Artificial Intelligence for Cybersecurity 

Artificial intelligence isn’t just fit for sci-fi speculation anymore. It’s here, and it’s changing the way our lives work, and our work flows.

More than half of businesses say that AI implementations have improved their productivity, and that’s just the beginning. As AI technology advances, AI programs can actually learn how to become more efficient without our input. If the technological advances of the past thirty years have felt fast, AI technological advances are going to happen at breakneck speed.

It would be hard to escape AI in today’s business landscape. From 2021 to 2022, there was an increase in artificial intelligence and machine learning solutions from 87% to 93%, and those numbers are almost certainly only going to keep rising.

AI solutions can help automate processes, find patterns, and analyze data quicker and more thoroughly than human intelligence can in some cases. But along with every boon to business comes a new, evolving threat.

The Dark Side of AI 

Cyberattacks using AI are a huge risk, that’s only getting more common as the technology improves. AI software was originally created for security, and then began to be used in attacks.

AI cyber attack software is attractive to cyber criminals for the same reason that it’s attractive to people who run legitimate businesses. AI technology improves efficiency without increasing workload. For businesses, this means more time and energy to devote to growth and refining processes. For cyber criminals, it means more time and energy to attack more victims.

Cyber criminals can take advantage of artificial intelligence in a couple of ways.

On the one hand, they can attack with an eye towards limitations in legitimate AI algorithms. While AI technology is incredible, it’s still far from perfect, and artificial intelligence can be “fooled” by cyber criminals who know how to find and exploit loopholes in their code.

The second way that cyber criminals can take advantage of an AI environment is by employing AI software that learns how to better perpetrate attacks. Because AI does the learning on its own and doesn’t need breaks from work, a smart hacking software can work around the clock to find and exploit weaknesses in a network, system, or device.

AI software can be used by cyber find loopholes in IT networks, launch denial of service (DoS) or distributed denial of service (DDoS) attacks, and counter the average organization’s security.

Cyber criminals are aided by the fact that the majority of individuals and businesses do the bare minimum to protect themselves against attack, if that. It’s all too common to see a SMB using consumer anti-virus protection for their business, skipping the all-important security training for their employees, or generally burying their head in the sand when it comes to cyber security.

AI technologies and AI attacks are increasingly sophisticated, but that doesn’t mean they’re impossible to counter.

Learning to Fight AI Cyber Attacks 

One of the most important things a business can do to help protect itself against AI cyber attacks is to learn about how they work. While many cyber attacks like phishing and Business Email Compromise (BEC) can be attributed to the weaknesses in a company’s security knowledge, AI cyberattacks are successful by virtue of weaknesses in a company’s overall security infrastructure.

Knowledge is power, and there are ways that human intelligence can still rise above artificial intelligence.

Machine Learning in Cyber Attacks 

Machine learning is a branch of artificial intelligence focused on the attempts to help machines “learn” as humans do. 

Machine learning began with simple computational tasks, such as winning at checkers, and has evolved into an inextricable part of our digital experience today. Recommendations from Netflix, self-driving cars, the songs that our Alexa plays for us, the ads we get served can all be traced back to machine learning computation. 

A typical machine learning algorithm will include three components: a decision process, an error function, and an updating or optimization process. Together, these three processes analyze data, compare it against known data, and using the information gathered, optimize for the next round of data collection and analysis.

The trouble with machine learning in cyber attacks is that hackers use complicated techniques to evade detection, including polymorphism, impersonation, compression, and obfuscation. 

This means that hackers can intrude on systems at their leisure, with algorithms that may be indistinguishable from those existing in the system. The malicious algorithms can meanwhile carry out nefarious aims such as data leakage or denial of service attacks without anyone being the wiser.

Machine learning is an important subset of artificial intelligence that makes many of the astounding AI advances possible.

Machine Learning vs AI

One important distinction to keep in mind is the difference between machine learning and artificial intelligence

Machine learning is the process of a machine learning from data. It’s all about data collection and analytics. 

Artificial intelligence, on the other hand, goes a step further, into programming. Artificial intelligence can not only “learn” like machine learning software, but can use its knowledge to determine and execute the best course of action.

Evolutionary computation falls under the umbrella of computational intelligence, and may be the most impactful technique for advancing AI. Computational intelligence describes a variety of computing techniques that seek to optimize algorithms through natural modes inspired by biology and linguistics.

Evolutionary computation is defined by algorithms inspired by natural biological evolution and used to define populations, terminating when it has found the best possible population, after going through processes that mirror biological evolution, like convergence, mutation, selection, and replication. 

The use of evolutionary computation within artificial intelligence can create ever-stronger programs and attacks that run 24/7. That means that they can work without rest, and in many cases, without detection.

These different types of intelligent computing can work wonders for humanity, by optimizing algorithms, processes, and systems that could bestow us with immense benefits. The downside is that hackers have access to these incredible technologies also, and are motivated to optimize them to achieve their aims.

Fighting Against AI Cyberattacks 

The battle against artificial intelligence is far from over. You can secure your network, and prevent the catastrophic losses that some businesses suffer by adhering to best practices and staying on top of key tips for cyber defense.

Understand your Inside Risks 

It’s important to know exactly what risks you have already built into your system so you can guard specifically against them. It’s more common than you’d think for programs and systems to utilize open source code, which has been largely responsible for the collaboration that has advanced our computational power so far so quickly.

The downside of open source code is that anyone can access it, and gain intimate knowledge of the vulnerabilities contained within. The same is true for code that you use from software programs that are publicly available for purchase.

It’s critical to be smart about your code. Know what you have, keep it updated, and ensure that you’re not allowing malicious codes in on the update. 

Monitor and Analyze Regularly 

Hand-in-hand with understanding your inside risks is the importance of monitoring and analyzing your code regularly. This doesn’t mean a spot-check once a month. It means developing a keen awareness of everything going on in your codebase, systems, and processes, so that you’ll be able to quickly identify anything that’s out of place.

According to IBM and the Ponemon Institute, it takes on average about 226 days to detect a cyber attack incident, and 73 days to contain it. Allowing an incident to go on for more than 60% of the year means that any incident involving artificial intelligence will be well-entrenched by the time you detect, and that much harder to contain and eliminate. 

Keep your eyes on your code, and flag suspicious activity immediately.

Mitigate human error 

Even as cyber criminals increasingly turn to machine learning and artificial intelligence to hack and thieve from companies, the human element remains the biggest variable that could be weakening your cybersecurity. 

Almost 50% of American workers trust public wifi for work-related tasks, more than half of organizations report that their employees don’t follow cybersecurity protocols, and people have notoriously bad password hygiene, including using common weak passwords or reusing passwords. In fact, even Mark Zuckerberg is guilty of both a weak password and reusing it: a 2016 data leak revealed his “dadada” password in all of its cyber-insecure glory.

Security and prevention training for employees is more important than ever. Plan it early, often, and regularly.

Familiarize yourself with AI Cyber Security Tools 

AI isn’t always a bad thing, though. Just as it was originally developed to help people retain more security, there are still astounding AI cyber security tools that can help you fight against the increasing proliferation of cyber threats.

Sometimes, you have to use the same weapon as the attacker, and do your best to ensure that your security system is stronger than their code.

Deploy an Expert

Fighting against ever-evolving cyber threats is a full-time job. If your job title is anything other than “cyber security specialist,” you should consider outsourcing your cyber security to someone who knows what they’re doing, and has the knowledge and experience to keep your business safe.

GroupOne has a team of dedicated experts who are obsessed with code and maintaining their clients’ security. Click here to learn more about how GroupOne can help your business remain secure, while you focus on growth.