Artificial Intelligence (AI) and Machine Learning (ML) prevents Cyber Attacks

As computing power, data gathering, and storage capacities have increased, Machine Learning (ML) and Artificial Intelligence (AI) are widely used in various sectors and applications.

Along with the advancements, there is a rise in threats such as ransomware, botnets, malware, and phishing. Though, AI and ML also help identify new exploits and weaknesses, reducing the workload of security professionals. Therefore, alerts them whenever an action is needed.

Here are some ways that AI and ML can protect various industries from cybersecurity threats:

Password Protection and Authentication - Sometimes, traditional face detection and other biometric security measures can be vulnerable. To prevent such attacks, AI helps to enhance validations and face recognition. AI offers the most up-to-date algorithms for facial recognition by monitoring significant connections and patterns.

Phishing Detection and Prevention - The majority of users cannot figure out which received emails have a malicious attachment or payload. In this situation, AI and ML are significantly faster than a person at identifying phishing emails. They can instantly distinguish between dangerous and trustworthy websites.

Threat Detection - Through logical data analysis, machine learning constantly keeps administrators informed of security threats. Deep learning is used to analyse the data received by ML and take steps to ensure the safety of the information systems.

Vulnerability Management - Systems built on AI and ML can predict how and when a vulnerability may be exploited. They never let a vulnerability last for long; instead, they constantly check for new ones and notify the administrators. Additionally, they assist in identifying the attacker's pattern.

Behavioral Analytics - Based on regular usage, specific user patterns are generated using AI and ML. It immediately notifies the admin, if AI software notices any suspicious activity or deviation from normal usage.

Network Security - AI and ML can carry out the network traffic analysis and propose efficient security policies by default, saving time as both of these factors are time-consuming.

AI-based Antivirus uses anomaly detection to understand programs' behaviour. They detect suspicious program behaviour instead of matching signatures for viruses. Read more here.

Fraud Detection - They can easily differentiate between authentic and illegitimate transactions and blocks fraudulent transactions. They carry out anomaly detection to identify payment inconsistencies and fraudulent transactions.

Botnet Detection - AI and ML algorithms alert suspicious behaviour of a network and detect unauthorized intrusions, as they can easily bypass IDS by leveraging its ineffectiveness in matching signatures.

AI to Combat AI Threats - AI technology can be used by attackers to access a network of a company; such cyber risks must be quickly identified. Such potential AI-augmented attacks can be detected by AI software before the network is hacked.

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