Year: 2024
Type: article
Abstract: The escalating complexity and volume of cyber threats targeting enterprise endpoints necessitate robust, scalable, and intelligent Endpoint Detection and Response (EDR) solutions. The study sets out to plan a strong EDR framework which is designed to serve the entire organization and can be increased easily as the company grows. The framework integrates lightweight agents, a hybrid detection engine combining rule-based and behavior-based models, and a distributed microservices architecture. With these components, we get better detection and still use few resources and respond fast. Researchers test the framework by setting up enterprise environments with up to 10,000 endpoints and measure its detection, how rapidly changes are shared to every endpoint and its ability to resist attacks. The model demonstrates effectiveness in decreasing alert clutter, allows for smoother handling of data as resources are added and enhances reaction to threats in real time through analysis of the data. The proposed system also improves SOC productivity by reducing false positives and automating policy orchestration. Since the solution functions best in cloud environments, alternatives are presented for when it’s used in hybrid or confined situations. The work in this research can be modified to fit modern security needs in large businesses and supports future broken forms of EDR protection systems using AI.
Author: Rohith Aitharaju
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4411501388