Despite these attempts to counter identity theft, however, the threat remains large and growing. Cybercrimeas-a-service (CaaS) allows criminals to purchase or rent tools and services that enable them to carry out identity-based attacks without having to develop the expertise themselves, meaning more criminals are capable of such attacks. This makes it even more important for businesses to be informed around identity security and how they can secure their organizations, employees and customers. Employees, in particular, must be monitored with the right policies and tools, as insider incidents are also growing, and over-privileged access and passive data security tools that only monitor traffic leave critical data vulnerable to exfiltration. All of these factors are fueling demand. According to Global Insights, the global identity and access management (IAM) market is expected to grow at a compound annual growth rate of 12.6 percent from 2023 to 2030, to reach $41.52 billion by the end of the forecast period. Demand for advanced biometric verification While fingerprint and facial recognition technologies have already made their mark, emerging ID trends indicate a shift towards advanced biometric verification methods. The integration of AI and machine learning (ML) is revolutionising identity verification. AI-powered systems equipped with pattern recognition capabilities can identify anomalies and detect fraudulent attempts in real time. These systems analyze patterns and behaviors to identify outliers and inconsistencies, adding an invaluable layer of security to the verification process. Machine learning algorithms act as adaptive detectives, continuously evolving to recognize and respond to new identity fraud tactics, enhancing the overall accuracy of the verification process. Additionally, liveness checks are becoming more frequent in biometric verification, adding an extra layer of security by ensuring the genuine presence of the individual undergoing verification. Liveness checks require users to perform real-time actions, such as smiling, blinking or speaking a specific phrase, thwarting attempts to use static images or pre-recorded videos. What are your organization’s biggest IT security and compliance blind spots? Identity and Access Management (IAM) 39% Data processing activities not compliant with regulatory demands 38% Purchasing outside of the normal process (shadow IT) 32% Business processes not compliant with regulatory demands 31% Unmanaged devices 31% Source: Vanta; Sapio Research, 9/23 CYBER PATROL Zero Trust Framework Investment vs. Prior Cybersecurity Investment More investment for zero trust 82% Less investment for zero trust 5% No difference 13% Source: CompTIA ‘2024 State of Cybersecurity’; U.S. technical/ business pros 34 CHANNELVISION | MARCH - APRIL 2024 Potential Uses of AI in Cybersecurity Source: CompTIA ‘2024 State of Cybersecurity’; U.S. technical and business professionals Monitoring network traffic and detecting malware Analyzing user behavior patterns Automating response to cybersecurity incidents Automating configuration of cybersecurity infrastructure Generating tests of cyber security defenses Predicting areas where future breaches may occur 53% 50% 48% 45% 45% 45%
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