How is AI revolutionising the cybersecurity industry?
Do you know that every time you connect to the internet from a computer, tablet or smartphone, you run the risk of a cyber-attack? Imagine this risk being multiplied by several hundred in case of large IT companies. Every year, the IT industry loses close to $600 billion as a result of cybercrimes or leaks in cybersecurity.
With every tech expert defining what is artificial intelligence and AI becoming the buzzword in every industry, the cybersecurity industry is also catching up with AI by integrating it in the development of top-notch security products. Features of artificial intelligence such as machine learning are redefining the way security networks detect malware and eliminate them.
This blog can satiate your curiosity on what is involved in cybersecurity and how AI is being integrated in the cybersecurity industry and help you understand its significance. Let’s begin.
The present state of cybersecurity
Today, companies place an emphasis on the security of their internal network. If hackers manage to infiltrate that layer of their infrastructure, it is only a matter of time before a tiny breach becomes a full-scale attack. Hence the development of different types of cyber-security measures is advancing at a tremendous pace.
The most common tactic for network protection is a firewall. Firewalls can exist either as a software tool or a hardware device that is physically connected to the network. In either scenario, the firewall's job is to track what network connections are allowed on which ports and block all other requests.
In an instance where a hacker has circumvented the firewall and network security, a company's next line of defence is antivirus tools that are designed to scan hardware for malicious code. The goal is to remove the malware before it can spread to other machines and spawn a form of attack like ransomware.
How can AI be utilised in the cybersecurity industry?
The field of AI is still evolving, and all of the possible applications of AI and ML in the cybersecurity space haven’t been developed or explored yet. However, here are some types of artificial intelligence-based systems can help in defending computers and networks.
- Automated network analysis: Network analysis is a perfect fit for machine learning systems, due to the sheer volume of available data that requires analysis. Most malware and cyber attackers operate over security networks; hence monitoring network communications is a good way to detect attempted installations of malware. AI systems can help in easy detection of malware in any network. They can also accomplish network analysis faster than manual systems.
- Email scamming: One of the biggest threats to organisational cybersecurity is phishing. Adversaries have discovered that it’s much easier to get a human to click on a link than to discover and exploit a zero-day or unpatched software in your system. Detecting and blocking these malicious emails is an extremely active area of research in cyber security.
Machine learning and AI-based algorithms are active in detecting phishing emails at all levels. Some anti-phishing programs perform deep link inspection, simulating clicks on all links in the email and examining the resulting pages for signs of phishing.
- Anti-virus programmes: The issue with conventional security approaches to antivirus detection is that it results in delays, scalability and applicability of the protection often too late. In the cyber world, split seconds make all the difference. Most antivirus programmes lag in detecting the malware, generating a protection web and deploying it. By that time, the malware accesses sensitive data and leaks it to the cybercriminal.
Antivirus systems using AI focus on detecting unusual behaviour by programs rather than matching signatures. Since most malware is designed to do things that are different from the standard operation of the computer, they can be detected based on these actions. This allows these AI-based systems to detect zero-day exploits and other previously unknown malware.
- End of passwords: The majority of internet users create their passwords for each website or service that they subscribe to online. This system can be frustrating to maintain as well as vulnerable to attack if you rely on simple passwords or use the same one for multiple sites.
AI tracks every user within an organization based on roles, privileges, and common actions. Any deviation from the norm is flagged and require the person to use a second form of authentication, such as biometrics that scan fingerprints or facial features.
How AI is shaping the future of the industry?
The majority of cybersecurity tools require human interaction or configuration at some level. For example, a person from the IT team has to set the firewall policies and backup schedules and then ensure that they are running successfully. The advancement of AI changes the whole equation.
In the future, companies will be able to rely on smart tools to handle the bulk of event monitoring and incident response. The next generation of firewalls will have machine learning technology built into them, allowing the software to recognize patterns in web requests and automatically block those that could be a threat.
The natural language capabilities of AI also play a huge role in the future of cybersecurity tools. By scanning large portions of data across the internet, AI systems can learn how cyberattacks originate and suggest solutions for decision makers within the organisation. This can save the organisation millions of dollars in losses of data.
To help integrate AI in cybersecurity systems, AI specialists must know the intricacies of cybersecurity networks and appliances. They must become familiar with the potential sources of data breaches to stop them in the first place. To do this, they can either pursue a course on the subject or gain an extensive experience by working in the domain.
If you too are interested in the applications of AI in cybersecurity and want to contribute in the field, the diploma in cybersecurity specialist co-op from the Toronto School of Management can be a good choice for you. The course allows you to gain work experience as a part of the programme to obtain a first-hand insight in the cybersecurity field. So don’t wait to start your career in AI integrated cybersecurity and click here to know more about the course.