Is AI in Cybersecurity a Dream Team or a Doomsday Scenario?

At this point, we can feel pretty confident labeling Artificial Intelligence(AI) as the trending technology of the modern age.  AI technology is not new, it has existed in some form since at least the 1950s. However, the technology has experienced something of a growth spurt in the last couple of years that has greatly expanded its capabilities and potential use cases. 

Before we begin, let’s take a minute to define what Artificial Intelligence (AI) actually is. The term AI gets thrown around quite a bit these days and it could apply to anything from automation to humanoid robots, so it’s important to understand the different types of AI and how each can be used. 

Defining AI

The AI label is generally applied to any computerized activity that simulates the way that humans think, speak, write, or express emotions. At its core AI was created with the idea of combining human ingenuity and creativity with the speed, stamina, and storage capacity of a computer. 

The results so far have been impressive. In some areas, AI can produce results that are indiscernible from, or in some cases, better than those produced by humans. Because computers are capable of analyzing massive volumes of data in seconds, AI that has been linked to the proper database can know far more and work much faster and longer than any human could. Of course, like humans, AI systems are most effective when they are focused on performing a specific subset of tasks. The vast majority of AI being developed and released today is what is known as Narrow AI, or AI that is purpose-built to perform a specific set of human tasks. 

Narrow AI

By now, most have seen the videos of self-driving cars behaving in strange and often comical ways. These events give us a glimpse of what Narrow AI is and what its limitations are. Most AI that is publicly available today falls into the Narrow AI category, meaning it was created to perform a specific set of tasks or fulfill a specific goal. Voice assistants, chatbots, and self-driving cars are all operating in accordance with a pre-defined knowledge base. 

The comical events generally occur when the self-driving vehicle encounters something ambiguous or unusual that it has no predefined instruction for. In most of these instances, the car simply stops because that is what it has been programmed to do in the face of uncertainty. That programming is one of the many guardrails put in place to ensure that Narrow AI stays in its own lane, pun intended.

Narrow AI is not where the story ends. In reality, it is just the beginning. Developers have been hard at work creating sentient AI, meaning AI that thinks for itself.

Artificial General Intelligence (AGI)

Artificial General Intelligence (AGI) is still unproven and exists solely as a theory that posits that eventually, AI will reach a stage where it no longer relies on human intervention and is capable of engaging in the sort of complex reasoning that would make it the intellectual rival of any human. While some believe this next breakthrough is right around the corner, experts in the field debate disagree. They point to the significant hurdles like human emotions, and instincts that are still largely a mystery, even to us, but do play a significant role in the human decision-making process.

Blurring the Lines Between Man & Machine

While AGI may exist only in futuristic fantasy, real-world research aimed at reaching this next plateau has resulted in Narrow AI that blurs the line between man and machine enough to allow AI to emulate human thought and behavior in increasingly complex scenarios. These gains are facilitated by a process known as Machine Learning.

Neural Networks 

Machine Learning (ML) focuses on creating systems that are capable of analyzing input in real-time and determining the best response without explicit programming that provides a definite answer. Deep Learning (DL) takes ML a step further by employing networked processes that mimic the pathways that the human brain follows when making a decision. These are generally referred to as neural networks and their successful deployment has blurred the lines between man and machine significantly, allowing AI to make use of new data to enhance its existing programming and enabling its ability to generate novel and creative content and carry on realistic human conversation.

Generative AI

Neural networks facilitated by DL made what we now call Generative AI possible. Generative AI is the term used for AI that is capable of generating a unique, often creative, product based on a set of instructions. This latest advance in the AI field was introduced to the public with the rollout of ChatGPT by OpenAI. Since that initial introduction, the field has exploded with new Generative AI models capable of producing everything from news articles and novels to music videos and interviews, all created by computers.  

Essentially, a combination of deep learning and machine learning has created AI that is far “smarter” than previous iterations. The new AI tools are capable of “reasoning” through a particular challenge and devising a viable solution on their own…sometimes. These models are still operating from a predefined database of knowledge, but the scope of that knowledge base has been expanded and enough guardrails have been removed that the computers are now capable of solving problems and finding workarounds without human intervention.

This latest development has created an excitement and innovation craze in the business world that is akin to the rollout of the World Wide Web. The possibilities are exciting, but the technology is still largely in its beta stage and there will be plenty of unforeseen issues to iron out before we arrive at a stable new normal. 

