Using
Machine Learning
for Cybersecurity
Why Cybersecurity Needs Machine Learning
The goal of modern Machine Learning is to help humans classify data based on a specific model, and/or make predictions for future outcomes based on those models.
In cybersecurity, this means facilitating faster response speed with accurate data. Because computers work faster than humans — they can use the mathematical models to determine what needs to be addressed. In an environment that’s constantly under attack, you need triaged findings that are timely and actionable.
The real-time response that is possible from having reliable data at your fingertips cannot be overstated.
What is Machine Learning?
The work of Machine Learning began back in the late 1950s with IBM. At the time, the concept of “self-teaching computers” was limited to a focus on pattern identification and classification. Over a period of 20 years, computer scientists worked to teach computers how to “learn” from “experiences”.
Simply, if they could get a computer to gain “experience” from having their performance evaluated on a set of “tasks” — then they could grow the computer’s “experiences” through the feedback on the “performance.”
Using
Machine Learning
for Cybersecurity
Why Cybersecurity Needs Machine Learning
The goal of modern Machine Learning is to help humans classify data based on a specific model, and/or make predictions for future outcomes based on those models.
In cybersecurity, this means facilitating faster response speed with accurate data. Because computers work faster than humans – they can use the mathematical models to determine what needs to be addressed. In an environment that’s constantly under attack, you need triaged findings that are timely and actionable.
The real-time response that is possible from having reliable data at your fingertips cannot be overstated.
What is Machine Learning?
The work of Machine Learning began back in the late 1950s with IBM. At the time, the concept of “self-teaching computers” was limited to a focus on pattern identification and classification. Over a period of 20 years, computer scientists worked to teach computers how to “learn” from “experiences”.
Simply, if they could get a computer to gain “experience” from having their performance evaluated on a set of “tasks” – then they could grow the computer’s “experiences” through the feedback on the “performance.”
Breaking it Down
Here’s an analogy:
Imagine you’re changing the oil in your car.
Task = change your car’s oil
Success = engine longevity
The process
Collect the supplies
Drain the oil
Change the filter
Pour in liquid
The outcome
The car seizing up… Why? You’ve mistaken transmission fluid for engine oil.
What you got right:
2. Drain
3. Change
4. Pour
What you got right:
2. Drain
3. Change
4. Pour
What “experience” was wrong:
1. Collect
(you grabbed the wrong fluid)
The Feedback:
- Funny sounds
- Smoke
- Engine stops running
Why are we talking about cars?
Because it’s easier to put it in your mind’s eye.
Now consider this…
The Magnitude of the Issue
One car seizing = unpleasant, expensive, time-consuming
One million cars, continuously seizing, over a period of a million years…
That’s what we’re dealing with — the cars are your algorithms at work.
They’re telling you “yes, you got it right!” Or “no — that’s not going to work.”
Why are we talking about cars?
Because it’s easier to put it in your mind’s eye.
Now consider this… the magnitude of the issue
One car seizing = unpleasant, expensive, time-consuming
One million cars, continuously seizing, over a period of a million years…
That’s what we’re dealing with – the cars are your algorithms at work.
They’re telling you “yes, you got it right!”
Or “no – that’s not going to work.”
Applying Machine Learning to Cybersecurity Challenges
Unefen utilizes a variety of Machine Learning tasks to help users discover their unknowns. We scrape data from your existing tech stacks in a form of data mining.
We then take the lessons learned from the tuned Artificial Intelligence and apply exploratory data analysis. Combined, we are able to use predictive analytics to determine what is residing within your environment.
From aggregation to classification, to triangulation, to risk mitigation, and actionability — Unefen solves the problem of revealing the unknowns and allows you to automatically remediate issues or dive into anomalies that require deeper inspection by a security analyst.
