A cyberattack that comes from a person who works for an organization or has access to access its networks or systems is known as an insider threat.
Insider threats can be divided into three main categories: trusted individuals whose credentials have been stolen or compromised by external attackers, enabling them to gain unauthorized access to systems; employees who unintentionally expose the organization to risk through careless actions; and employees who deliberately misuse their access to harm the organization, steal data, or cause disruption.
Anyone with access to sensitive information and vital assets, whether they are current or former employees, could be a risk.
Contractors, suppliers, and vendors are types of external partners who may have system access but lack adequate security measures, making them prime targets for cybercriminals.
By using machine learning, data analytics, and behavioral analysis to more precisely and effectively identify possible risks, artificial intelligence (AI) provides an effective way to insider threat detection.
New AI/ML techniques may be able to lessen insider threats. Behavioral analytics can be used to identify anomalies that could be the result of insider assaults by using the typical patterns of each PLC/HMI as a baseline.Employee awareness and training program implementation are also essential.
