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.

oil can icon

Task = change your car’s oil

engine icon

Success = engine longevity

The process

The Lucidum Process Collect the Supplies Icon

Collect the supplies

The Lucidum Process Drain the Oil Icon

Drain the oil

The Lucidum Process Change the Filter Icon

Change the filter

The Lucidum Process Pour in Liquid Icon

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

Lucidum 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 — Lucidum 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

r

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

Lucidum 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 – Lucidum 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

r

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 Lucidum 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 Lucidum — 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 Lucidum’s Artificial Intelligence/Machine Learning platform will help you:

&

Scale your security to shield enterprise-size attack surfaces

U

Identify threats and minimize breach risks

Enhance cyber hygiene and improve security posture

s

Discover risky users, assets, and data faster

Z

Directly respond to relevant alerts and incidents

Benefits of Artificial Intelligence and Machine Learning

The greatest benefit of AI/ML in Lucidum 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 Lucidum’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 Lucidum – it does.

&

Scale your security to shield enterprise-size attack surfaces

U

Identify threats and minimize breach risks

Enhance cyber hygiene and improve security posture

s

Discover risky users, assets, and data faster

Z

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 more savvy.

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 Lucidum, 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 more savvy.

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 Lucidum, you can harness AI/ML in an easy-to-incorporate way.

Machine Learning and Artificial Intelligence gif