Technology has changed the way we perceive things and work. It has made things possible which were inconceivable a century ago. Tedious tasks that seemed tiresome and no one wanted to be the one doing it, are now piece of cake. Huge amount of data now can be processed, stored and analyzed through the use of latest innovations. But like any new invention and innovation, the facilities do come with their own sets of problems. (Dickson, 2016)
With so much data being processed and floating on Internet, makes it almost impossible to keep an eye on every megabyte that pass their way. It is therefore, highly likely that potential threat pass their radar unnoticed. Cyber security has become a major headache for the companies and this problem cannot be tackled by just hiring cyber security experts due to the magnitude of problem. (Dickson, 2016)
Just as machines were invented for assisting us and sharing our burden, cyber experts are trying to apply the same philosophy to counter ever growing cyber threats which till now, have caused huge data and economic loss to individuals and companies. They are trying to counter these threats by forming a combination of machines equipped with artificial intelligence and human analysts going by the name – Centaur threat analysts. (Truvé, 2016)
Centaur threat analysts are a part of new phenomenon called machine learning that has become talk of Silicon Town. Just like many other jobs taken over by machines and robots, cyber security becoming part of the bandwagon is not inconceivable notion anymore. In fact, it is now being discussed and is source of heated debates. And now this has become a hot commodity that every tech firm and security retailers are looking forward to get their hands on. (Dickson, 2016)
What is Machine Learning?
It refers to the system that is capable to improve with experience automatically. That is how our brain is wired by nature. But to expect our computer software or Brower to do the same thing; is a little far-fetched. No matter how many times you open the same site, your computer software won’t know by itself that it should open it on auto as you always open it. Here is where machine learning comes into picture. With it, our computer software can become smart enough to learn from previous experience and predict your future behavior and also make a guess for new scenarios and which course of action it should take. (Kanal, 2017)
Machine Learning and building future Cyber Security system
The multitude of cyber-attacks in today’s world can be gauged by example of Singapore where in 2016, 550 Ransomware-related attacks were experienced per day. So, it is a huge task at hand and cannot be handled by cyber experts alone. So the induction of Machine learning and AI is a welcome notion in dealing with cyber security.(Machine Learning will Transform Cybersecurity, 2016)
Machine Learning can perform the job of detecting possible cyber-attack by inducing algorithms into analytical programs to observe routine day to day operation from different angles. The machine learning process will trigger an alert for any extraordinary activity going on and prompt the company to take necessary action. Machine learning and AI are ideal solution to handling and managing of big data and is best solution for risk detection. (Burry, 2017)
Machine Learning systems are found to be more accurate than human factors. Machine learning systems are improved over a period of time. One of the major factors that played in this improvement is the shortage of human talent pool for the job of cyber security analysts. (Wolff, 2017)Huge amount of data being transmitted through IoTs alone makes it impossible to process and analyze every byte. So the introduction of Machine Learning and AI is more than welcome in the realm of Cyber security.
The artificial perception is just in place to detect and determine whether the incoming messages are potential threat to the recipient system; and if it finds it so, it label it to be problematic and alert the receiving system to take corrective actions. The corrective actions always need human intervention and it is the duty of professionals to eliminate security blind spots by established effective counter actions that will keep the malicious entities in check. Cyber-crimes cannot be curbed completely but using Machine Learning and Artificial Perception can keep us vigilant to prepare for remedial actions. (Jakobsson, 2017)
Machine Learning will Transform Cybersecurity. (2016, December 20). Retrieved August 09, 2017, from GovTech Singapore: https://www.tech.gov.sg/TechNews/Opinions/2016/12/Machine-Learning-will-transform-Cybersecurity
Burry, J. (2017, June 08). Big Data, Machine learning and AI – a Perfect Combo for Cyber Security. Retrieved August 09, 2017, from Spinbackup: https://spinbackup.com/blog/big-data-machine-learning-and-ai-a-perfect-combo-for-cyber-security/
Dickson, B. (2016, July 01). Exploiting machine learning in Cybersecurity. Retrieved August 09, 2017, from Tech Crunch: https://techcrunch.com/2016/07/01/exploiting-machine-learning-in-cybersecurity/
Jakobsson, M. (2017, July 24). Endpoint Protection: Spotting te Cyber Wolf in Seep’s Cloting. Retrieved August 09, 2017, from Securityweek: http://www.securityweek.com/endpoint-protection-spotting-cyber-wolf-sheeps-clothing
Kanal, E. (2017, June 05). Machine Learning in cyber security. Retrieved August 09, 2017, from SEI Insights: https://insights.sei.cmu.edu/sei_blog/2017/06/machine-learning-in-cybersecurity.html
Truvé, S. (2016, December 08). Threats of Tomorrow: Using AI to Predict Malicious Infrastructure Activity. Retrieved August 09, 2017, from Recorded Future: https://www.recordedfuture.com/artificial-intelligence-cyber-defense/
Wolff, M. (2017). Applying Macine Learning to Advance Cyber Security Analytics. Retrieved August 09, 2017, from Cyber Security Review: http://www.cybersecurity-review.com/industry-perspective/applying-machine-learning-to-advance-cyber-security-analytics/
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