Detection of ransomware attacks using federated learning based on the CNN model
Computing is still under a significant threat from ransomware, which necessitates prompt action to prevent it. Ransomware attacks can have a negative impact on how smart grids, particularly digital substations. In addition to examining a ransomware detection method using artificial intelligence (AI), this paper offers a ransomware attack modeling technique that targets the disrupted operation of a digital substation. The first, binary data is transformed into image data and fed into the convolution neural network model using federated learning. The experimental findings demonstrate that the suggested technique detects ransomware with a high accuracy rate.
Code (0)
등록된 구현이 없습니다.
Tasks
Federated LearningMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
FedDICE: A ransomware spread detection in a distributed integrated clinical environment using federated learning and SDN based mitigation
An integrated clinical environment (ICE) enables the connection and coordination of the internet of medical things around the care of patients in hospitals. However, ransomware attacks and their spread on hospital infras…
Federated LearningPrivacy PreservingMinerva: A File-Based Ransomware Detector
Ransomware attacks have caused billions of dollars in damages in recent years, and are expected to cause billions more in the future. Consequently, significant effort has been devoted to ransomware detection and mitigati…
feature selectionRansomware Detection and Classification using Machine Learning
Vicious assaults, malware, and various ransomware pose a cybersecurity threat, causing considerable damage to computer structures, servers, and mobile and web apps across various industries and businesses. These safety c…
ClassificationRansomware Detection using Process Memory
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 mec…
Federated Cyber Defense: Privacy-Preserving Ransomware Detection Across Distributed Systems
Detecting malware, especially ransomware, is essential to securing today's interconnected ecosystems, including cloud storage, enterprise file-sharing, and database services. Training high-performing artificial intellige…
Federated Learning