How AI is shaping the future of cybersecurity

As organizations look to strengthen their defences against increasingly sophisticated cyber threats, the use of artificial intelligence (AI) in cybersecurity is growing exponentially. With the ability to automate tasks and respond to threats faster than ever before, AI and machine learning are playing a vital role in transforming traditional cybersecurity practices.

This article will take a deep dive into how AI is reshaping the cybersecurity landscape as we know it: we’ll discuss what this means for the future of digital security and will also predict upcoming trends that might begin to take shape in the industry. We’ll also identify the different challenges and risks that come with leveraging AI cybersecurity, and even how to counteract them.

Finally, we’ll explore how prospective cybersecurity professionals can gain the skills they need to succeed in this fast-paced industry. We’ll discuss some pathways for learning and education, including the option of enrolling in programs and bootcamps offered by Lighthouse Labs.

The role of AI in cybersecurity: Enhancing defence

When introducing the subject of AI, there can definitely be some mixed responses: some people certainly value the potential of artificial intelligence and see its great power, but others are understandably intimidated by it.

Although the abilities of artificial intelligence might be hard to comprehend, the reality is that AI is incredibly powerful and useful in any industry: it can automate tasks, enhance decision-making, and create innovative solutions.

In establishing the incredible potential of AI, let’s dive into the many areas of cybersecurity where AI can enhance existing protocols.

Threat detection and prevention

One of these is in threat detection and prevention, as AI is able to analyze vast amounts of data and can identify potential threats faster than human analysts.

This speed is particularly important to keep up with as new threats and attacks are emerging at an unprecedented pace in our ever-changing world. For this reason, AI is critical in identifying malware, detecting anomalies in network traffic, and predicting attacks through pattern recognition.

To predict, detect and identify these attacks, AI uses machine learning algorithms and deep learning models to analyze data. Once fed with the data, AI assigns labels to different features and classifies the data in order to ultimately identify recurring patterns.

Automating incident response

AI can also help automate incident response times. When anomalies are detected, AI systems can trigger predefined actions, such as notifying appropriate stakeholders. This use of AI in cybersecurity automation can significantly alleviate the manual workload of a security team and can even aid in minimizing human error and mitigating damage during breaches. In doing so, AI will allow organizations to contain and resolve incidents more efficiently and effectively.

Adaptive learning and evolution

Lastly, another significant advantage that AI has in this field is its ability to adapt, learn and evolve. Unlike traditional security systems, AI can learn and adapt to new, evolving threats through machine learning. AI models are continuously updating and improving their accuracy by learning from past attacks and security data, which ensures that organizations can maintain resilience against new threats.

AI use cases in cybersecurity

There are so many ways that artificial intelligence can be leveraged in cybersecurity. Let’s dive into 3 main ones.

1. AI-driven security tools

For one, there are a variety of AI-driven security tools and platforms that are commonly used in the cybersecurity industry today.

Let’s begin with behavior analysis systems like Darktrace and Vectra. Tools like these leverage machine learning capabilities to detect unusual behavior that might indicate a security threat or attack.

There are also automated threat-hunting tools like CrowdStrike Falcon that proactively seek out and identify malware.

AI is also often used in antivirus software like Sophos, which uses pre-existing intelligence to cross-reference potentially unusual or fraudulent activity.

2. Real-time threat intelligence

Another way that AI can be implemented into cybersecurity is in real-time threat intelligence. Since artificial intelligence is able to sift through large amounts of data very quickly, AI is able to analyze threat intelligence feeds in real-time. AI-powered threat detection can, in turn, help organizations reduce response times and enable teams to make faster decisions about potential risks.

3. Fraud detection and prevention

Fraud detection and prevention is also an important use case for AI, particularly when it comes to sectors like financial services or e-commerce. Since these industries disproportionately deal with fraudulent transactions and identify theft, AI can help detect and prevent fraud by analyzing behavioral patterns, financial transactions, and unusual activity.

Challenges and risks of AI in cybersecurity

Since the use of artificial intelligence in cybersecurity is a somewhat recent development, there are many challenges and risks that come along with this new approach.

1. AI-powered cyberattacks

For example, just as AI can enhance our defence against threats, it can also unfortunately be weaponized by ill-intentioned attackers. AI-driven malware and adversarial machine learning techniques pose new threats to cybersecurity that have not previously existed.

One common cyber attack using AI includes the use of deepfakes for automating phishing scams. This is usually when attackers use AI-generated images, videos or even audio to create convincing imitations to steal sensitive information.

Cyber attacks have been on the rise in recent years: Forbes reported that there were more than 343 million cyber attack victims in 2023, and that data breaches rose by 72% between 2021 and 2023. With attacks on the rise, it’s more important than ever to ensure you have the right cybersecurity skills.

2. Over-reliance on AI and automation

Another prominent challenge that comes with using artificial intelligence in cybersecurity is developing an inevitable over-reliance on AI and automation in general. Relying too much on AI can be risky if systems lack human oversight, as AI models can easily misinterpret data or fail to respond correctly to novel threats.

This notion is already present in our modern day with the likes of ChatGPT, which has had to add a disclaimer for users to double check before they blindly copy and paste (“ChatGPT can make mistakes. Check important info.”)

With this idea in mind, it is clear that the future of cybersecurity AI lies in human-in-the-loop systems (HITL for short) that combine AI with human judgment. These kinds of systems use a collaborative approach that allows for human feedback to improve the accuracy of machine learning models.

