Cybersecurity hygiene project encompasses a set of routine practices critical for maintaining the security and well-being of users, devices, networks, and sensitive data within organizations. This project focuses on strategies to bolster cyber hygiene through the implementation of a research-driven, low-impact sandboxing approach. The primary objective is to investigate and analyze vulnerabilities and potential attack vectors originating from both internal and external sources.
PROJECT COMPONENTS:
METADATA COLLECTION: The project entails a methodical collection of malware Portable Executable (PE) files sourced from Malware Bazar. These files are subsequently subjected to execution within a controlled sandbox environment to conduct dynamic analysis.
SANDBOXING TECHNOLOGY: The project leverages sandboxing technology to create a controlled and secure environment for analyzing potentially malicious activities. This sandboxing approach allows for the safe execution of suspicious code, enabling in-depth examination without risking the organization’s network or systems.
MACHINE LEARNING: Advanced machine learning techniques analyze and classify data based on the collected data from the sandbox environment. These technologies enable the identification of evolving attack patterns and the creation of more effective security rules.
OUTCOMES:
This project has yielded a valuable open-source dataset for researchers, along with the publication of a conference paper.