Humanity Elevated Future Proofing Your Career - Ethical AI in Cybersecurity - The Human Firewall

Episode Date: January 9, 2025

This upcoming book by Muammar Lone, an experienced enterprise architect, provides a comprehensive framework for implementing ethical AI security solutions. It integrates academic research with practical experience, offering technical guidance on AI security mechanisms, architectural patterns, and ethical considerations. The text covers various industries, including financial services and healthcare, providing case studies and best practices. It emphasizes human-AI collaboration, risk management, and continuous improvement, ultimately aiming to build ethically robust AI security cultures. Appendices offer further resources, including technical references, ethical guidelines, assessment tools, and implementation templates

Hey, everyone. Welcome to another deep dive with us. Today, we're tackling this new book, The Human Firewall by Muammar Lone. Yeah, The Human Firewall, Ethics and Security in the Age of AI, to give it its full title. Oh, the full title. Very important. So Lone is an enterprise architect. That's right. And he's also got an executive MBA. Yeah, so he's coming at this whole AI security thing from a really interesting angle.

Definitely. Like he gets the tech side, but also the business side. Yeah. Which I think is super important. Absolutely. Because at the end of the day, businesses are the ones who have to actually implement these AI security solutions. Exactly. And make decisions about how to use AI ethically, you know, responsibly.

Right. Which is a whole other can of worms. Totally. But we'll get to that. So this book, The Human Firewall, is kind of aimed at. Well, Lone says it's for anyone in a leadership role who's dealing with technology. OK, so like CIOs. Yeah. All those C-suite folks. But also like tech leads, software architects, anyone who's making decisions about, you know, what tech to use and how to use it. Right. Because those are the folks who are going to be shaping how AI is used in their organizations. Exactly. And whether it's used for good or for.

Or for not so good. Yeah. Okay. So even though the book is kind of targeted at those leadership roles. I think everyone should at least have a basic understanding of this stuff. Yeah, for sure. Like AI is impacting all of our lives, whether we realize it or not. Totally. And it's only going to become more prevalent in the future. Absolutely. So that's why we're doing this deep dive to give everyone a crash course in AI security. Exactly. So buckle up, folks. It's going to be a wild ride. Okay. So to kick things off, Lone starts the book with this crazy story. Oh, yeah. The one about the Fortune 500 company

that got hit with that AI-powered ransomware attack. Right. Back in the winter of 2023, I think it was. Yeah. It was a pretty big deal. It really showed how AI is changing the game when it comes to cyber threats. Definitely.

Like, we're not just dealing with those stereotypical hackers in hoodies anymore. Right. These attacks are getting way more sophisticated, and AI is making it possible. Okay, so for those of us who aren't cybersecurity experts, can you give us a little background on how we even got to this point? Sure. So cybersecurity has been around for a while, but it used to be a lot simpler. You know, back in the day, it was all about building those digital walls around your network.

Yeah, like firewalls and antivirus software. Exactly. That was kind of the main focus. Keep the bad guys out. But now it's a lot more complicated. Way more complicated. It's not just about keeping people out anymore. It's about detecting threats that are already inside your network.

And AI is a big part of that. Huge part. AI can analyze massive amounts of data and identify patterns that humans would never be able to see. So it's like having a super-powered security guard who's constantly watching for any suspicious activity. Exactly.

And AI can also respond to threats much faster than a human can. Which is crucial because these days attacks can happen in the blink of an eye. Exactly. Like Lone points out in the book, global corporations are facing over a trillion security events every year. A trillion. That's mind boggling. It is. And there's no way humans can handle that kind of volume on their own.

So AI is basically essential for cybersecurity now? Pretty much. It's not a question of if you should use AI anymore. It's a question of how. Okay. So what does all of this mean for the cybersecurity professionals out there? Are they all going to be out of a job soon? I don't think so. But their jobs are definitely changing. How so? Well, Lon talks about three main challenges that are facing the cybersecurity industry right now. Okay, hit me with them.

First, you've got the sheer volume and speed of the data. Like we were just saying, there's just so much information to process these days. It's like drinking from a fire hose. Exactly. And it's only going to get worse as more and more devices come online. Okay, so that's challenge number one. What's next?

Challenge number two is the increasing sophistication of the attacks themselves. Like we were talking about earlier, AI is making it possible for attackers to create these incredibly complex and adaptive threats.

So it's like an arms race, but with technology instead of weapons. Exactly. And the attackers are always one step ahead. Okay, so tons of data, super smart attackers. What's the third challenge? Resource constraints. A lot of security teams are already stretched thin, and they don't have the budget or the manpower to keep up with these evolving threats. Yeah, I can imagine that's a huge problem. So basically, it's like a perfect storm. Pretty much.

Tons of data-sophisticated attackers. Not enough resources to fight them off. Sounds pretty daunting. But I'm guessing Lone doesn't just leave us there in despair, right? No, no. He actually sees these challenges as opportunities. Opportunities? How so? Well, for one thing, it means that cybersecurity professionals are going to need

to develop new skills. Like what kind of skills? Things like data science, AI engineering. You know, they're going to need to be able to understand and work with these new technologies. So instead of being replaced by AI, they're going to need to learn how to partner with it. Exactly. It's a whole new way of thinking about cybersecurity. That makes sense. Yeah. So what else does Lone suggest? He talks a lot about the need to redesign existing security processes.

