UK’s National Cyber Security Centre (NCSC) has taken down more than 2,000 online coronavirus scams last month. The NCSC has created a new national reporting service where members of the public can alert the authorities to potentially suspicious emails. If the content contains suspicious links or addresses, then the NCSC says it will be taken down. The data will also be analyzed to try to identify patterns that will allow for a quick takedown of new scam websites.
The @NCSC and UK authorities launched an initiative for reporting #phishing emails and have already removed more than 2000 online #coronavirus scams. via @ZDNet https://t.co/UcHiD52b9j #cybersecurity
— SonicWall (@SonicWall) April 21, 2020
We are definitely seeing a huge rise with phishing attacks in a COVID-19 theme being the primary aggressor,\” he said. \”I wouldn\’t necessarily say the total number of cyberattacks has gone up. I do think the method by which they\’re carrying out these attacks is that they\’re leveraging this opportunity.
Because these highly lucrative attacks are succeeding, they will continue to attract more groups willing to attempt their methods. It’s time that businesses consider applying security to their business practices because IT security tools are not infallible against human behaviour.
Attackers using newsworthy events to lure users into clicking malicious links is nothing new, however, in this current climate stress and distractions are putting users at an increased risk of accidentally dropping their guard. Using statistical modelling to identify patterns and protect people from this risk clearly demonstrates the benefit of machine learning in promptly detecting and blocking attacker behaviours.
This is an approach many organisations can learn from. Using machine learning and analytics to draw insight from vast amounts of data is the most effective way of identifying security risks. These tools set baselines of normal behaviour that help to identify threats much easier and faster – detecting and escalating unusual patterns, pinpointing event timelines and providing deeper insight on sources.