Even if you’re not a technology expert, you’re well-aware of the criminal presence that’s online and elsewhere. Over the years, we’ve seen plenty of new scams, thefts and threats unfold. Hackers never sleep.
While established scams like phishing emails, sent by criminals “fishing” for your personal information, are nothing new, the rise of artificial intelligence (AI) has provided scammers with tools like deepfake video and audio voice cloning.
Thankfully, the methods and tools that comprise cybersecurity are largely preventable. By incorporating AI's ability to process vast amounts of data, security experts and IT developers are creating new methods to battle the bad guys.
This article will define some of the ways that AI is helping improve levels of cybersecurity.
We’ll begin with one security feature that you may already be using every day.
Enhanced Authentication
Whenever you log into a phone app with your fingerprint, you’re using a popular AI-powered biometric authentication method. Facial recognition is another method.
AI algorithms continue to improve biometric accuracy. In addition, AI can analyze behavioral biometrics, such as typing patterns or mouse movements, to verify a user's identity or identify an imposter.
These reduce the risk of unauthorized access and eventual loss while providing a convenient, secure alternative to traditional passwords. (When was the last time you forgot your fingerprint?)
Another first AI-powered system helps keep common hackers’ threats at bay.
Advanced Threat Detection
You may remember the massive data breach from 2013 that affected millions of Target customers. This resulted in Target Corporation’s investing heavily in AI-powered data protection.
AI-powered algorithms improve security systems’ threat detection “skills”. They accomplish this by analyzing network traffic, user behavior, and system logs in realtime, identifying anomalies that warn of a possible cyber attack.
For individuals, AI can be integrated into personal security software, providing more robust protection against malware, phishing attempts, and other common threats.
However, not every detection system is perfect since hackers are always looking for ways to defeat them. AI has the potential to improve their performance.
Automated Incident Responses
When a security breach occurs, it needs to be addressed immediately. AI incident systems can launch an initial response procedure before IT is notified of the breach.
Apps such as incident.io are able to identify, classify and automate incident processes, containing threats before human intervention arrives. Users can focus on fixing individual issues and learn from incident insights to improve site safety.
Rapid response is particularly valuable for businesses, where a quick reaction can mean the difference between a minor incident and a major data breach.
For individuals, AI-powered security tools can automatically block suspicious connections or quarantine potentially malicious files, providing an extra layer of protection.
One area where AI excels is controlling and managing current cyber breaches. Another AI “talent” is looking for future break-ins.
AI Detectors Are Essential in Cybersecurity
AI detectors like Undetectable AI and ZeroGPT are essential to improving cybersecurity by detecting and mitigating threats posed by malicious AI tools.
These detectors are designed to identify anomalous patterns or suspicious activities that might indicate a possible cyber attack and then report back. AI detectors use advanced algorithms to examine video and audio content for signs of manipulation, including inconsistencies between visual or auditory elements and their appearance on-screen.
In the case of deepfakes, these detectors also detect possible manipulation by looking for signs that the source might have altered the file before publishing it online.
AI detectors can also monitor network traffic and user behavior to detect emerging threats and ensure security measures are updated in real-time. This proactive approach protects systems against emerging cyber threats while providing additional safeguards that supplement human oversight and standard security protocols.
Predictive Security
One of AI's most promising applications is its ability to predict future threats. By analyzing historical data and current user activity, AI systems can forecast potential hacks by noting subtle changes in activity.
This enables security teams to patch weaknesses before they’re exploited.
This predictive capability improves long-term security strategies and resource allocation for businesses. For individuals, it can mean more timely security updates and personalized risk assessments based on their personal surfing behavior.
The next topic looks at an increasingly common problem—deepfakes—and how AI tools help detect them.
Identifying Altered Video and Audio
A popular new scam category, deepfakes, is created with a variety of AI apps.
Deepfake creators alter video in a variety of ways, from replacing the audio to converting an unknown person to a celebrity. AI apps that transfer faces from one “host” body to another make this possible.
Deepfake videos are often created with political strategies in mind. For example, recent political campaigns in India were awash with deepfake videos.
Another type of deepfake replaces the audio portion, using voice cloning applications. This short YouTube video is an example of a real and fake Anderson Cooper.
An increasing number of AI tools help users detect deepfakes. Two methods are:
- Source analysis. This identifies the original source of a video by analyzing file metadata.
- Background video consistency. AI can identify altered backgrounds by performing highly granular checks at multiple points to identify changes.
No matter how we use AI to improve cybersecurity, the human element is as vital as ever. Here’s why.
Human-AI Collaboration
While AI continues to transform cybersecurity, the human element remains crucial. This is because AI systems are designed to augment human expertise rather than replace it.
These collaborative systems can handle routine tasks and initial threat assessments, allowing human analysts to focus on complex decision-making and strategy development.