Impact of AI on Cyber Security

Cyberattacks are growing in volume as well as complexity. Firewalls and access controls can be bypassed in much intelligent ways by attackers to enter highly secured networks. The level of complexity surpasses the human capability to handle the attacks themselves. AI offers solutions to tackle such security risks at present and for future. Security analysts use AI to identify and counteract complex criminal activity and intentions without human intervention. Cyberattack vectors are better explored using AI and machine learning. They provide improved responses to incidents related to security by learning and updating algorithms on the basis of data received. They can predict threats and observe any inconsistency or discrepancy with high accuracy beyond the capacity of humans. 

Certain advantages of AI in cybersecurity are discussed here. AI detects malicious activities from the beginning and prevent full-fledged attack on network or business. It removes zero-day vulnerabilities, identifies patching accurately where required, analyzes mobile endpoints for threats, performs security tasks in routine and improves human analysis from depicting attacks to endpoint safety.

Artificial Intelligence can be used in Cybersecurity among many applications. Organizations can use AI-ML to manage several factors which may adversely affect their security. Some of them are mentioned below.

• Vulnerability Management- The systems that are empowered by AI- machine learning, detect potential vulnerabilities of IT system of the entire organization through proactive approach. They apply several factors for identifying such vulnerabilities like patterns, reputation of attackers and discussions on attacker’s network. These factors are analyzed by the AI-ML machines to determine high risk sections of the organization’s network. 

• User Authentication- Passwords are the main barrier between attackers and business accounts. They require robust security measures to avoid security breach. However, employees tend to underestimate the importance of their passwords for the organization as a whole. AI technology is being developed by engineers to boost the traditional biometric authentication to make the password security mechanism foolproof. One of the successful applications is face recognition by a high end brand which claims there is a minuscule chance that a device empowered with this technology can be opened by another face.

• Behavioral Analytics- The ability of behavioral analytics in AI can be used observe user’s behavior on using networks and platforms and to create a pattern based on it. This pattern is considered as a standard pattern for that user. AI algorithms are capable of observing inconsistencies in real time pattern as compared to standard pattern thus detecting suspicious activity like substantial change in typing speed, too much downloading or too much online purchase, etc. Such detections will lead the machine to mark the user as suspicious or block her from the network.

• Phishing Control: AI-ML can detect and prevent phishing attack to a great extent. It can track thousands of phishing sources in order to make the system capable of defending itself from those attacks faster. AI machine can scan phishing threats and attacks from all over the world. The system can easily differentiate between a legitimate and fraud website using AI.