Latest technologies in AI like Explainable AI, behaviour analysis, & smart malware detection can make cyberspace a little easy]
“Starter Kit”
Justina Alexandra Save published a report in Statista. As per the report, AI in cybersecurity was worth $10 billion in 2020. The number will reach $46.3 billion by 2027. As the culture of AI continues to grow, it will become increasingly vital in the field of cybersecurity. If your company wants to be successful in today’s world, it might need to invest in AI in cybersecurity.
AI & Cybersecurity
In an age where cybersecurity is an undeniable priority, AI technology is a must-have for any company looking to protect its data/processes/systems or all of them.
- Cybersecurity operations like monitoring, troubleshooting, & other protective measures are often done manually. This eats up a lot of time & effort delaying remediation activities. Further exposing the system & its adversaries.
- These manual processes, if automated by AI solutions, can transform cyber workflows into streamlined processes & speedy remediation. By automating key elements of labour-extensive activities. AI can serve a broad range of organisations.
- These approaches are necessary. In fact, unavoidable. Especially when it comes to the defence departments or system security of a nation.
Emerging trends in AI & cyberspace- The next big thing:
AI has yet a long way to go in developing skillsets like creativity and “outside the box” thinking that are required for hacking humans.
But they do have some skills that humans do not have. Let’s take a very basic characteristic of AI i.e., processing large amounts of data in seconds instead of days or weeks – which is helpful when dealing with cyber threats.
- With the extensive growth in AI-ML applications, Explainable Cyber AI is popping up. The Explainable Cyber AI would work on the concept of Explainable AI or XAI.
- As the name suggests, the XAI basically explains the “why” behind a software breach. This would allow your team to continuous improvement to cybersecurity life. The Security Operations Centres (SOCs) have these crucial insights about your software or systems.
- Behaviour analysis examples for AI are growing in IoT & in Operational Technology (OT). Especially in device & network security issues. Researchers are already applying AI/ML to learn behavior’s of simple operational technology.
- Besides, Neuromorphic computing is another tastiest term in AI-backed cybersecurity. It’s a new approach to give AI the processing power that mimics the neural structure of a human brain.
- Also, companies are partnering with globally renowned academia to develop advanced malware detection mechanisms.
This would include the latest neurotrophic computing chipsets.
Is AI-integrated Cybersecurity the future?
AI is changing the way we see cybersecurity. AI-powered algorithms are capable of analysing data and identifying patterns as well as malicious activities that might have been impossible to predict.
- AI is also being implemented in cybersecurity tools, such as behaviour-based prevention systems and anomaly detection systems.
- AI has proved itself as a powerful ally when it comes to recognizing and defending against cyber threats.
- Yet this same challenge means that AI’s opinion has a much better chance of finding what humans cannot see.
So, now we must see the benefits of AI in Cybersecurity
As reported in Statista, 80% of telecommunication leaders believed that they won’t be able to conquer their system security issues without AI. The survey was conducted in 2019. Here you can guess the percentage in 2022
- Automated detection and classification of malware samples are crucial. AI’s cyber applications detect this malware with other nuanced attacks. And help businesses & government officials protect people, and organizations to keep up their public decorum.
- This further fertilizes your brand recognition & trust in system security & protocols.
- Automated vulnerability identification and mitigation help you to work on remediation & enhanced incident response.
- The automated system will save a lot of & labour in detecting & responding. Thus, helping analysts to mitigate the thing.
- Also, the time saved here can then be invested in high-level discussions to reach the purpose for which you are working.
- Threat modelling using automated analysis tools, such as machine learning or artificial neural networks i.e., neuromorphic computing approach.
- AI is meeting the needs of advanced security systems. And redefining security strategies rather. Its use cases have minimised human error & inconsistency.
- Cybersecurity leaders are themselves exploring the AI use cases to broaden its impact & efficiency. And through autonomous systems, AI is giving a competitive edge in the market.
The Bottom Line
AI is expanding its own arena of helping businesses through innovative solutions, processing, & automation of course!
Want to learn the Echelon Edge approach to conquer cyber threats through creative AI strategies? Click here to know the scene.