Supervised Machine Learning and Unsupervised Machine Learning both are important technologies used in preventing data breaches.
Five most important cybersecurity trends for 2019
After the introduction of the GDPR on may 25th, 2018 we have seen a lot of changes in the way consumers and organizations perceive sensitive data, and the way it's being handled. In order to comply with the new regulations and the increasing demands of consumers, we have seen a big change in data security across all industries. Dimension Data recently released a report on the Tech Trends for 2019. In the report, we see the 5 most important trends in cybersecurity for the coming 12 months of 2019 when it comes to data security. In this blog we will go over the five trends from this report, so that you can be better prepared for whats to come in 2019.
From Zero Trust to Digital Trust
To reduce the amount of lateral movement by cybercriminals who have infiltrated an organizations network, we saw the adaptation of the Zero Trust model a lot more in 2018. This model emphasizes that nobody can be trusted. Therefore, “never trust, always verify” which means that you are never too privileged to not verify yourself in order get access somewhere. In 2019 we can expect digital trust to be the new emerging model. The focus with digital trust is to improve user experience by lowering the amount of verification, provided they are consistent with their own user profile.
More cloud-based security platforms
In 2019 we can expect to see cloud-based security gain more popularity for the same reasons that cloud-based services are getting more popular, namely that they are flexible and scalable. The biggest issue with cloud-based security is that it presents some security challenges, but with the increasing sophistication of the cloud-based security software we can expect many of these issues to be solved.
Secure by Design becoming the new standard
Rather than being implemented at the end of development for a project, we will likely see cybersecurity being included from the conceptualization of technologies and applications. This means that we will hopefully see a lot more integrity and sturdiness in different organizations data security, as security by design becomes more common.
The introduction of machine learning has and will continue to radically change our different technologies. This of course also included cybersecurity, both in terms of attacks and protection. In gathering intelligence for the purpose of defending against cyber attacks, and reducing cyber risks, machine learning will play a key role. And these processes will likely become very automated through the use of machine learning and AI. The issue is that these technologies will also be adopted about cybercriminals more and more, which means that our security measures need to be increasingly sharper.
Stricter regulations affect organizations risk profiles
The pressure on organizations to comply with data security regulations has certainly increased the last year since the introduction of the GDPR, and the various interpretations by different countries. A big part of complying with these regulations is assessing the security risks an organization may have. Therefore any new technology or application an organization chooses to deploy, it is now a lot more important to consider how it may affect their risk profile. For smaller organizations, a lot of these new regulations, and different assessments can put a real strain on the different day-to-day operations. However, after the introduction of the GDPR, security is no longer optional but required.
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