The next cybersecurity challenge lies with the advances in quantum computing that are set to revolutionize tech while simultaneously equipping threat actors with a new arsenal of cyberweapons.
When it comes to advancements in cybersecurity, rule-based systems are holding the industry back. Relying on humans to constantly input and label rules in order to detect and stay ahead of threats is a bottleneck process that is setting security teams up for failure, especially with tools like SIEM, NDR, and NTA.
Although it is not surprising at all that hackers are taking advantage of the global pandemic —phishing threat reports are always highest when there is some natural disaster happening— we have never before had such an unsafe environment to protect. Here are a few of the most popular malicious acts:
While it’s true that having a SIEM is better than forgoing network monitoring all together, a standalone SIEM solution is simply insufficient in today’s cybersecurity landscape. Hackers and other bad actors have become more sophisticated — many of today’s cybercriminals can easily outsmart a standard SIEM setup.
Advances in Artificial Intelligence (AI) have led to smarter, more robust network security platforms that are quickly replacing legacy security solutions.
Knowing the difference between Discriminative and Generative Unsupervised Learning can tell you a lot about the effectiveness of a cybersecurity solution’s artificial intelligence, for example, whether or not that security solution can perform actions like identifying and stopping a zero-day attack.
In October, 2019 a MixMode customer experienced an incident where an external entity attacked a web server located in their DMZ, compromised it, and then pivoted internally through the DMZ to attempt access of a customer database. While the attacker was successful in penetrating the customer’s network, MixMode was able to detect the event before they were successful in penetrating the customer database.
Zero-day attacks cost businesses millions of dollars in lost revenue and recovery costs and can cripple a company that is not prepared to respond decisively and effectively.
Mixmode’s platform utilizes third-wave, context-aware AI to inform the user of threats (including Zero-Day, and encrypted traffic) on their network, and reduces the rate of false positives in intel and alerts consistently by 90% or more.
Zero-day attacks are considered the number one cybersecurity threat to company networks large and small. Understand what they are, why it’s so hard to detect them, and how artificial intelligence (AI) is helping to solve this modern problem.
Attacking and Defending with Artificial Intelligence Often when discussing Machine Learning and AI in the cybersecurity space, we focus on the potential defense capabilities of AI systems. However, it’s time we start paying attention to the other side as well, as hackers begin to arm themselves with similar technologies. Industry practitioners believe that we will …
Silicon Valley Has Let Its Cybersecurity Guard Down According to an article by Brian O’Keefe for Fortune Magazine, Silicon Valley isn’t paying enough attention when it comes to threats posed by state-sponsored hackers. At least, that was the conclusion a group of cybersecurity experts came to in a discussion at the Fortune Brainstorm Tech conference in Aspen, Colo., on …
Silicon Valley Needs to Step up Their Security: This Week in AI Read More →
850 senior executives from Information Security, Cybersecurity, and IT Operations in seven industries across ten countries were recently surveyed by consulting and technology services firm, Capgemini, in their “Reinventing Cybersecurity with Artificial Intelligence” report. The goal being to understand today’s benefits, complexities, and levels of implementation of AI in cybersecurity across IT (information technology), OT (operation …
AI-Enabled Cybersecurity Is Necessary for Defense: Capgemini Report Read More →
“The biggest misconception people have about endpoints is that they have an idea of what their endpoints really are. The security industry has rightly taught defense-in-depth & blocking. However, too many companies rely solely on that concept, and aren’t prepared for what happens when something is breached. That breach, when it happens, will take place …
Originally published on 5/20/19 on scmagazine.com, this article by Dr. Peter Stephenson is the first in a four-part series to help enterprise and security professionals discover the tools needed to deploy a next-generation enterprise security stack. As it features MixMode as the true AI system needed for your deception network, we wanted to share the article here on our …
SC Magazine: Beefing Up Your Next Generation Security Tool Set Read More →
How AI is Solving the False Positives Problem in Network Security By Ana Mezic, Marketing Coordinator at MixMode The term “False Positives” is trending in the cybersecurity industry right now. Rightfully so. Managing the impossible amount of alerts IT teams get from their cybersecurity software is an issue that demands a solution as hackers and gatekeepers play tug-of-war …
How AI is Solving the False Positives Problem in Network Security Read More →
5 reasons why Context-Aware Artificial Intelligence (CAAI) is needed in Cybersecurity CAAI delivers understanding of the network baseline and reducing false positives By Dr. Igor Mezic, CTO and Chief Scientist Artificial Intelligence (AI) has surfaced as the technology of the day, in the same way internet, personal computers, airplanes and cars have in earlier eras. And, just like these others …
5 Reasons Why Context-aware Artificial Intelligence (Caai) Is Needed in Cybersecurity Read More →