3. Ethical considerations

Finally, there are also some ethical considerations with AI that we need to keep in mind. AI introduces many ethical concerns, such as bias in algorithms, privacy concerns with AI data processing, and the risk of unaccountable decision-making in critical security situations.

To maintain a sense of transparency and ethics in cybersecurity, it is important for organizations to begin using transparent, explainable AI in their cybersecurity systems. As is evident in the name, transparent AI systems allow users to understand how they work: this includes insight into how algorithmic decisions are made and how data is processed.

If you are interested in building your own transparent AI program for your business, Lighthouse Labs can help ensure that your company is implementing best practices for cybersecurity and AI.

Check out our Tailored Solutions and see how Lighthouse Labs can help you drive results!

The future of AI in cybersecurity: What to expect

As the use of AI in cybersecurity continues to grow and evolve, there are some developing trends to keep an eye out for.

1. Increased AI integration across sectors

For instance, it is expected that AI integration will increase across all sectors of business, including healthcare, finance, and government.

As AI continues to expand its role in these different sectors, it will, in turn, be able to offer better protection against industry-specific cyber threats. As the volume of cyber threats continues to increase, we can also predict AI adoption in cybersecurity will grow both in Canada and globally.

Statistics Canada recently found that in the first quarter of 2024, approximately one in seven Canadian businesses were already using (9.3%) or had plans to use (4.6%) generative AI. They also found that larger organizations are more likely to adopt AI than smaller ones, and that businesses in information and culture industries (24.1%) are using AI more than any other industry.

2. AI and the human-AI partnership

Additionally, as noted earlier, another likely trend in this industry is the collaborative partnership between humans and artificial intelligence. By combining the speed and accuracy of AI with the intuition and creativity of humans, the future of AI in cybersecurity will be both an ethical and an efficient one.

Although there is a common misconception that robots and artificial intelligence will eventually replace us all (be nice to the robots), the truth is that we still need the unique nuances of the human touch. AI is really there to augment human capabilities rather than replace them entirely, which in turn, will allow cybersecurity professionals to focus on more strategic tasks.

In practice, this can manifest in many ways: developers might use AI to assist in writing lengthy code, writers might use it to help in structuring a long-form piece, and marketers might use it to help build a framework for new personas. The possibilities are truly endless!

3. AI in offensive security

Finally, we can also expect that the presence of AI in offensive security will increase. In order for organizations to be more resilient to incoming threats, it is vital to be proactive and perform penetration testing to get ahead of new attacks.

AI can definitely help in this case: for instance, AI is able to simulate real-world cyberattacks to help organizations improve their defences. This is a process typically known as red-teaming in cybersecurity, which is when organizations look at threats from the perspective of the attacker.

With so many ways to leverage the power of artificial intelligence in cybersecurity, it’s clear that the future of the industry is one that embraces AI as a resource and a tool. Even cybersecurity experts are saying the same thing: Lighthouse Labs recently sat down with Penny Longman, Director of Security Assurance Services at Kyndrl, who said the following about AI in cybersecurity:

“I do see a rearrangement of things. I see there are technologies coming into play that will change where we focus our energies on protection and detection and response. But I don't see there being a reduction in the workforce.

I do see it changing. I see a lot more in what we call shifting left of boom. So before, not responding after the attack, but also preparing but also better software design. You know in our field it's medical device design. We still have devices running Windows XP because of the nature of this cycle, but it's better software design, better application security, better architectural design.”

Upskilling for the AI-driven future of cybersecurity

As AI continues to improve and innovate, cybersecurity professionals need to be able to adapt to new updates and functionalities. This is critical for staying competitive in the field as professionals must continuously enhance their skills in order to stay relevant and keep up with artificial intelligence cybersecurity trends.

For those interested in starting to learn about AI, there are many introductory (and often free!) courses available online on platforms like Coursera. These kinds of foundational courses can give you a solid baseline understanding in order to eventually upskill in AI.

However, if you’re interested in a more in-depth and intensive training program, consider enrolling in Lighthouse Labs’ Data Science Bootcamp.

You can also start your cybersecurity career by completing industry certifications and training programs that focus on cybersecurity, like Lighthouse Labs’ Cybersecurity Bootcamp In this program, you will study a variety of subjects including network security, encryption and threat detection, and you’ll also get to learn the basics of coding and programming.

Whether you’re interested in becoming a Security Analyst, Security Researcher or Incident Responder, this bootcamp will teach you all the fundamentals you need to jumpstart your career. Plus, our programs can either be completed in a full-time, 12-week format or a flexible, 30-week format, so you can pick whichever works best with your schedule and lifestyle.

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In conclusion, it’s clear that AI has the immense potential to revolutionize cybersecurity as a whole. Artificial intelligence can help us by improving defence mechanisms, detecting threats, and streamlining security operations, which in turn reduces the workload of hard-working cybersecurity professionals.

However, this does not mean that we should completely rely on automation and machine learning. As we’ve discussed, there is a need for a balanced approach that recognizes both the opportunities and risks associated with AI in cybersecurity.

If you are considering pursuing a career in cybersecurity, make sure that you start taking proactive steps to upskill so you can stay ahead of AI advancements in the industry. Check out the curriculum for our Cybersecurity Bootcamp and enroll today to start your journey!