AI in Cybersecurity

Summary

The video script highlights the urgent demand for cybersecurity experts and introduces AI as a force multiplier to address this gap. It explains how AI, through knowledge graphs, can investigate issues, identify anomalies in log records, enrich security reports, and assist in research via natural language processing. The speaker emphasizes AI's integral role in IBM's security software, showcasing its potential to revolutionize cybersecurity practices.

Takeaways

• 📈 There is a significant shortage of cybersecurity professionals, with hundreds of thousands of jobs open and a need for more experts.
• 🔧 To address the shortage, organizations are turning to force multipliers like automation and artificial intelligence to increase efficiency and intelligence in cybersecurity operations.
• 🧠 AI is being utilized to investigate issues by creating knowledge graphs that represent information about the physical or logical world in a structured format.
• 🔗 Knowledge graphs can connect various data points, such as domains, IP addresses, URLs, and user activities, to identify and trace the path of potential threats like malware.
• 🔍 Machine learning and pattern recognition are employed to analyze log records and detect anomalies or outliers that may indicate security breaches or insider attacks.
• 📊 Time decay functions and machine learning algorithms help in identifying sequences of actions that, when occurring in rapid succession, could signify a security incident.
• 📝 AI assists in generating compliance reports by processing and enriching data from log records, thus reducing the time spent on manual reporting.
• 🤖 The integration of natural language processing systems, such as chatbots, is on the rise, providing a knowledge base for staff to quickly gain insights about threats or systems.
• 🛡 IBM has recognized the value of AI in cybersecurity, incorporating it into 100% of their security software products.
• 👍 The video encourages viewers interested in cybersecurity to like and subscribe for more content on the topic.
• 🌐 The script highlights the importance of AI in the evolving landscape of cybersecurity, emphasizing its role in investigation, identification, reporting, and research.

Q & A

Why is there a significant number of unfilled positions in the cybersecurity industry?

There are hundreds of thousands of jobs open in the cybersecurity space because the industry is growing rapidly, and there aren't enough experts being trained or developed to fill these positions quickly enough to meet the demand.

What is a 'force multiplier' in the context of cybersecurity?

In cybersecurity, a 'force multiplier' refers to tools or strategies that enhance the effectiveness of existing resources. It allows a limited workforce to work more efficiently and intelligently to meet the growing needs of the industry.

How can automation be used as a force multiplier in cybersecurity?

Automation can be used as a force multiplier by allowing cybersecurity professionals to work more efficiently. It can handle repetitive tasks, analyze large volumes of data quickly, and respond to threats without the need for constant human intervention.

What role does artificial intelligence play in enhancing cybersecurity efforts?

Artificial intelligence can work more intelligently to investigate problems, identify issues, report on problems, and research more about specific problems. It can analyze patterns, detect anomalies, and provide insights that would be difficult for humans to achieve alone.

What is a knowledge graph and how is it used in AI for cybersecurity?

A knowledge graph is a data structure that represents information about the physical or logical world. In cybersecurity, it can be used to connect different pieces of information, such as domains, IP addresses, URLs, and user activities, to identify patterns and relationships that might indicate a security issue or attack.

How can a knowledge graph help in identifying a user infected by malware?

A knowledge graph can represent the connections between a user, an IP address, a URL, and malware. By mapping out these relationships, it can show the path of infection and help identify not only the infected user but also other potential points of compromise.

What is the purpose of log records in cybersecurity?

Log records document events that occur within a system, including the time, date, user actions, and system affected. They are crucial for investigating security incidents, identifying anomalies, and understanding the scope of a potential breach.

How can machine learning be applied to analyze log records and detect anomalies?

Machine learning can be used to analyze vast amounts of log data, applying pattern recognition to identify outliers and anomalies that may indicate suspicious activity or an attack. It can process multiple factors across records to detect unusual behavior that might be missed by human analysis.

What is the significance of time decay function in identifying anomalous activities?

A time decay function can weigh recent activities more heavily than older ones when analyzing log records. This helps in identifying rapid sequences of actions that, when occurring in close succession, may indicate an anomaly or a security breach.

How can AI-assisted reporting help in meeting regulatory compliance requirements?

AI can help in gathering and processing log records more efficiently, enriching the reporting data with insights gained from its analysis. This not only speeds up the reporting process but also ensures that the reports are more comprehensive and compliant with regulatory standards.

What is the potential of a natural language processing system or chatbot in cybersecurity research?

A natural language processing system or chatbot can serve as an interactive knowledge base, allowing cybersecurity professionals to ask questions and receive information quickly. This can aid in investigations by providing rapid access to relevant data and insights about malware, systems, or other security issues.

