Category: Threat Detection and Response

Digital Asset Monitoring

Digital asset monitoring is the process of tracking and managing digital resources such as files, images, videos, documents, or cryptocurrencies. It involves observing the status, usage, and security of these assets to ensure they are safe, up-to-date, and accessible when needed. This helps organisations prevent data loss, unauthorised access, and ensures compliance with policies or…

Smart Alert Prioritization

Smart alert prioritisation is a method used in technology and security systems to sort and rank alerts by their level of importance or urgency. Instead of treating every alert the same, it helps teams focus on the most critical issues first. This approach uses rules, data analysis, or artificial intelligence to decide which alerts should…

Automated Incident Response

Automated incident response refers to the use of software or systems to detect and react to security threats or operational issues without requiring manual intervention. These systems can quickly identify problems, contain threats, gather evidence, and even fix issues based on pre-set rules or machine learning. This approach helps organisations respond faster to incidents, reducing…

AI-Based Vulnerability Scans

AI-based vulnerability scans use artificial intelligence to automatically check computer systems, networks or software for security weaknesses. Unlike traditional scanners, AI can learn from new threats and adapt its methods over time, making it better at spotting unusual or new types of vulnerabilities. These scans help organisations find and fix problems before hackers can exploit…

Automated Threat Monitoring

Automated threat monitoring is the use of software tools and systems to continuously watch for signs of potential security threats or attacks on computer networks and systems. These tools work by scanning data traffic, user behaviour, and system logs to spot unusual or suspicious activity. When a potential threat is detected, the system can alert…

Intelligent Fraud Detection

Intelligent fraud detection refers to the use of advanced technologies, such as artificial intelligence and machine learning, to identify and prevent fraudulent activities. These systems analyse large amounts of data to spot unusual patterns or behaviours that may indicate fraud. By learning from past incidents, intelligent fraud detection tools become better at predicting and stopping…

Intelligent Endpoint Security

Intelligent endpoint security uses advanced tools, including artificial intelligence and machine learning, to protect devices like laptops, smartphones and servers from cyber threats. These systems can detect unusual behaviour, automatically respond to attacks and adapt to new risks without constant manual updates. By constantly analysing data from each device, intelligent endpoint security helps organisations stay…

AI-Driven Anomaly Detection

AI-driven anomaly detection refers to the use of artificial intelligence systems to automatically identify unusual patterns or behaviours in data. These systems learn from large sets of normal data to spot anything that does not fit the expected pattern. This helps organisations quickly detect issues or risks, such as fraud or equipment failures, without needing…

AI for Anti-Poaching

AI for anti-poaching refers to the use of artificial intelligence technologies to help detect, prevent, and respond to illegal hunting and wildlife trafficking. These systems can analyse data from cameras, drones, sensors, and other sources to spot suspicious activity or patterns that suggest poaching. By using AI, conservation teams can react more quickly and efficiently…