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In this article, we’re going to discuss machine learning and artificial intelligence in cybersecurity. We’ll look at the benefits and challenges of AI, their role in cybersecurity, and how criminals can abuse this technology.
Cyberattacks have been rising in frequency and scale for a few years now. We saw a sharp jump since the start of the notorious pandemic.
With data security in more danger than ever, it’s no surprise that more and more companies are turning to artificial intelligence in the hope of getting more powerful digital protection from hackers, phishers, and other cyber criminals.
By the way, there is much more to AI than just the ability to enhance cybersecurity. Learn some curious facts about AI here
But first, what are the main benefits of artificial intelligence?
1. Applications and Uses of AI
As its very name suggests, artificial intelligence is the intelligence displayed by machines rather than by living creatures.
Machine learning is a subcategory of AI that identifies patterns and applies them in problem-solving. Currently, both AI and ML are successfully implemented in a variety of domains, including:
- Banking and Finance
- Real estate
- Retail and e-commerce
- Logistics and transportation
- Entertainment and gaming
- Digital marketing
- Software development
And finally, AI and machine learning can be indispensable in cybersecurity.
2. The Role of AI in Cybersecurity
AI can predict and ward off cyberattacks more accurately, since it can process enormous amounts of data fast.
Artificial intelligence enables modern businesses to replace traditional tools with more efficient solutions and thus boost their productivity. Thus, AI is reported to be quite effective in security awareness training.
AI solutions that have been developed with specific cyber security needs in mind can deploy more creative and time-saving techniques, which allows expediting the onboarding, on-job training, and mentoring process.
AI-powered tutors may successfully assume the role of mentors that automatically assign some tasks to beginner cyber security experts and keep tabs on their progress.
Thus, AI solutions free experienced practitioners from supervising and mentoring duties and allows focusing on other, more complex or important tasks.
Machine learning can be very effective against malware. It can scan massive databases of existing malicious software and block an attack, if a new, modified, version of it surfaces.
AI is also great at network monitoring. Machine learning can dictate user behaviors, and when something unexpected happens, flag it as a potential threat.
As you may know, artificial intelligence also shows a lot of promise in countering cyberterrorism. Today, governments, companies, and big corporations pin their hopes on AI.
AI techs are believed to be helpful in improving homeland security and states’ abilities to protect their citizen’s rights to privacy. What’s more, AI empowers dedicated agencies to analyze the activity of a broad section of population and identify potential hazards more promptly.
Recent developments in AI and machine learning have expanded the ability to conduct network surveillance without having to spend enormous resources. AI technologies are now widely used for conducting online surveillance, receiving, transmitting, and processing data over an IP network.
And the good news is that AI makes it possible to conduct surveillance without infringing on human rights to privacy and data protection.
AI allows encrypting video data and preventing data misuse.
AI also plays a significant role in biometric authentication, which can help eliminate the need for passwords. That can be good news, since a staggering 80% of data breaches are linked to weak and thus unreliable passwords.
Most importantly, AI-powered solutions can go a long way towards spotting and addressing threats as soon as they arise. Thus, AI enables cybersecurity experts to be proactive and employ the best methods available to neutralize a threat.
Furthermore, AI technologies can come in handy when it’s necessary to deal with critical vulnerabilities quicker. AI is 40% more effective when it comes to detecting weak points in applications, databases, etc.
And they are not just some ordinary bugs that may occasionally disrupt user experience and get in the way of installing a new feature update. We’re talking about exploitable vulnerabilities hackers may use to get access to users’ private information.
Still, with machine learning, it becomes much easier to teach systems how to effectively spot dangers, sift through malicious code line by line, and come up with workable solutions that can patch the system in a timely fashion.
3. Main Challenges of AI
Notwithstanding all the indisputable benefits AI brings to the cybersecurity industry, it should in no way be considered a panacea. AI isn’t necessarily the all-powerful solution to end cyberattacks all together. In fact, it poses challenges, too.
First all, it’s important to keep in mind that AI techs are not invincible. Some tasks performed by Ai can be manipulated if hackers manage to access them. For example, an AI-enabled program could be tricked into labeling malicious software or dangerous user behavior as safe or normal, or the other way around.
Biometric authentication, which is highly popular among users, can also prove to be dangerous. Biometric information in the wrong hands can be used for surveillance or other infringements of users’ privacy.
And unlike passwords, there is no way you can make any changes to your biometric data. This brings users to another problem. AI technology has enabled us to collect and process more data than ever before. As a result, it will probably cause further deterioration of digital privacy and security.
Another challenge that AI poses is how expensive it actually is to implement. Since a good deal of AI is still in its nascent stage of its development and is experimental, the cost associated with it may be too high for many businesses.
And what if criminals tap into the power of AI solutions? This will enable hackers to carry out bigger and more sophisticated attacks very quickly. Like network monitoring and learning patterns of user behavior, criminals can also apply machine learning to determine why certain cyberattacks have ended in failure and devise more powerful and effective attack models.
AI also can be used to create malware that resembles trusted software. It can be used to learn more about the target network’s patterns and execute dangerous attacks without ever being detected.
Hackers can also use AI for more powerful attacks with deep learning. When researchers provided AI with millions of leaked passwords and tasked it to generate new ones, the program had an alarming 24% success rate.
4. Ways to Improve on Security Measures
Those companies that aim to enhance their AI-based cybersecurity systems should invest enough time and effort in configuring a robust cybersecurity policy. It’s also essential to establish efficient network topography to manage all users’ networks more effectively.
This will also help cybersecurity experts to locate and troubleshoot issues faster. AI itself can be employed for devising effective cybersecurity strategies, policies, and documenting network traffic patterns.
Finally, to get the most out of the AI-powered systems and solutions, companies should take special care to hire only reputable and experienced software developers. There are tons of firms and individual developers that claim to be highly qualified and experienced in developing AI cybersecurity solutions, which makes it more difficult to choose a proper service.
Unless you have an established team of professionals, make sure to research all available options carefully and never leave your cybersecurity program development to chance.
Last, but not least, those companies and agencies that employ AI and ML techs should take care to constantly improve and update their existing solutions.
As with any technology, AI-powered solutions tend to become obsolete even faster than you might think. So, it’s critical to keep abreast of any changes that occur in the cybersecurity domain and implement fixes and updates in a timely manner.
So, will AI take over cybersecurity? It certainly will have a more prominent role in the digital security industry in the upcoming years. The AI market is poised to reach over $35 billion by 2026. And with it being as powerful and promising as it is, AI is becoming an integral part of the cybersecurity industry.
AI provided the cyber security sectors with the tools necessary to automate threat and data breach detection, predict and fend off malicious attacks within the shortest possible time. Developments in AI and in machine learning also help provide timely and more efficient training for beginner cybersecurity experts and allow veteran practitioners to focus on more important tasks.
Though relatively young, AI has already gone a long way towards enhancing cybersecurity. And there are more challenges to overcome and new heights to reach until this promising technology can finally unravel its full potential.
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