The Biggest Advances in Cybersecurity Technology in 2019
Every year, the cyber attack vector continues to grow, bringing about new threats and concerns. The ever-evolving cybercrime landscape means security systems, technologies and processes require continuous modernization to keep up. Fortunately, cybersecurity companies are updating their technologies to help match the threat landscape, and 2019 was one of the best years on record for cybersecurity innovation. Here are some of 2019’s best cyber advances that will help companies implement stronger malware detection, endpoint security and other types of threat protection.
Although Artificial Intelligence (AI) is a broad term, its use in cybersecurity applications has seen exponential growth in the past year. More specifically, cybersecurity AI has seen advancements in Deep Learning, a subset of Machine Learning and AI. Although Machine Learning and Deep Learning are both very complex systems, the simplest distinction between the two has to do with their required inputs. Machine Learning algorithms need structured data and human input to learn. Deep Learning algorithms, on the other hand, rely on layers of artificial neural networks, which do not require manual input and are structured to learn similarly to the human brain.
In 2019, cybersecurity AI continued its expansion from Machine Learning to more advanced techniques in Deep Learning that are better suited for the large, complex data sets found in malware detection, endpoint security and breach detection software. The transition from Machine Learning to Deep Learning will prove to be essential because Deep Learning, unlike Machine Learning, can detect unknown attacks, isn’t susceptible to human error and can analyze a file of any size. This transition will help to detect attacks before they happen, as Deep Learning deciphers between helpful and harmful software’s and neutralizes threats.
Although AI has many benefits, it can also be incredibly dangerous when used in the wrong ways. In the years to come, cyber criminals could use AI techniques to infiltrate previously unsuspecting industries, such as auto and biotech, to execute attacks on unmanned vehicles and stored DNA code. To help stop these attacks, enterprises must correctly implement AI as only a part of their cybersecurity solutions instead of relying on it as a sole line of defense. Having a comprehensive approach to cybersecurity is the most important way to stop cyber attacks.
Zero Trust Privileged Access Management
In 2019, the cybersecurity landscape also saw major interest gravitate towards Zero Trust, which is the practice of not trusting anything attempting to connect to an enterprise’s systems. This transition means the days of “trust, but verify” are moving towards “always verify.” When it comes to Zero Trust privileged access management, there are many verification steps that can be employed such as multi-factor authentication, biometrics and behavioral analytics. At the very least, Zero Trust privileged access management should have authentication keys such as network credentials, external tokens and biometrics. Although former privileged access management solutions worked well protecting against yesterday’s cyber landscape, companies can no longer rely on a shared account protected by a traditional character password. As cyber threats continue to progress, enterprises must remain one step ahead.
User Behavior Analytics
Historically, user behavior has been one of the biggest blind spots in the middle of the attack vector. User Behavior Analytics (UBA), a practice of EDR that is often employed in Zero Trust efforts, has been instrumental in filling-in the missing links in the network security chain. Using big data analytics, UBA identifies abnormal user behavior and shuts out users who seem to be behaving anomalously in a network. Even if an enterprise isn’t under cyber attack, UBA is still a great EDR tool for identifying weak links in company security as a way to help educate employees on how to improve their security methods and procedures. As threats continue to increase both internally and externally, UBA will become a necessary part of everyday cybersecurity protocols.
2019 was a great year for advancements in cybersecurity technology. The progress in network protection developed in 2019 will have a major effect on the cybersecurity landscape of 2020. Although Deep Learning, Zero Trust privileged access management and UBA all have very promising futures, cyber criminals are constantly working to outmatch the latest technology. As these cyber threats continue to evolve, 2020 will require additional innovation.
Interested in learning more about the 2020 attack vector? Read this blog post on how to prepare for the newest cyberthreats.
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