AI & Cybersecurity
Traditional IT security tools like antiviruses or firewalls function based on a predetermined structure. Such tools come equipped with a list of malware types or blacklisted websites, which must be regularly updated – a system with obvious limitations.
AI combines large data sets and utilizes them based on intuitive processing algorithms. It helps automate operations by processing large amounts of data faster than humans ever could.
Today’s cybersecurity tools integrate such capabilities intended to work with big data.
Artificial intelligence is generally used in cybersecurity for behavioral analysis, threat detection, vulnerability assessment, and incident response.
AI algorithms can analyze network traffic data, learn what normal network traffic patterns look like and based on that can detect patterns and anomalies indicating suspicious attempts and attacks.
AI-powered behavior analysis is used to successfully indicate malicious activities. This makes user activity monitoring and threat detection more effective.
Also, AI-based systems can be used to automatically respond to various threats by limiting user access, terminating connections, quarantining infected devices, disabling user accounts, etc.
Proven Benefits
AI requires preparation and providing the learning models with data to be used as a reference when identifying patterns, but the benefits are obvious. Here are just some of them:
Self-improving models
AI models utilize machine learning to analyze user behavior. After an anomaly is discovered, the system triggers various response actions. Such a system refines its model over time, making it increasingly more accurate.
Secured authentication
The IT security industry is moving away from old security methods such as user/password combinations and looking for ways to make IT security smarter. AI is a valuable addition as it can be integrated with multiple authentication layers to verify a user’s identity.
Using fingerprint scanners, facial recognition, and other AI solutions will help identify fraudulent login attempts, creating a much tighter security mechanism.
Better vulnerability management
Artificial intelligence solutions analyze existing security measures to identify potential gaps, enabling organizations to focus on the most critical areas. This makes troubleshooting more efficient and provides insight into the circumstances faster than any human could.
Improved security-related processes
There are some cybersecurity tasks which are repetitive and monotonous, tasks that may slip by. Fortunately, AI-driven tools can perform all those recurring tasks automatically and only require confirmation before making any changes.
Improved efficiency
Human attention is limited, while AI can cover multiple tasks simultaneously. AI solutions are both time and cost effective.
Balanced workloads
Skilled work isn’t cheap to hire or maintain, so it is in a business’s best interest to ensure the IT security staff’s experience is used on complex tasks. While AI can take care of most manual tasks, human personnel can develop other ways to improve the organization’s cybersecurity posture.
AI-powered Cybersecurity Solutions
Today’s AI capabilities include advanced models allowing them to process large amounts of data in real-time. Here are a few technologies that integrate AI for cybersecurity.
Endpoint Security
Endpoint security uses AI to tack and analyze processes on laptops, desktops, and mobile devices allowing your IT security team to shut down threats before they cause any damage.
Intrusion Detection Systems (IDS)
AI-powered intrusion detection systems are capable of autonomously identifying threats using machine learning models. With enough data to work with and professional training, such models can be very accurate when dealing with potential threats and can help identify signs of intrusion early on.
Data Loss Prevention (DLP)
Data loss prevention tools automatically encrypt data before it is transmitted or restrict any unauthorized users from accessing sensitive information. DLP tools are now using AI and machine learning to improve their functionalities and performance.
DLP tools monitor, analyze, and successfully detect potential data exfiltration attempts preventing unauthorized or accidental data leaks.
Security Information and Event Management (SIEM)
AI-powered SIEM tools use behavior analytics and cybersecurity threat feeds to detect abnormal activities. SIEM solutions automate many time-consuming manual tasks such as suspicious activity detection allowing faster incident response.
In Summary
AI can detect in real time potential vulnerabilities within systems and networks, alert security teams, shut down network parts, etc. Unfortunately, cybersecurity threats are increasingly more complex, which is why static models are too slow in today’s cyber landscape.
