After AI adoption, cybersecurity faces new challenges worldwide. Hackers now use artificial intelligence to create difficult attacks. Individual users and large companies both face these growing risks. Traditional security methods alone cannot handle these advanced threats.
Therefore, Microsoft plans to use AI as a defence system. The company is developing Project Perception for stronger cybersecurity.
What Is Microsoft Project Perception?
Project Perception works as an AI agentic security system. It reacts at the same speed as incoming threats.
The system does not only alert security teams. Instead, it starts analysing threats after detection. Furthermore, AI continuously monitors suspicious activity and can take required action. The system protects complete company networks, not just one device.
Three types of AI agents operate inside this system. Red Team agents search for weaknesses attackers could exploit.
After that, Blue Team agents identify risks from those weaknesses. They analyse which vulnerabilities require attention.
Finally, Green Team agents fix those identified problems. These three teams continue working together through a learning loop.
As time passes, their understanding improves through continuous learning. However, humans maintain control over final decisions.
Why Microsoft Trusts Project Perception For Security
Microsoft says the system can monitor devices, applications, data and cloud systems. It can also act according to detected information.
Moreover, combining this system with a multi-model setup allows different AI models for different tasks. This prevents one AI model from handling every responsibility. Microsoft built the system using its new cybersecurity stack.
The stack converts signals into context before sending them to models and agents. Together, these elements create a stronger security layer.
How Attackers Use AI For Cyber Crimes
Cyber attackers use AI to discover system weaknesses and execute complete attacks. AI has made vulnerability detection faster and easier.
Additionally, attackers collect target information from social media and public sources. They analyse this data to create personalised messages.
These messages often support phishing and other cyber attacks. AI has increased the speed and complexity of such activities.
Types Of AI Powered Cyber Attacks
AI-driven phishing and social engineering attacks manipulate human behaviour. Attackers collect information using techniques like voice cloning. Deepfake attacks use AI-generated fake videos that appear realistic. These videos support fraud and deception. Adversarial AI attacks disrupt AI accuracy through misinformation and manipulation. Attackers target AI performance through such methods.
Meanwhile, AI ransomware improves itself using artificial intelligence. These ransomware systems find ways to avoid security defences.
