Correlating Heterogeneous Information Sources to Predict DDoS Attacks

• Grant number: 23/13307-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): October 01, 2023
• Effective date (End): September 30, 2024
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Acordo de Cooperação: MCTI/MC
• Principal Investigator: Michele Nogueira Lima
• Grantee: Lucas Albano Olive Cruz
• Host Institution: Instituto de Ciências Exatas (ICEx). Universidade Federal de Minas Gerais (UFMG). Ministério da Educação (Brasil). Belo Horizonte , SP, Brazil
• Associated research grant: 18/23098-0 - MENTORED: from modeling to experimentation - predicting and detecting DDoS and zero-day attacks, AP.TEM

Abstract

Information sources are essential for the efficient prediction and detection of DDoS attacks. Efficiency is directly related to the quality of these information sources, but not always all the requirements for efficient prediction and detection are achieved in a single source. Thus, the correlation of information sources is presented as an important tool to enrich the base information used in decision-making by the employed prediction and detection mechanisms. Undoubtedly, correlating heterogeneous sources of information is not an easy task. There are several challenges, from the data formats, the different moments of the acquired visions and mainly the volume of data necessary to be treated. Thus, in this scientific initiation project, we intend to analyze how to correlate two heterogeneous data sources and apply this correlation in the prediction of DDoS attacks in the context of IoT treated in the scope of the MENTORED project. (AU)