Using Machine Learning and natural language processing helps:
Provide rapid insights, not just generate volumes of data
Reveal key findings and prioritize alerts
Reduce mean time to detect (MTTD) and mean time to respond (MTTR)
Eliminate manual aggregation and time-wasters
Connect the dots between threats within your environment
Applying Machine Learning to Cybersecurity Challenges
Unefen utilizes a variety of Machine Learning tasks to help users discover their unknowns. We scrape data from your existing tech stacks in a form of data mining.
We then take the lessons learned from the tuned Artificial Intelligence and apply exploratory data analysis. Combined, we are able to use predictive analytics to determine what is residing within your environment.
From aggregation to classification, to triangulation, to risk mitigation, and actionability – Unefen solves the problem of revealing the unknowns and allows you to automatically remediate issues or dive into anomalies that require deeper inspection by a security analyst.
Using Machine Learning and natural language processing helps:
Provide rapid insights, not just generate volumes of data
Reveal key findings and prioritize alerts
Reduce mean time to detect (MTTD) and mean time to respond (MTTR)
Eliminate manual aggregation and time-wasters
Connect the dots between threats within your environment
Benefits of Artificial Intelligence and Machine Learning
The greatest benefit of AI/ML in Unefen is comprehensively identifying and triaging “unknowns”… until now, that wasn’t possible.
To quote Mark Twain, “It’s not what you don’t know that kills you, it’s what you know for sure that ain’t true.”
CIOs, CISOs, and CSOs invest in a multitude of cybersecurity technologies aimed at knowing what’s going on in their threat landscapes. Decisions are made based on incomplete data.
Until now, these people have chalked it up to “it is what it is” — wishing for a magic wand to solve the problem, but believing it couldn’t exist. But at Unefen — it does.
Now, you can know the truth. You can see with limitless visibility. You can know all of the ins and outs of who, what, when, where, and how. And, you can take action.
In short, incorporating Unefen’s Artificial Intelligence/Machine Learning platform will help you:
Scale your security to shield enterprise-size attack surfaces
Identify threats and minimize breach risks
Enhance cyber hygiene and improve security posture
Discover risky users, assets, and data faster
Directly respond to relevant alerts and incidents
Benefits of Artificial Intelligence and Machine Learning
The greatest benefit of AI/ML in Unefen is comprehensively identifying and triaging “unknowns”… until now, that wasn’t possible.
To quote Mark Twain, “It’s not what you don’t know that kills you, it’s what you know for sure that ain’t true.”
CIOs, CISOs, and CSOs invest in a multitude of cybersecurity technologies aimed at knowing what’s going on in their threat landscapes. Decisions are made based on incomplete data.
Now, you can know the truth. You can see with limitless visibility. You can know all of the ins and outs of who, what, when, where, and how. And, you can take action.
In short, incorporating Unefen’s Artificial Intelligence/Machine Learning platform will help you:
Until now, these people have chalked it up to “it is what it is” – wishing for a magic wand to solve the problem, but believing it couldn’t exist. But at Unefen – it does.
Scale your security to shield enterprise-size attack surfaces
Identify threats and minimize breach risks
Enhance cyber hygiene and improve security posture
Discover risky users, assets, and data faster
Directly respond to relevant alerts and incidents
Scalability and Evolution
Scalability and Evolution
We know it’s trite… the sophisticated adversary is evolving (PS, they’re using AI/ML too) — but the reality is, they are becoming savvier.
Defending your attack surface means discovering your vulnerabilities before they can. It also means prioritizing which risks must be addressed, and which will have to wait. Dynamic detection that uses the tools you already have in place will allow you to scale your operations and evolve. With Unefen, you can harness AI/ML in an easy-to-incorporate way.
We know it’s trite… the sophisticated adversary is evolving (PS, they’re using AI/ML too) — but the reality is, they are becoming savvier.
Defending your attack surface means discovering your vulnerabilities before they can. It also means prioritizing which risks must be addressed, and which will have to wait. Dynamic detection that uses the tools you already have in place will allow you to scale your operations and evolve. With Unefen, you can harness AI/ML in an easy-to-incorporate way.