Why does IBM include AI in all of its security software products?

IBM includes AI in all its security software products to leverage the power of artificial intelligence for more effective and intelligent cybersecurity solutions. It helps in investigating issues, identifying problems, and providing a higher level of security against the evolving threat landscape.

Outlines

00:00

🔒 Leveraging AI for Cybersecurity Investigations

The first paragraph discusses the significant gap in the cybersecurity workforce and the urgent need for force multipliers like automation and artificial intelligence (AI) to address it. The speaker emphasizes AI's role in investigating issues by using knowledge graphs to represent and connect information, such as linking a web domain to an IP address and identifying potential malware. The paragraph also touches on using AI to analyze log records for anomalies and outliers, which can help in identifying attack scenarios, such as an insider exploiting a system. The use of machine learning for pattern recognition and anomaly detection is highlighted, showcasing how AI can be instrumental in diagnosing security problems.

05:02

📝 AI in Streamlining Security Reporting and Research

The second paragraph focuses on how AI can enhance the efficiency of security reporting by reducing the time spent on compliance checks and enriching reports with AI-generated insights. The speaker also envisions the integration of natural language processing systems, such as chatbots, into cybersecurity teams to provide quick answers and facilitate research on threats like malware. The paragraph concludes by highlighting IBM's commitment to AI in security, with all its security software products incorporating AI, and encourages viewers to engage with the content for further exploration of cybersecurity topics.

Keywords

💡Cybersecurity

Cybersecurity refers to the practice of protecting internet-connected systems, including hardware, software, and data, from theft, damage, or unauthorized access. It is the main theme of the video, discussing the challenges of filling job positions and the need for force multipliers like automation and AI to enhance effectiveness in this field.

💡Force Multipliers

In the context of cybersecurity, force multipliers are tools or strategies that amplify the effectiveness of existing resources. The video mentions the use of automation and AI as force multipliers to address the shortage of experts and to work more efficiently and intelligently.

💡Automation

Automation is the use of technology to perform tasks without human intervention. In the video, it is presented as a force multiplier that allows for more efficient work in cybersecurity, potentially handling repetitive tasks and freeing up experts to focus on more complex issues.

💡Artificial Intelligence (AI)

AI refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The video emphasizes AI's role in cybersecurity for investigating issues, identifying problems, reporting, and researching, thus working more intelligently.

💡Knowledge Graph

A knowledge graph is a structured data representation that connects various entities and their relationships. In the video, it is used to illustrate how AI can represent information about the physical or logical world, enabling the connection of various data points to investigate potential security issues.

💡Antivirus Signature

An antivirus signature is a unique pattern or identifier used by antivirus software to detect and block malware. The script uses this term to explain how a knowledge graph could link a URL to a file system that is flagged by an antivirus signature as malware.

💡Machine Learning

Machine learning is a subset of AI that enables systems to learn and improve from experience without being explicitly programmed. The video describes using machine learning to identify anomalous activities by analyzing patterns across multiple log records, helping to detect potential security breaches.

💡Log Records

Log records are detailed reports generated by systems to document events, such as user actions or system changes. The video mentions the use of log records as a data source for AI systems to analyze and identify abnormal behaviors or security incidents.

💡Anomaly Detection

Anomaly detection is the process of identifying unusual patterns or outliers in data that may indicate problems or threats. The script describes how AI and machine learning can be used to analyze log records and detect sequences of actions that deviate from normal behavior, potentially signaling a security incident.

💡Natural Language Processing (NLP)

NLP is a branch of AI that focuses on the interaction between computers and human languages. The video suggests the use of an NLP system, such as a chatbot, to answer questions and provide information during cybersecurity investigations, enhancing the research capabilities of the team.

💡Chatbot

A chatbot is a computer program designed to simulate conversation with human users, often used for customer service or information provision. In the context of the video, a chatbot with a knowledge base could assist cybersecurity experts by answering questions and providing relevant information during investigations.

Highlights

Hundreds of thousands of jobs open in cybersecurity, but not enough experts to fill them.

Force multipliers needed to be more effective in cybersecurity.

Automation and artificial intelligence are key force multipliers in cybersecurity.

AI can be used to investigate problems, identify issues, report on problems, and research more about them.

Knowledge graphs represent information as a data structure for AI to reason over.

Example of using a knowledge graph to trace a path from a user to malware infection.

Knowledge graphs can help identify affected users, malware, and sites.

AI systems use log records to identify anomalous activities and outliers.

Machine learning can detect attack scenarios by analyzing patterns across multiple log records.

