The cybersecurity market has, simply put, been cobbled together. A tangled web of non-integrated systems and alerts from siloed systems. Enterprises are now being forced to utilize a “Frankenstein” of stitched together tools to create a platform that might cover their security bases.
The evidence indicates that these attackers are traditionally specialized in hijacking social media accounts via SIM Swapping.
Most cybersecurity vendors today tout some form of “Artificial Intelligence” as an underlying mechanism for the differentiation of their product among the market. But if everyone is saying they have AI, and everyone is also claiming theirs is the “best,” how can they all be telling the truth?
Many CISOs and SecOps teams were faced with a gut-wrenching choice: addressing the operational challenges of keeping workers connected, or shoring up vulnerabilities before hackers exploited them. Both options involved time-consuming, repetitive, manual work.
A recent WhiteHat Security survey revealed that more than 70 percent of respondents cited AI-based tools as contributing to more efficiency. More than 55 percent of mundane tasks have been replaced by AI, freeing up analysts for other departmental tasks.
Since we determine everything on data here at MixMode, we went into our website data to see which of our Q2 articles got the most traffic over the past few months. Not surprisingly, the majority of our top articles covered topics on the advancement of AI in cybersecurity and network traffic analysis (NTA).
Real unsupervised AI spots security issues sooner and predicts future behavior more accurately than older first- and second-wave solutions. Self-supervised AI technology draws on an understanding of the fundamental nature of the network where it lives, an understanding that isn’t possible with supervised-AI.
Yann LeCun and Yoshua Bengio were recently interviewed by VentureBeat Magazine on the topics of self-supervised learning and human-level intelligence for AI. Our CTO Dr. Igor Mezic sat down with our team to discuss some of the most interesting pieces of the LeCun article, and offer a potential solution to a search for truly self-supervised …
MixMode CTO Responds to Self-Supervised AI Hopes Read More →
Artificial Intelligence – or AI – has become a buzzword since it emerged in the 1950s. However, all AI systems are not created equal. In our white paper, “Self-Supervised Learning – AI For Complex Network Security,” Dr. Peter Stephenson explains the different “waves” of artificial intelligence. He uses the DARPA definitions for each of these …
Whitepaper: Self-Supervised Learning – AI For Complex Network Security Read More →
The relationship between modern cybersecurity solutions and AI has become inextricable. The unfortunate reality is that even the most talented and responsive SecOps teams are unable to manually catch every threat posed to the sprawling, hybrid networks on which today’s organizations rely. Forward-looking organizations know they need to bring AI and machine learning based security …
Self-Supervised Learning – The Third-Wave in Cybersecurity AI Read More →
MixMode leaders John Keister, Dr. Igor Mezic, Bryan Elliot, and Russell Gray share how the single algorithm that is the foundation of MixMode’s self-learning AI can understand and continually build a generative baseline of your network without human training.
Our newest whitepaper, “How Predictive AI is Disrupting the Cybersecurity Industry,” evaluates several common SecOps issues around Network Traffic Analysis, explaining why typical solutions are wholly ineffective and represent sunk costs versus added value. We examine how self-supervised learning AI is poised to overcome the SecOps challenges of protecting today’s distributed networks.
Imagine serving as a CISO for a prominent enterprise and being thrown into a situation where overnight 80 to 100 percent of your workforce moves inside and begins working remotely. The logistics challenges alone are almost too daunting to imagine.
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:
We interviewed MixMode CTO Dr. Igor Mezic to better understand how machines should be protecting themselves with AI, what roles humans play, and how the DoD and the private sector both benefit from rapid innovation in cybersecurity.
Throughout the tech community, “artificial intelligence” has become a blanket term often used to describe any computing process that requires little human input. Tasks like routine database functions, scheduled system scans, and software that adds automation to repetitive actions are regularly referred to as AI. In truth, AI can play a part in these processes, …
Not All Artificial intelligence is created Equal Read More →
For the past few years, a major problem has been mounting in the cybersecurity industry: a people shortage. Even before the outbreak of the current global pandemic, enterprises were hurting in the cybersecurity hiring department. Companies are struggling to find employable cybersecurity professionals to handle an ever increasing and evolving number of new threats from …
In today’s ever evolving cybersecurity landscape there are major problems facing professionals that continue to worsen. These problems center around a shortage of tools advanced enough to understand the baseline of a network in order to pinpoint anomalies and a massive information overload problem in the form of security alerts.
Phishing scams feeding off of Coronavirus fears have taken advantage of the current state of national emergency to trick concerned citizens into opening malicious PDF’s claiming to help protect them from the disease.
Data breaches are expensive. By now, most organizations are well aware of this fact. When it comes to resource planning, however, SecOps teams need concrete data to ensure adequate funding is available to handle a breach.
