With the introduction of unique device policies in the workplace and the proliferation of various smart devices available to end-users, not to mention the growth of IoT, there are more endpoints than ever and endpoint security is under threat. They never told me.
In various studies, 70-95% of security breaches occurred at endpoints.
This is not an internal threat, but it is a big problem, but it could also suggest that the phishing attack is still successful. In fact, the 2017 Verizon Data Breach Investigations Report shows that phishing scams continue to thrive, despite many warnings about the dangers of opening unknown emails and efforts to raise awareness through employee training. He said.
According to DBIR, 95% of the phishing attacks that resulted in breaches were followed by software installations and malware deposits on the system. Antivirus and antimalware software are still essential, but even the best software can only tackle known threats. Human intervention is required to ensure coverage of new threats.
Regular software updates are not enough to address the multiple threats facing businesses today. Cyber attacks are evolving rapidly, and businesses need to catch up to protect their end-users and valuable data.
Even a team of human security analysts can't wait to examine all the data provided by corporate anti-virus and anti-malware software, and most companies have only a few people dedicated to cybersecurity. not.
There are also a lot of trust issues around AV, and the recent controversy over software created by Russia-based Kaspersky Labs is a striking example. Kaspersky's software, despite being one of the world's largest antivirus providers, claimed last year after the Department of Homeland Security claims it could allow Russian espionage and threaten national security. It was banned for use by US government agencies.
There is no one solution that fully protects all endpoints from all cyber threats, but there is a way to use artificial intelligence (AI) and machine learning algorithms. You can use machine learning, which enables your system to learn from your data without specific programming, to collect and analyze your data to identify threats that may target cyberattacks at the enterprise level.
These threats can be stopped at the endpoint before they cause harm.
AI is many times faster than human security analysts want, and it literally counts millions of possibilities every second.
The best example of recent times was when machine learning technology was able to detect and protect many systems from last year's WannaCry ransomware outbreak, avoiding almost all traditional AV software and other systems.
The WannaCry attack attacks more than 200,000 computers in 150 countries, including the UK's NHS computer system, demonstrating the need for improved endpoint security.
Today, the key to machine learning success lies in the cloud. While traditional servers are not large or fast enough to process data and build the models necessary to detect and combat attacks, with cloud servers, the process is faster than ever Easy, much more affordable and accessible for more and more companies.
Hackers are already using automation, machine learning, and artificial intelligence systems to create new cyber threats. Security experts believe that the adoption of machine learning by hackers is accelerating in the next 12 months as hackers seek to carry out increasingly sophisticated phishing attacks.
However, AI antivirus solutions are still relatively rare in practice. Some companies offer machine learning and artificial intelligence cyber threats for endpoints like Cylance, Darktrace, and Symantec, which really should be the industry standard.
Microsoft, at least, seems to have learned from the WannaCry experience, apparently using AI to create the next generation of antivirus software. Latest security update incorporates machine learning of millions.