The Impact of AI in Cybersecurity

Introduction

Cybersecurity is an increasingly important focus in the digital age.

As technology evolves, so do cyber attacks.

AI plays a key function in the security of your data, networks, and systems.

AI improves security by identifying and analyzing threats, deciding how to prevent them, and responding in real-time.

This article will help you understand how AI is changing the field of cybersecurity.

What Is AI in Cybersecurity?

AI in cybersecurity refers to machine learning / intelligent systems that can identify, classify, and respond to digital threats.

AI can help security teams manage massive amounts of information.

AI can identify patterns in data to detect suspicious, abnormal, or malicious user behaviors.

AI can act faster than humans and learn and improve over time.

Why AI is Necessary in Cybersecurity

Cyberattacks are becoming more complex, and the volume of attacks is increasing rapidly.

Hackers use advanced sets of tools and techniques to breach systems.

Traditional password-protection methods are poorly equipped to catch new types of attacks.

AI can add an intelligent layer to cybersecurity.

It can learn from data and detect attacks at rates and with patterns that might escape the attention of the naked human eye.

Detection in Real-Time

One primary advantage of AI is real-time detection. It can constantly monitor and observe everything that happens on a network or system. If it recognizes unusual behavior (suspicious activity), it can immediately send alerts (e.g., email, mobile, or push notifications), ensuring that security teams can intervene quickly enough to stop an attack, minimizing damage. The speed in response (real-time detection and alerts) can provide organizations with some downtime as well as minimizing damage to sensitive data.

Automated Response Systems

AI can be programmed both to detect, and to respond to, threats. Where you have automated security response systems, when an AI detects a threat, it can react autonomously (with no human oversight) to remediate a threat (e.g., isolating files, blocking IP addresses, turning off access). The AI's ability to respond autonomously speeds the reaction time and stops propagation, while freeing a security team to address bigger issues.

How AI and ML are Similar

Machine Learning is a type of AI that allows AI to learn from past experiences with data. Each time a cyber incident occurs, machine learning algorithms get smarter, because they learn to recognize attack patterns and shore up the characteristics that aid in malware attacks, phishing attempts, etc. A primary goal is for machine learning to have an ongoing advantage that at least addresses if not mitigates a significant portion of external attack factors/conditions that might jeopardize the integrity of your IT setup.

Behavior Analysis

AI has the ability to monitor behavior of users and devices. If a user accesses an account from an unusual location, or executes actions deemed jumpy or aggressive, AI recognizes and alerts on this behavior. From here, security might get involved and flag the behavior, or block access, etc. Monitoring user or device behavior is an efficient way to detect insider threats and compromised accounts.

Fraud Detection

AI is used across many industries to combat online fraud.

Banks and e-commerce sites utilize AI to detect abnormal transactions.

AI reviews the user's history of activity and payment transaction patterns.

If a transaction appears suspicious, AI will halt or require verification for a transaction.

This serves to protect customers and maintain stakeholder trust.

Email and Phishing Protection

Phishing emails are considered one of the most significant cyber threats.

AI examines millions of emails for identifying fraudulent or harmful content.

It will scan for suspicious links, spammy behavior, or scams known for certain behaviors.

Users can either be warned or blocked from the harmful email.

This reduces the chance of users falling for phishing attacks.

Predictive Threat Intelligence

AI is capable of predicting threats, based on past trends it has analyzed.

AI collects data from global inputs, such as attack logs and cybersecurity feeds.

This predictive intelligence, allows companies to be proactive.

Companies can remediate weaknesses before hackers exploit them.

AI in Endpoint Security

End-Points (laptops, tablets, or smartphones) are among the most common attack surfaces.

AI security tools will constantly monitor end-points

They monitor the software activity, app activity, and external devices activity.

If a risky action is taken, AI will intervene.

Cybersecurity Success of AI AI has several benefits in cybersecurity.

Speed: AI can detect and respond to threats more quickly than humans.

Scalability: AI can deal with big data and examine it at any quantity of time without getting tired.   

Accuracy: AI's detection process creates a lower rate of false positive incidents.  

Constant Monitoring: AI’s benefit is in 24/7 (always on) for contextual anomalies and threat detection.  

Cost Efficiency: No need to have several humans in a situation and pay them. AI can automate the detection processes and alerts.

Cybersecurity Issues of AI 

While there are wonderful benefits of AI, it does have some problems.  

Data Dependency: AI requires large amounts of quality data to train. 

False Alarms: While low in number, there are instances where an AI will classify safe activity as a threat. 

Skills Gap: Organizations need a trained person or people to interpret AI tools.  

AI Versus AI: Lastly, hackers are using AI technology to thwart or trick cybersecurity protections. 

Combining AI and Human Intelligence 

While AI technology has advanced seriously, it is still not perfect. The human experts in your organization offer critical thinking analysis and judgment. You allow AI to perform the routine action while you reward the computer software with you using your human high order thinking skills to derive an optimal outcome. It brings all together when AI and humans work together. 

Case Studies of AI Working 

IBM Watson for Cyber Security: AI uses Watson as an advanced interface to analyze thousands of data points in threat data while supporting human security professionals and teams. 

Darktrace: Darktrace is an artificial intelligence based cybersecurity company that uses AI to identify threats in real-time. 

Google Gmail: Google’s Gmail uses AI to filter out 99.9% of spam and phishing scams. 

The examples presented above showcase how AI technology allows for enhanced protection in a real-time environment along with human intelligence and training.

The Future of AI in Cybersecurity

AI will continue to play an even larger role in the future. 

Also, new technology such as quantum computers will introduce advanced threats to organizations. 

AI will adapt to this situation. 

AI-powered security will become the norm, as the development of industry standards around AI will offer security that will transform industry standards everywhere. 

The idea of an AI system is a continuous learning and innovation capability.

All of which means improved safety.

Conclusion

The stars that Artificial Intelligence creates is a tool in the battle of cybercrime.

It can detect threats, responses to the threat can be automated, and thank goodness it can learn continually.

While there will be limitations to Artificial Intelligence that we acknowledge when discussing it, the positive impact of AI is irrefutable.

With the right combination of Artificial Intelligence and human capability, it is fairly easy to build stronger and smarter systems of cybersecurity.

The future of cyber security is powered by Artificial Intelligence.