usually target Android users by either locking their devices or encrypting their data files and then requesting them to pay money to ...
Rana Almohaini, Iman Almomani, Aala AlKhayer   +2 more
doaj   +1 more source