intelligent

By examining statistics and identifying known patterns , ML is well equipped to detect anomalies that could indicate malicious behaviour . It allows SMEs to automate detection processes so that any unusual emails entering the inbox are flagged and investigated . Rather than simply relying on the limited number of employees to investigate every email , SMEs are strengthening their defences with ML .

The technology learns what is deemed ‘ normal ’ user behaviour and compares this to all resources entering the network . Even those more convincing attempts , like BEC , have minute indicators of deceit and will be detected by ML . On top of this , the accumulation of data over time will help the ML system predict who could realistically become the next target . It will examine who has already been hit and provide reports of potential future approaches and victims .

Why should SMEs pay close attention to threat intelligence ?

As valuable as Machine Learning is , there is a missing piece that is vital to a strong cyberdefence strategy . SMEs must not

Machine Learning can work at a pace unattainable for human workers and can therefore free up employees to focus on higher-value tasks . While it ’ s important for individuals to have a good knowledge base of phishing attempts and how to spot them , the responsibility of defending the company against attacks should not rest solely on their shoulders . ML can offer SMEs real-time detection and automated remediation to their email cybersecurity , which human workers cannot . Additionally , the broad coverage of protection offered by ML solutions means SMEs can save costs with one service that does multiple jobs . This is ideal considering the limited budgets available . Both machines and employees have their own specific skills , so it ’ s important that SMEs allow each side to work to the best of their ability .

The most effective form of Machine Learning protection is one that slots in with existing security stacks to form one unified form of defence . As the ML email security system is continuously scanning emails and subsequent attachments and URLs , other detection techniques that spot threats that ML cannot should also be deployed . Deploying systems

Mike Fleck , VP Marketing at Cyren

underestimate the value of human intelligence . ML is essential for identifying suspicious and malicious behaviour patterns , but it cannot give a reason why . However , when combined with in-depth threat analysis , SMEs can get a better understanding of the phishing attempts , including who the primary targets are and how best to respond to the threat in the future . that work in unison with each other is essential for SMEs looking to future-proof their network and stay ahead of the advancing cyberthreats . Phishing will continue as a popular choice for adversaries simply because of its success rate , so SMEs should remain committed to identifying potential attempts before they gain access to the network . �

THE ACCUMULATION OF DATA OVER TIME WILL HELP THE ML SYSTEM PREDICT WHO COULD REALISTICALLY BECOME THE NEXT TARGET .