AI can enrich security reports with data gathered during investigations.

Chatbots with natural language processing can answer questions and provide information during investigations.

IBM includes AI in 100% of its security software products.

AI helps work more efficiently and intelligently in cybersecurity.

Investigating issues with AI involves connecting information and making inferences.

Identifying problems involves analyzing log records for anomalies using time decay functions and machine learning.

Reporting in cybersecurity can be streamlined with AI by enriching reports with investigation data.

Researching about malware or systems can be aided by AI chatbots with knowledge bases.

Transcripts

Right now there are hundreds of thousands of jobs open in the cybersecurity space.

And we can't fill those positions fast enough and we can't make experts fast enough to fill them either.

So what are we going to do?

With the people we have, we're going to have to use force multipliers in order to be more effective and meet the need.

And two of the things that we can do for force multipliers is we can use automation.

That allows us to work more efficiently, or we can use artificial intelligence--that allows us to work more intelligently.

I'm going to specifically focus on this one in the video today--to talk about how we can use AI to investigate a problem,

to identify an issue, to report on a particular problem, and ultimately to research and find out more about a particular problem.

So let's start with this first one: investigate.

How could we use AI to investigate a particular issue, if we become aware that there might be an issue?

Well, we can use a construct called a knowledge graph,

which is a way of representing information about the physical or logical world, but representing it as a data structure.

And the way this works is--to give you an example.

Let's say we have a domain.

And this would be like the name of a web domain.

And that domain then resolves to a particular IP address.

Also we--so this is what we normally have with a website.

Now, what else do we have?

Well, we might also have a URL.

That's the actual link that you're going to type into your browser.

And that is going to link to a particular file on the file system.

Now, let's take, for instance, if that file on the file system ends up pointing--

because we know through an AV signature, an antivirus signature --what if this points to malware?

Then this is some information that we can now connect together.

Then, if we say that this URL is in fact contained by that domain, and then I add a user out here

unsuspecting--who connects then to this IP address.

Then, all of a sudden I have a path that goes all the way through from this user to this malware.

And now I have this data structure that has represented, in fact, the connection that occurred.

I now know this user has been infected by this malware, and here's the path it took to get there.

And in fact, if this knowledge graph is good enough,

I'll be able to look and see what other users might also be affected and what other malware and what other sites.

So this is a way of representing information and then we can do some reasoning over that in order to do inference.

Now, this is how an AI system might do this internally.

Now, so that's one way we could do investigation.

How about to identify in more detail a particular problem?

So systems will typically write out lots of log records.

Once an event occurs on a system, then we cut a log record.

We put out information about--here's the time, the date, here's who did it.

Here's what they did, here's the system they did it to.

Here's where they did it from.

Those kinds of bits of information would be contained in these log records.

And we have loads and loads of these.

So it's very difficult to sort through all of that and find where are the anomalous activities.

Where are the outliers?

Well, in particular, what we'll find is, in this case, let's go with an example

and say here is a record where a privileged user logged into the system and created a new account.

Then, almost immediately afterward, in almost no time, they copied all the contents of a database.

And then, almost directly immediately, they deleted the account.

Now, each one of these activities independently wouldn't represent necessarily a problem,

but if you do all of these within a very short period of time, then we could use a time decay function and something like machine learning,

which is essentially pattern matching on steroids,

to look at all of these things and look at multiple factors across multiple records and realize we have an outlier, we have an anomaly.

We have what may be an attack scenario where an insider has taken advantage of the system.

So that's another use of AI and machine learning, in particular, in order to diagnose a problem.

What else could we do?

Well, we could report.

There's a requirement in security circles that you report against: Are you complying with regulatory requirements or not?

And some of the things that we might do in those cases is gather the log records and process those.

We might also use information that we've gained here to enrich our reporting data.

So that's another example where enriching the report with the information we have from the AI system,

and that's also allowing us to report, we're spending less time.

And then finally, to do research. Imagine I'm investigating, I'm identifying, I'm doing all these kinds of things.

And what I'd like to be able to do is find out, what is this bit of malware?

And I'd like to know more about it.

I want to know more about any of these systems.

So it would be nice if I had a natural language processing system--a chatbot

that I could go and talk to and ask it questions and it has a knowledge base that it draws on.

So, in fact, we're going to see more and more of this kind of capability going forward

where a chatbot becomes essentially another member of the staff to answer questions as we're trying to do investigations.

So you can see now, AI can help us a lot in the cybersecurity space.

And that's in fact why IBM, 100% of our security software products include AI.

Thanks for watching.

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