The Difference Between Artificial Intelligence and Machine Learning in Network Security

Be in the Know About AI for Network Security

Artificial Intelligence (AI) and Machine Learning (ML) are often used interchangeably when discussing developments in deep learning. However, there is an important difference between the two that network security professionals will need to understand in order to serve their clientele effectively. 

Unfortunately, some tech organizations are deceiving their customers by claiming their product utilizes AI or ML, without it actually doing so. Recently a report by the Verge showed that 40% of European startups classified as using Artificial Intelligence don’t actually use the technology

Additionally, AI is constantly developing, and it is no longer sufficient to claim that a system “uses AI” as proof that it is up-to-date with the most effective technologies. First- and second-wave AI made valuable strides in this ever-changing field, but this technology is also in use by cyber attackers. That’s why it’s important to know how to recognise third-wave AI and know how it differs from Machine Learning and other less powerful technologies. 

So What’s the Difference? Machine Learning vs. Third-Wave Artificial Intelligence

You may hear the terms “Machine Learning” and “Artificial Intelligence” used interchangeably, but the truth is Machine Learning is a subset of AI, focusing on computer algorithms that allow computer programs to automatically improve through experience and become artificially intelligent. 

To do so, Machine Learning relies on small-to-large data sets, by examining and comparing the data to find common patterns and explore nuances. 

For example, if an ML system studied the music you listened to and was provided its genre, tempo, mood, etc.,it would be able to recommend other music categorized similarly for you.

Then there’s cutting edge AI which goes above and beyond, referred to as Context-Aware or Third-Wave AI, which is capable of studying the patterns of songs and melodies and coming up with a brand new and unique melody of its own, just like a human musician could. 

More on Third-Wave AI

The Defense Advanced Research Projects Agency (DARPA) explains the progress of Third-Wave AI in this way: 

·   Engineers create systems that construct explanatory models for classes of real-world phenomena

·   AI systems learn and reason as they encounter new tasks and situations

·   Natural communication among machines and people

Third-Wave AI enables systems to process interactions with a more intuitive and contextual understanding. Thus it is a stronger form of AI than Machine Learning, in that it involves Natural Language Processing and understands the context of various forms of communication. This is increasingly necessary for cybersecurity purposes, as cyber attackers begin to use more advanced AI.  

“AI changes the scale at which cyberattacks can occur … AI can also be used to exploit human vulnerabilities, for example by using a chat bot to uncover personal information or to sway behavior.” – Center for Long-Term Cybersecurity, 2019

Benefits of Third-Wave AI in Cybersecurity

·    AI lowers the cost of detecting and responding to breaches by 12%, on average.

·   This is in part related to the decrease in false positives (MixMode has found a 90% reduction in false positives through its development of Third-Wave AI)

·   Cyber attackers are using first- and second-wave AI, so security systems need to employ third-wave technology to predict their behaviors 

·   In a study of 850 IT professionals across 10 countries, Capgemini found that 28% are using security products with AI embedded, with 30% using proprietary AI algorithms. The remainder, 42%, currently either use (or plan to use by next year) both proprietary solutions and embedded products.

·   As usage across the board increases, so will customers’ expectations increase. In other words, some level of AI is becoming the industry standard for cybersecurity. In order to stand out as having top-notch cybersecurity, companies will need to employ the most advanced third-wave AI available.

Recent Developments in Cybersecurity AI

Third-Wave AI was developed for applications in cybersecurity by MixMode’s CTO, Dr. Igor Mezic. It is currently the fastest available breach detection technology on the market. 

Armorblox is working to develop Natural Language Understanding for use in cybersecurity, enabling the scanning of content and context of communication.

AI developers are also working on diminishing the need for passwords, using sensors and other contextual information to establish authenticity instead. 

Third-Wave AI is an exciting terrain, with developments that make cybersecurity faster, simpler for the user, and more effective in protecting systems.

MixMode Articles You Might Like:

Unsupervised AI as a Service: Predictive Intelligence for Cybersecurity

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Turning the Unsupervised Tables on the Turing Test

Top 5 Ways AI is Making Cybersecurity Technology Better

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