Securing Sensitive Data through AI and ML-Driven Cloud Models
Artificial Intelligence and Machine learning can is now into securing sensitive data driven by cloud models. As it has becoming challenging task for defending your systems against cybercriminals and these systems are being used for some sort of criminal activity.
“Threat Landscape” has changed from a perception that locking my doors is good enough protection to I need the secret service with the most modern weapons and technology.
Botnet is a network of compromised devices that are controlled by an attacker without the knowledge of their owners. Botnets are not new. As a matter of fact, a research study “Why Botnets persist” from Internet Policy Research Initiative by MIT.
There have been numerous scenarios where the attacker enters a system and can stay there for months if not years just observing and studying your environment before going for an all-out attack. This whole life cycle of an attack is now commonly known as a cyber-kill chain.
When you adopt an assume-breach mentality, then you gather the people, processes, and technology that will help you find out when a breach occurs as early as possible, discover which breach has occurred, and eject the attacker while limiting the effects of the breach as much as possible.
This is where AI and ML-driven systems come into play. You have if not billions, millions of systems and you have four patterns:
- Normal system functioning parameters
- Change in Normal before a system is attacked.
- Change in Normal after a system is attacked
- Change back to Normal after the threat is identified and removed.
AI and ML will one day not only detect the attacks and the attackers, but maybe even attack them back too.