The teams at ITrust's SOC (Security Operations Center) rely on our Reveelium tool, which integrates powerful internally developed algorithms and artificial intelligence to analyze massive volumes of data in real time and identify ongoing or emerging threats. These algorithms enable incident detection as well as automated responses to accelerate response times.
AI and Cybersecurity
Amid the widespread adoption of Artificial Intelligence, malicious actors are increasingly leveraging AI in their attacks. AI facilitates the execution of complex tasks, significantly enhancing the sophistication and scale of their operations.
On their side, defenders are also adopting AI-driven tools. These enable security teams to detect and respond to advanced threats more rapidly and accurately, while automating traditionally manual, routine tasks.
How does AI work in cybersecurity?
Cybersecurity AI operates through AI algorithms, machine learning, and neural networks capable of analyzing massive amounts of data to detect patterns and anomalies indicative of cyberattacks.
Here is a simplified workflow to understand the use of AI in cybersecurity:
AI in cybersecurity
- Data Collection: AI algorithms use diverse sources to gather relevant data. Key data collection sources include user behavior, system logs, and network traffic.
- Data Processing: The collected data is then filtered and processed to remove irrelevant information. Data processing involves noise reduction within the data.
- AI Model Training: AI algorithms are subsequently trained to recognize normal behavior, and then search for anomalies and abnormal activities that deviate from this baseline.
- Threat Detection: The trained AI model, algorithms, and neural networks monitor vast amounts of data in real time to identify threat patterns, thereby contributing to threat detection and prevention.
- Anomaly Response: After identifying a system threat, the automated AI algorithm alerts human analysts to the potential attack for verification and remediation.
Reveelium, an AI-powered SIEM/UEBA/XDR/SOAR engineered by ITrust!
Used internally and by our clients, the new Reveelium V12 release delivers numerous advantages.
- Advanced Threat Detection: Integrating AI into Reveelium enables the real-time analysis of massive amounts of data, detecting patterns and anomalies that may indicate a cyberattack.
- Behavioral Analysis: Reveelium's AI enhances behavioral analytics by monitoring and evaluating user activities. It identifies deviations from established baselines, uncovering potential security vulnerabilities or insider threats.
- Efficiency: Deploying Reveelium and Machine Learning frees analysts from time-consuming manual tasks required for threat detection and identification.
- Scalability: Driven by AI and Machine Learning, Reveelium seamlessly scales to meet exponential data growth.