Like how? So. Well, for example, incident response. You know, traditionally, when there's a security incident, a team of humans would have to investigate it, figure out what happened, and then take steps to contain the damage. Right. But with AI, a lot of that process can be automated. So AI could detect the threat, analyze it, and even take steps to neutralize it? Exactly.

And that frees up the human analysts to focus on the more complex and strategic tasks. So it's not about replacing humans altogether. Yeah. It's about using AI to make them more efficient. Exactly. And that's a theme that runs throughout the whole book, this idea of humans and AI working together. I like that. It's not just about the technology. It's about the people, too. Right. And Lone has some really interesting ideas about how that partnership can work. OK, well, I'm definitely intrigued.

So in part two of our deep dive, let's explore some of those ideas in more detail. Sounds good. Let's do it. Picking up on that idea of, you know, redesigning security processes, Lone has this whole concept of the human firewall. Yeah, that's a really catchy phrase. But what does it actually mean? Like, are we talking about turning people into actual firewalls? Not quite. It's more about creating the synergy between human intelligence and artificial intelligence.

Okay. So humans and AI working together. Gotcha. But how does that actually work in practice? Well, Lone lays out this framework he calls the decision support architecture. It's kind of like a blueprint for how humans and AI can collaborate on security decisions. Interesting. So it's not just about throwing AI at the problem and hoping for the best. Nope. There's a real structure to it. Lone breaks it down into three levels strategic tactical

and operational. OK. So strategic level. What's happening there at the strategic level you've got AI analyzing long term trends you know trying to predict what threats might be coming down the pipeline.

So it's like AI is doing the big picture thinking. Exactly. And then human experts use those insights from the AI to set overall security policies for the organization. Okay, so AI is kind of like a crystal ball. And humans are the ones interpreting the visions. Yeah, something like that.

Then at the tactical level, things get a little more hands-on. So at the tactical level, you might have AI monitoring network traffic in real time. Looking for anything suspicious. Exactly. And when the AI spots something, it flags it for a human analyst to investigate. So AI is like the alarm system and humans are the security guards. Perfect analogy. And then the operational level is where AI can really start to automate things. Like what kind of things? Things like patching software vulnerabilities, blocking known malware.

You know, the routine stuff that takes up a lot of time for human analysts. So the AI is handling the grunt work, freeing up the humans to focus on the more complex stuff. Exactly. It's all about efficiency. This decision support architecture sounds pretty cool, but it also sounds like it requires a lot of trust between humans and AI. Oh, definitely. Lone talks a lot about the importance of trust in this whole human-AI partnership.

Because if you don't trust the AI, you're not going to be very likely to follow its recommendations. Right, which defeats the whole purpose. So Lone suggests different interaction models for how humans and AI can work together. Interaction models? What are those? Well, one model he highlights is called augmented intelligence, which is basically about using AI to enhance human capabilities. So it's not about replacing humans. It's about making them better at their jobs. Exactly. In this model, AI systems act as like super smart assistants to the human analysts. OK, so like AI could analyze a ton of data and then present the key findings to the human in a way that's easy to understand. Exactly. Or it could offer recommendations for how to respond to a threat.

But the human is still the one making the final decision. Right. It's all about collaboration. It's kind of like having a co-pilot in the cockpit. Yeah, that's a good way to think about it. The AI can provide valuable information and guidance, but the human is still the one flying the plane. I like that analogy. But even with a good co-pilot, you still need a good cockpit to work in, right? Exactly. And that's where the design of the human AI interface becomes really important.

Because if the interface is clunky or confusing, it's going to make it hard for humans to trust the AI. Right. Lone emphasizes that the interface needs to be intuitive, easy to understand, even for people who aren't tech experts. So no complicated code or anything like that? Nope. It should be all about clear visualizations, personalized dashboards, you know, things that make it easy for humans to digest the information and make decisions. So it's not just about having the right AI. It's also about presenting it to humans in a way that makes sense. Exactly. And that builds trust. Okay.

So we've got the AI. We've got the interface. What else do we need to make this human firewall thing work? Well, Lone also talks about the importance of transparency and explainability, meaning that the AI can't just spit out a decision. It needs to be able to explain how it got there. So like show its work. Exactly. Because if humans don't understand how the AI is making decisions, they're not going to trust it. Makes sense. So transparency and explainability are kind of like the foundation of trust in this whole human AI partnership.

Exactly. And it all ties back to those ethical considerations we were talking about earlier. Right. Because if we're going to give AI more and more power in cybersecurity, we need to make sure that it's being used responsibly. Absolutely. And that's something that Lone really emphasizes throughout the book, this idea of ethical AI. Okay. Well, I'm definitely starting to see how all of these pieces fit together. Yeah. But I'm also realizing that there were probably a lot of challenges that come with implementing these changes. Oh, yeah, for sure. There are technical challenges, organizational challenges, and even cultural challenges.

