Guardianiq: Enhancement of the heuristic analysis method in computer security through machine learning and sandboxing method
ABSTRACT: With the continued appearance of new and dangerous cyber threats, the growth of cybersecurity is essential. To deal with such threats, the researchers developed a solution that uses two of the world’s most useful tools, machine learning and sandboxing methods. The use of these tools will help the entirely of the cyber world regarding the security itself; that way, the researchers will be able to ensure that users are safe from these threats. This study is something that can be used for future studies, for the fact that this requires more expert handling as well as analysis. The researchers will be just the start of a new research study that may last for more than a decade, correcting, improving, and making it more useful for the masses. The researchers started incorporating the enhancement by researching that will used to integrate the said enhancement through machine learning and sandboxing. In usual heuristic algorithms, there are instances where most malware is just being flagged by the system and there are no known instant actions that are being taken, on which our enhancement proposes. With the enhancement that researchers are proposing via machine learning and sandboxing, they will be able to train these algorithms that were previously only flagging a certain threat or quarantining it. The researcher’s enhancement will take immediate action on certain malicious software, scanning it in full and if ever found a malicious code or programming on it, will immediately quarantine the said software and then proposed on “healing” it by removing the malicious code and then transforming the programming of it into a safer one.