Collection and analysis system of malware based on the human immune system

Abstract

The malicious code are the main concern current. The mechanism that the human immune system uses to detect and protect organizations that threaten the human body is very efficient and can be adapted to detect malware on the internet. Therefore, this proposal aims to develop an architecture that performs distributed collection of malware, also to analyze, detect and classify the artifacts collected. To achieve this goal, each malicious artifact will have a signature to represent the malware. In addition, the system will be able to detect known and unknown malware. Also compose the system an immune response agent which is responsible for classification of malware taking into account a behavioral analysis provided by flow data NetFlow and adaptability of an artificial neural network. Thus, this project aims to absorb the concepts of a human immune system, such as, distribution and parallelism, protection mechanisms in multi-layer, autonomy, adaptability and memory, infectious agents detection and others to provide a analysis and classification system malware fast, effective and autonomous.