Results 71 to 80 of about 2,945,918 (205)

Regulating critical technologies: National security and intellectual property

The Journal of World Intellectual Property, Volume 29, Issue 3, Page 435-461, November 2026.
Abstract In recent years, claims of ‘national security’ have surged internationally to protect various security interests including public health, economic security and cybersecurity. National industrial strategies for building critical technologies challenge the scope of ‘national security’ in international intellectual property (IP) protection ...
Phoebe Li, Atilla Kasap
wiley   +1 more source

Graph-contrast ransomware detection (GCRD) with advanced feature selection and deep learning

Discover Computing
Ransomware 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

When Business Breaks the Rules: The Value of a Criminology‐Informed “Organizational” Perspective for the Regulation of White‐Collar and Corporate Crimes

Regulation &Governance, Volume 20, Issue 4, Page 1323-1340, October 2026.
ABSTRACT This article argues that if the aspiration is to enhance regulatory and governance responses to white‐collar and corporate crimes, consideration of the organization of these offending behaviors must be central to the scholarly, practice, and policy discussion.
Nicholas Lord, Michael Levi
wiley   +1 more source

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  

Leveraging Machine Learning for Ransomware Detection

, 2022
The current pandemic situation has increased cyber-attacks drastically worldwide. The attackers are using malware like trojans, spyware, rootkits, worms, ransomware heavily.
Rani, Nanda, Dhavale, Sunita Vikrant
core  

Detecting Ransomware Through Dynamic API Call Monitoring and Machine Learning

Applied Sciences
Ransomware is malicious software that encrypts user files, rendering them inaccessible unless a ransom is paid to the attacker. Ransomware detection has been a challenge recently. In this paper, we present a comprehensive analysis of ransomware detection
Anas AlMajali, Waleed Dweik, Yahia Abdelghafur, Obada Alhasan, Omar Tawalbeh, Moustafa Amer   +5 more
doaj   +1 more source

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, Volume 1, Issue 2, September 2026.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source

MIRAD: A Method for Interpretable Ransomware Attack Detection

IEEE Access
In the face of escalating crypto-ransomware attacks, we introduce MIRAD, a novel dynamic detection method. MIRAD leverages machine learning to continuously monitor API calls and registry entries, detecting ransomware at all stages of infection while ...
Bartosz Marcinkowski, Maja Goschorska, Natalia Wilenska, Jakub Siuta, Tomasz Kajdanowicz   +4 more
doaj   +1 more source

Lightweight Multilayer IoT Attack Detection: An Evaluation of the Semi‐Automated Intrusion Detection System (SAIDS) Framework on Simulated and Real‐World Traffic

SECURITY AND PRIVACY, Volume 9, Issue 5, September/October 2026.
ABSTRACT The rapid growth of the Internet of Things (IoT) creates concern around multilayer cyber‐attacks that exploit interactions between physical, network, and application layers. Traditional Intrusion Detection Systems (IDS) often utilize outdated datasets, high dimensional features, or computationally heavy deep learning models, which are not ...
Badeea Al Sukhni, Soumya K. Manna, Jugal M. Dave, Leishi Zhang, M. A. Hannan Bin Azhar   +4 more
wiley   +1 more source

Ransomware Detection Using Machine Learning: A Review, Research Limitations and Future Directions

IEEE Access
Ransomware 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, Md. Rafiqul Islam, Md. Zahidul Islam, M. Arif Khan   +3 more
doaj   +1 more source