Combining artificial intelligence and cybersecurity creates an optimised and effective process for eliminating outsider threats. However, failing to properly understand how to implement AI with cybersecurity procedures could lead to disastrous results, such as poor data quality, false positives, and exploitation by malicious users.
To properly use AI security, one has to be aware of the delicate balance between overdependence and using it as a support.
Additionally, hiring AI cybersecurity specialists who know how to implement it properly is an important step.
But before you begin the process of mixing AI and cybersecurity, you should first know what they are, how these two programs can benefit you, and how they relate to one another.
What is AI?
Artificial intelligence (AI) is the technology that allows machines to mimic human comprehension. It has been around since the 1950s and has since evolved into the Generative AI we know today.
As of the 2020s, the AI threat of job displacement and intellectual property has caused a worldwide debate on its ethical practice. However, AI doesn’t just create images, texts, and sounds like generative AI.
Machine learning and deep learning-predecessors of generative AI-are also well-known branches of artificial intelligence that remain widely used today. This is because generative AI is impossible without being built through these two branches.
Machine learning is a process of letting a machine learn patterns through historical data. Meanwhile, deep learning enhances machine learning by mimicking human brain function more precisely than machine learning does. Both types of AI use popular algorithms, such as the neural network, interconnected nodes that take inspiration from the human brain.
AI’s evolution has helped shape and improve the quality of our technology. It can now be seen in our recruitment teams, marketing, content creation, our own coding, and even in healthcare. So it makes sense that cybersecurity would also be supported by this revolutionary invention.
What is Cybersecurity?
Anything connected to the internet requires cybersecurity, especially private data. Why? Because cybercriminals are very good at taking important documents of individuals and using them for ransomware, identity theft, and more.
How cybercriminals do this isn’t just one method. As technology continues to escalate and change, so do the criminals on how they achieve unauthorised access to data centers and systems. Blocking their movements and alerting the owners of the data being accessed is the main goal of cybersecurity.
However, being complacent with your cybersecurity procedures will lead to these criminals overtaking your security systems faster than anyone else. Incorporate artificial intelligence and cybersecurity together to remain up-to-date on the best ways to protect your private data.
Cybersecurity VS AI
There’s an ongoing debate on the overdependence of artificial intelligence. Because of this, many consider AI as a separate entity that could cause disruption within their workforce and processes.
The good news is that there is no need to worry about any cybersecurity vs artificial intelligence concerns. This is because AI should be considered as another technological application that functions as a tool rather than a replacement. Depending on how effectively one uses this tool, there could be more benefits provided in comparison to how others handle it.
Artificial Intelligence in Cybersecurity
There are multiple ways to incorporate AI in cybersecurity practices. By implementing these AI models into your cybersecurity process, you could achieve a more optimised and foolproof security system for your sensitive data, regardless of the nature of your business.
Fraud Detection
Fraud detection is a popular choice for incorporating artificial intelligence and cybersecurity. The goal of AI fraud detection is to identify fraudulent activities, possibly prevent them, or at best mitigate the damages they have caused.
The AI involved in fraud detection is mostly machine learning models that are trained to identify which activity is done by an actual user and which is an attempt to incite damages.
Anti-Phishing
The popularity of phishing as a cybersecurity threat remains at an all-time high. The goal of phishing is to receive private information from the victim by pretending to be a reputable business that can give them specific rewards or contact information.
To prevent phishing, email security combined with AI can identify malicious messages through specific indicators. In other words, the AI within the email security system can analyse all the content and context of emails to sort the phishing ones, the legitimate ones, and the malicious ones.
Password Protection
Infiltrating through the use of passwords is a common concern for many. Thanks to the development of artificial intelligence, security has evolved to using AI-powered tools. These tools are used by organisations to distinguish genuine and fraudulent logins.
Examples of these tools are CAPTCHA, which requests users to identify random objects or type in codes shown by the application.
Passwordless logins are now growing increasingly popular, with facial recognition and fingerprints being a form of login instead of written to ensure that the user signing in is the actual owner of the account.
Behavioural Analytics
With behavioral analytics, organizations can identify evolving threats and known vulnerabilities. Traditional security defenses rely on attack signatures and indicators of compromise (IOCs) to discover threats. However, with the thousands of new attacks that cyber criminals launch every year, this approach is not practical.
Organizations can implement behavioral analytics to enhance their threat-hunting processes. It uses AI models to develop profiles of the applications deployed on their networks and process vast volumes of device and user data. Incoming data can then be analyzed against those profiles to prevent potentially malicious activity.
Security Network
Network security is a heavily loaded process that requires a total understanding of the network’s topography and the creation of specific policies. With these policies in place, the organisation can identify connections to its server between those who may have malicious intent.
AI enhances the security network by providing the best policies and workloads after a significant amount of time learning the network’s traffic patterns.
Should You Use Artificial Intelligence for Cybersecurity?
Artificial intelligence in security systems can open doors for better identification, prevention, and risk mitigation. As cybercriminals become more advanced in their methods to maliciously intercept private information, it is our responsibility as businesses and organisations to safeguard the trusted data clients and individuals provide for personalised services.
Using the best technology introduced to the public for cybersecurity is never a bad thing. However, lack of awareness regarding the tools being used is. We recommend utilising artificial intelligence and cybersecurity hand-in-hand only if you have the proper knowledge of what these tools can provide you with the security you need.
Conclusion
Introduction to artificial intelligence and cybersecurity is one thing–applying them is another. If you find yourself interested in implementing cybersecurity programs powered by AI for your business, why not get specialists to do the job?
We can help you advance your cybersecurity with AI today. Contact Flexisource IT for a free consultation and a browse through our talent pool, who are cybersecurity specialists.
