Artificial intelligence is here to… No, not to steal your job but rather to make it easier and its – results more impressive, at least, concerning cybersecurity services. If properly harnessed and used, the power of AI and machine learning can significantly improve the levels of software protection.
AI for cybersecurity is quite a theme to discuss and imagine things about. In this article, we will scratch the surface of the topic to get that essential understanding of the matter; we will examine how and for what purposes people use AI and machine learning; we will learn about the benefits and challenges that AI poses.
Artificial Intelligence in Cyber Security
Currently, AI is not almost omnipotent, in terms of problem solving, program, but a highly-specialized algorithm, which sometimes is capable of learning (machine learning), and thus can improve incredibly fast in their specific task if given the proper environment. Thus, a properly-adjusted AI can do wonders in the narrow field for which it was created. Considering that the modern cybersecurity threats as well as people who pose and create said threats become more sophisticated and resourceful in their methods of undermining cyber defenses and getting hold of sensitive data, people who responsible for data protection should use any tools and instruments that can improve cybersecurity. Using AI to combat cybercrime proves to be a viable and effective solution.
What exactly does AI in cybersecurity do?
Well, some of the most prevalent applications include:
Some of that biometric verification stuff, such as a face or fingerprint recognition, runs on some kind of machine learning algorithm to grant a ‘pixel-precise’ accuracy and decrease the probability of mismatch. It’s expected that these algorithms will become more intricate and accurate because passwords aren’t the most reliable way of protection considering that people rarely create truly complex passwords. Let’s face it those will be very difficult to remember and very easy to forget.
Regression is a complex process, which when distilled to its core is about analyzing correlations between different datasets and estimating whether relations between them are present. Regression can be used to detect activity that shouldn’t be present in the system. Good AI can handle regression fast and furiously.
Clustering is about finding similarities between datasets, grouping information based on found similarities, identifying discrepancies, inconsistencies, et cetera. Again, AI can handle clustering quickly and efficiently.
It’s an extremely useful and multipurpose machine learning algorithm, which can classify different files and datasets based on previous observations. Afterward, the AI can put a label on those data, i.e. malware, ransomware, non-executable file, etc.
There’s no shortage of letters from people who do their best to act natural and innocent and ask for your money coming up with a whole range of unbelievable and imaginative reasons. AI can analyze the letters and determine the ones that were born out of malicious intent. Phishing monitoring can decrease the load on a corporate email and decrease the probability of some sincere and trusting soul falling victim to fraud.
Analytics of behavior
It’s perhaps the most complex and promising artificial intelligence for cybersecurity solution on this list. Such an AI can analyze the behavior and actions of a user in an app or website to detect strange or malicious activity. Analysis of behavior also raises some legality of artificial intelligence in cybersecurity issues as it touches the matter of personally identifiable information.
Mobile devices security analysis
As mobile becomes the primary way of going online, the necessity to closely monitor mobile endpoints becomes more relevant. AI applications in mobile cover a wide range of fronts, such as network connections, applications, and unique mobile device threats.
Benefits of Artificial Intelligence in Cyber Security
The effect that AI has on the cybersecurity field is quite significant (on both sides of the equation through — defending and attacking one). Whether it’s people who want to сarry through a cyber attack or deflect one, AI can be handy to both. Therefore, whether the effect of AI on security is positive rather than negative depends on which side implements AI better.
If cybersecurity professionals are well-versed at AI, then the software they’re protecting will have:
Better vulnerability management
It’s much easier to determine, prioritize, and address weak points in the system with nice AI in hand. Unlike previously, when it was quite difficult to determine a vulnerability until it was exploited, now, AI can help to determine weaknesses before the system’s security was undermined.
Not all attempts on the defenses of software are easily identifiable. In fact, only around 90% of threats are being caught, which reduces the security potential of a system. Each unidentified threat is a possible security breach, which can cause hefty financial and reputational damages. AI can make the number of identified threats much higher.
Better overall security
Regression. clustering, classification, data analysis, phishing monitoring, and other neat processes performed at AI-possible speeds are quite a combination. With such equipment, any system is quite an impenetrable fortress. A cybersecurity professional who has all the insights driven by AI at his or her hand can do wonders and craft truly remarkable defenses.
Challenges of Artificial Intelligence in Cyber Security
The world of artificial intelligence and cybersecurity is sweet and promising. However, as it often happens sweet and promising things have quite an assortment of challenges to offer.
The technology is young and fresh. It still has a long way to go and a lot of challenges to endure. Finding cybersecurity-AI professionals is also quite a task because of it and the overall difficulty of the field.
Advancements in artificial intelligence and cybersecurity are constantly advancing (the pun intended). Staying on top of everything is quite a challenge for cybersecurity professionals, though a rewarding one.
Cybercriminals can use AI too. AI doesn’t discriminate. If you can have it, people with not so good intentions can have it too. As we mentioned, it boils down to who uses it better.
Investments. Nice cybersecurity is quite an expensive and fancy thing; nice AI-powered cybersecurity — is even more so. To find that golden middle ground where the price to quality ratio will be optimal, requires additional research and analysis of each particular case.
If you have to do it yourself, training AI can be a hustle. You need plenty of specific datasets, quite some time, and computational power, so the machine can learn how to do its job properly. Obtaining such datasets can be a challenging task.
As you see, the use of artificial intelligence tools in cybersecurity is diverse and promising. Though to implement all the array of instruments, significant investments and time may be required. However, very few systems in the world need a full stack of defenses as not all software is threatened equally, and not all software actually deals with sensitive data ‘on all fronts.’ Therefore, every case should be considered separately to determine the most optimal defense solutions that would grant robust protection of data for a justified price. Sustainable, adaptable, flexible, and lasting cybersecurity solutions require careful analysis and research, so in the future, an owner won’t pay more than he or she should pay to have the data secured.
If you are in doubt, regarding the cybersecurity of your system, Kindgeek experts can offer you comprehensive consultancy services or help you build a well-protected system from scratch. Our experience in security-heavy industries, such as FinTech, HealthCare, and eCommerce makes us a great fit for projects that deal with sensitive data and call for complex security and architectural solutions.