Okay, well, let's unpack those a bit. In part three of our deep dive, we'll explore some of the specific hurdles that organizations face when they try to implement these AI security solutions and how they can overcome them. Welcome back to our deep dive. All right, so we spent the last two parts talking about all the cool stuff that AI can do for cybersecurity. Yeah, the potential is definitely huge. But I'm guessing it's not all sunshine and roses.

Uh-huh. No, not exactly. There are definitely some real world challenges that organizations face when they try to implement these AI security solutions. Okay, so let's get into the nitty gritty. What are some some real world challenges that organizations face when they try to implement these AI security solutions. OK, so let's get into the nitty gritty. What are some of the biggest hurdles? Well, one of the biggest is integration complexity. Integration complexity, meaning? Meaning that a lot of organizations already have all these different security systems in place.

Right. Like firewalls, antivirus software, that kind of thing. Exactly. And most of those legacy systems weren't designed with AI in mind. So trying to integrate these new AI-powered tools into those older systems can be a real pain. Yeah, it can be a nightmare. It often requires a ton of custom coding and configuration just to get everything to talk to each other. And even then, there's no guarantee that it's going to work perfectly. Right. You might run into compatibility issues or performance bottlenecks. So it's not just a matter of buying the latest AI-powered security tool and plugging it in. Nope. It's a lot more complicated than that.

Organizations really need to think strategically about how they're going to integrate AI into their existing security infrastructure. Okay. So that's challenge number one, integration complexity. What else? Another big one is performance optimization. Meaning? Meaning that AI systems can be really resource intensive. Yeah, I can imagine. They're crunching tons of data all the time. Exactly. And that takes a lot of processing power, memory storage, the whole shebang. So if you don't have the right infrastructure in place, your AI security solution might not be as effective as it could be. Right. You might end up with slow response times or even system crashes,

which is obviously not ideal when you're trying to protect yourself from cyber attacks. Definitely not. Okay. So integration and performance are two big challenges. What else is there? Well, there's also the issue of data quality. Data quality. How so? Well, as you know, AI systems are trained on data. Right. And if that data is bad, the AI is going to make bad decisions. Garbage in, garbage out, as they say. Exactly. So organizations need to make sure that they're feeding their AI systems high quality data, data that's accurate, relevant, and representative of the actual threats they're facing. And that's not always easy to do. Nope. The threat landscape is constantly changing. So organizations need to have robust

data collection and analysis processes in place just to keep up. Okay. So we've talked about some of the technical challenges. Yeah. But I'm guessing there are also some human challenges. Oh, yeah, for sure. One of the biggest ones is the skills gap. The skills gap. The skills gap. Meaning that there just aren't enough people out there who have expertise in both cybersecurity and AI. Yeah, I can imagine that's a pretty niche skill set.

It is. And it's in high demand. So organizations are struggling to find qualified people to fill these roles. So what can they do? Well, they can either invest in training their existing cybersecurity teams in AI, or they can try to poach talent from other companies. Which can be expensive. Very expensive. But it's an investment that a lot of organizations are willing to make because the stakes are so high. Right. If you don't have a strong AI security team, you're basically leaving yourself wide open to attacks. Exactly. So the skills gap is a major challenge, but it's not the only one. What else is there? Well, there's also the issue of process redesign. Process redesign, meaning? Meaning that as AI becomes more integrated into security operations,

organizations are going to need to change the way they do things. Can you give me an example? Sure. Let's say an organization implements an AI-powered threat detection system that can automatically block certain types of attacks. Well, that might change the way the security team responds to incidents. How so? Well, before, they might have had a human analyst investigate every single alert. Right. But now, with the AI blocking some of those attacks automatically, the human analysts might only need to get involved in the more serious cases. So it's about freeing up the humans to focus on the things that AI can't do.

Exactly. But changing those processes can be difficult. Yeah. Because people are used to doing things a certain way. Right. And they might resist change. So organizations need to have a good change management plan in place. Definitely.

They need to communicate clearly with their employees, explain why these changes are necessary, and provide adequate training and support. Okay. So we've got the skills gap. We've got process redesign. Anything else? Well, Lone also talks about the importance of ongoing evaluation and measurement, meaning that organizations need to track how well their AI security solutions are performing. And make adjustments as needed. Exactly. It's not a set it and forget it kind of thing. So it's like a continuous improvement process. Exactly. You're always learning. You're always tweaking. You're always trying to do better. Makes sense.

Well, this has been a really fascinating deep dive. I feel like I've learned a ton about AI security. Me too. It's definitely a complex topic. But Lon does a great job of breaking it down and making it understandable. Yeah, he really does. And I think his book, The Human Firewall, is a must read for anyone who's interested in this field. Absolutely. It's a great resource for both technical folks and business leaders. All right. Well, that's all the time we have for today. Thanks for joining us on this deep dive into the world of ethical AI security. And be sure to check out the Human Firewall if you want to learn more.

Thanks for having me. And as always, stay curious, stay vigilant, and stay safe out there.