As businesses rely more and more on technology and have fully transitioned into the digital phase, cyber-security has become the topmost priority for all C-level executives. Data breaches are now more common than ever; more than 1.5 million records became a victim in January 2020 only.

A data breach can cause a massive blow to the reputation of the company regardless of the size and can have a significant impact on the bottom numbers at the end of the year.

Therefore, traditional cyber-security approaches are no longer sufficient enough to protect the integrity of an organization. Additional resources are required to protect and maintain a secure IT infrastructure for a digital transformation.

That is why all these organizations are now implementing Artificial Intelligence and Machine Learning to automate the process and generate predications to have better data analytics. A survey carried out by Forbes said that 48% of the organizations are looking to increase their Artificial Intelligence budget for Cyber Security by almost 29% in the present year.

Systems based on AI can enhance the abilities of the IT officers and implement better protection policies against cyber threats.

Artificial Intelligence and Machine Learning: The Market Development Aspect

With the digital transformation mentioned above, comes a range of connected devices, which offers convenience to customers, no doubt, but also brings along the risk of major cyber-attacks for enterprises of all sizes.

Both machine learning and artificial intelligence have been very popular with cybersecurity industries. However, the interesting part is that it is not only used for counter-attacks but, hackers themselves are using AI and ML for more sophisticated attack strategies.

This indicates that threat management including detection and response are very costly to implement. But at the same time, attacks using AI and Ml at an all-time high, cybercriminals employ malware and automated AI techniques to produce more sophisticated methods.

Therefore, it requires more advanced-level security practices and automated responses to combat the outbreaks.

AI and ML are now a part of all phases of Cybersecurity as they enable an enterprise to approach cyber defense in a smarter, proactive, and automated way. Cyber defense including threat prevention and protection, detection and hunting, and response can all benefit from machine learning.

Startups were initially more driven towards the AI-enabled security services, but many large IT entities have now ventured into the market as well.

The largest example of such is no other than Microsoft. For the new Windows 10, they have introduced Windows Defender Advanced Threat Protection (ATP) which works for preventive protection, breach detection, automated investigation, and response. It is custom built in the Windows 10 and has used multiple levels of machine learning and Azure cloud AI to identify vulnerabilities and threats.

Similarly, we all are familiar with the Blackberry Empire which was once the revolting technology in smartphones they now, however, produce and sell software to other large enterprises. One of their main products is a range of their cybersecurity solutions which are programmed with high-level Artificial Intelligence and Machine learning algorithms to prevent cyber threats and automate a client’s threat response.

The main issue that C level executives are now struggling with is the availability of professionals who are trained highly enough in AI and ML. However, if organizations provide the right education and spread awareness about easy cloud-based services such as Microsoft’s Azure App Service they can handle this situation to a greater extent.

Even courses that are marketed will prove to be an excellent source for AWS professionals who have cloud computing experience as they can easily transition and provide better cybersecurity for their company.

Key Trends for AI and ML in Cyber Security

Now is the perfect time to implement AI and ML to improve secure Cyber practices.

In 2020, CEOs can no longer ignore the power of an effective Cyber Security approach as it is no more a luxury to experiment upon but a need of the hour; in the Cisco report of 2018, they wrote that they blocked seven trillion threats on the behalf of their users.

Here are the most essential key trends that you must look out for in the present year.

Integrating AI-enabled abilities into existing security solutions to enhance cybersecurity and gain a competitive edge.

• Use resources to achieve a more holistic IT infrastructure and cyber-security framework, which ranges from threat detection to prevention and lastly to the response.
• Assist cybersecurity teams with different evaluations using false scenarios to further enhance a system and its reaction to defects.
• Educate your team on the importance of using automated systems and enunciate the need for incorporating AI and ML into your existing strategies.

Here are a few predictions for AI in cybersecurity in 2020:

• AI will not only assist in cybersecurity practices in 2020 but will also improve endpoint resiliency by the end of the year.
• Threat actors will leverage the power of AI algorithms to analyze an organization and in the process find out the weak and strong points and any vulnerabilities there might be.
• AI/ML organizations will seek out professionals with advance level capabilities to secure their operations.
• As cyber threats and cybersecurity evolve, AI will be put against AI.

Final Words

As Amy Lin once said, “Cybersecurity teams with less time and manpower investment and higher efficiency to identify the cybersecurity gaps.”

In the end, one must remember that even though the thought of AI and ML taking over Cyber Security is very tempting, there are a lot of things that need to be taken into consideration. While AI is making waves in cyber securities, the hackers also have access to the same AI technologies.

And just like pretty much everything else in the world, a powerful thing in the wrong hands can do much worse than good. That is why, in addition to employing cybersecurity and cloud-based systems such as Azure Security Apps an organization must train cloud and ML professionals to their maximum capacity to implement security systems that they can monitor at all times.

In summary, use Artificial Intelligence and Machine Learning to intensify humane efforts rather than replacing them completely. Enroll your employees to get Secure coding training and network security training from InfoSec Academy and prepare your cyber workforce against the criminals