AWS
MALWARE
ANDROID
Gruppo SCAI had the opportunity to collaborate with Zayed University on the Proof of Concept (PoC) solution of an automated malware analysis system.
The primary objective of this project was threefold: to develop a system for the automated analysis of incoming Android malware, to create algorithms to characterise and track the aggregate network footprint of threats, and to design a framework to generate intelligence on the sources of malware threats.
To achieve the set objectives, Gruppo SCAI implemented a number of strategic activities. First, an automatic analysis system was created using the AWS infrastructure. Secondly, machine learning environments for algorithm development were implemented. Thirdly, machine learning libraries were used for the identification and training of the models. Finally, the Zayed University dataset was analysed to understand the nature of Android malware and to develop learning algorithms.
The automated analysis system provides a proactive defence against Android malware, reducing the risk of cyber threats. By automating the analysis process, the client can now quickly respond to emerging threats and mitigate potential risks. In addition, the framework generates valuable information on the sources of cyber threats, providing the customer with useful information for future security measures.
The infrastructure used for this project includes AWS services, with detailed specific configurations for VM instances and machine learning environments.
The integration of machine learning models and analysis tools allows Android threats to be effectively identified and tracked, thus improving the client’s cyber security.
Gruppo SCAI’s implementation of an automated malware analysis system not only meets the client’s specific objectives, but also enhances its cybersecurity capabilities, ensuring a more secure digital environment.
expertise
Business Intelligence & Big Data Analysis
Cyber Security