For those tasked with ensuring the safety of businesses and individuals as they interact in cyberspace, Generative AI presents both opportunities and challenges. It can be used to quickly identify suspicious patterns automatically blocking access and preventing bad actors from carrying out their attacks. However, criminals can also use it to commit fraud or automated attacks. 

The Role of AI in Cybersecurity

The fact is, AI has been a major part of the cybersecurity landscape for well over two decades now, so the cybersecurity industry is not operating in unfamiliar territory. The industry has been able to put ML algorithms to good use as tools to improve the efficiency and accuracy of their existing fraud detection efforts and counter malware. AI’s ability to quickly spot abnormal patterns in vast amounts of data has allowed the industry to stay a step ahead of bad actors by detecting potential threats much faster than any human-driven system could achieve.

So far, AI’s track record in cybersecurity has been a net positive.  ML-powered antivirus and antimalware algorithms have grown faster and better over time. Today’s iterations can recognize even the most complex forms of malware by simply analyzing its structure and behavior and comparing it against the massive trove of data on known threats.  Following the same basic premise, AI-driven monitoring systems are able to spot and flag suspicious behavior, keeping bad actors and would-be identity thieves from getting a look at private data. AI has become such an integral piece of the cybersecurity ecosystem that it is hard to see any downside. 

So, what are the risks?

The Risk Factors

When it comes to harm potential, it is important to note that the danger is not caused by the AI technology itself, rather it is a consequence of this powerful technology in the wrong hands. All the benefits and advantages of AI in cybersecurity can easily be turned around and weaponized against an innocent target as well. With AI now accessible to the general public in most countries, the risk that this powerful tech is already in the hands of individuals or organizations with nefarious intentions is high. Cybercriminals have already begun using AI to create more sophisticated threats, far beyond those that we have seen in the past.

Automated Attacks 

Automated attacks, known as brute force attacks, have been an ongoing threat to cybersecurity. Essentially, the human attacker creates an algorithm  or code designed to achieve the attackers goal on a remote system. AI has expanded the capabilities of attackers and the scope of the attacks by allowing the automation of complex schemes. Additionally, the latest AI has enabled the creation of malware and other threats that can automatically adapt to evade detection making the threats more difficult to spot and fully eliminate. 

Deepfakes

Generative AI has opened the door to an alarming and insidious new threat that is shifting the battlefield with cybercriminals now using cyber tools, including AI to carry out real-world crimes against real humans. Generative AI is capable of producing what are known as deepfakes, realistic video or audio impersonations of actual humans, producing fraudulent media of unlimited length based on a few seconds of actual footage. Cybercriminals have already used this frightening new ability to conduct “kidnapping” scams tricking terrified family members into delivering large sums of money to save their loved ones. 

AI-Powered Phishing

Phishing attacks are some of the most common of all cyberattacks. Phishing attacks were once able to be countered by simply educating consumers about the red flags to watch for like spelling and grammar mistakes, or unprofessional language. The widespread use of AI has made phishing attacks far more convincing, making it easy for attackers to mimic legitimate businesses or authorities with alarming accuracy convincingly. 

Fighting AI with AI

Sure, AI has given the bad actors a much larger toolkit to work with, but cybersecurity professionals are rising to meet the challenge. As a consumer, there is plenty that you can do on your own to help protect yourself and your family as well. 

Be Proactive

Both companies and individuals should, at a bare minimum, invest in security software or tools that employ AI-powered threat detection. These tools monitor and analyze your system’s activity in real-time, enabling the early detection and elimination of threats before they have a chance to wreak havoc.

Be Certain

Know exactly who you dealing with and make certain that only authorized users gain access to your private data by employing AI-enhanced identity authentication. 2-factor authentication is no longer a fail-safe, by adding AI to create a multi-factor authentication) solution you can protect yourself from bad actors who may have gained access to multiple accounts. 

Be Aware

We say it every time but it is worth repeating. Knowledge is power, and an educated mind coupled with a well-trained staff is one of the strongest defense layers you can have. Make sure that you and your staff are aware of the latest threats and take the steps to mitigate them. 

Call in the Professionals

The world of cybercrime is well-funded and well-educated. When it comes to protecting your vital data, it is important to remember that you are not up against your average criminal. You are facing a vast network of professionals. Give yourself a fighting chance with your own team of professionals.

iLOCK360 service is professional-grade credit monitoring and identity theft protection ready to go to battle for you. Lock down your identity with iLOCK360 now and cross one more worry off your list.

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