Organization sPecific Threat Intelligence Mining and sharing
The OPTIMA project (Organization sPecific Threat Intelligence Mining and sharing) aims to design techniques and tools for the extraction of Threat Intelligence targeted to organizations using ML algorithms, and effectively share a...
The OPTIMA project (Organization sPecific Threat Intelligence Mining and sharing) aims to design techniques and tools for the extraction of Threat Intelligence targeted to organizations using ML algorithms, and effectively share attack records using privacy-preserving methods. The project will use technologies to protect societies from cyber-attacks and sophisticated threats prioritized in the European Council’s New Strategic Agenda. The key beneficiaries of the project are (a) security operation center-to support real time monitoring (b) incident response, threat hunting, fraud detection team-to prioritize risk (c), operational leaders- to prioritize activities of IT staff and (d) Strategic leaders such as Chief Information Security Officers - to make well-informed business decisions. This project will be executed at the University of Padua, under the supervision of Prof. Mauro Conti. The project will investigate solutions for the core questions: RQ1: How effectively can ML algorithms extract organization-specific threat artefacts to be utilized for preparing actionable Threat Intelligence? RQ2: How can organizations share threat intelligence without disclosing their private information to others?
The objectives (SO) of the project are as follows:
1. SO1-To develop techniques for automatic extraction of threat intelligence using OSINT data for diverse IT industries (health care, finance, IoT, education, etc.) using deep learning approaches.
2. SO2-To create a novel automated system to derive Indicator of Compromise (IOC) based on word embedding and syntactic dependencies of words to identify unseen IOCs. Utilizing the extracted IOCs a threat index will be estimated to define the impact of threat and attack trends across individual organizations;
3. SO3-To build a system by integrating cryptographic tools and Federated learning which will enable an organization to anonymously share threat logs with different parties in a privacy-preserving mannerver más
Seleccionando "Aceptar todas las cookies" acepta el uso de cookies para ayudarnos a brindarle una mejor experiencia de usuario y para analizar el uso del sitio web. Al hacer clic en "Ajustar tus preferencias" puede elegir qué cookies permitir. Solo las cookies esenciales son necesarias para el correcto funcionamiento de nuestro sitio web y no se pueden rechazar.
Cookie settings
Nuestro sitio web almacena cuatro tipos de cookies. En cualquier momento puede elegir qué cookies acepta y cuáles rechaza. Puede obtener más información sobre qué son las cookies y qué tipos de cookies almacenamos en nuestra Política de cookies.
Son necesarias por razones técnicas. Sin ellas, este sitio web podría no funcionar correctamente.
Son necesarias para una funcionalidad específica en el sitio web. Sin ellos, algunas características pueden estar deshabilitadas.
Nos permite analizar el uso del sitio web y mejorar la experiencia del visitante.
Nos permite personalizar su experiencia y enviarle contenido y ofertas relevantes, en este sitio web y en otros sitios web.