What is Cyber Security?
Cyber Security basically means to protect computing systems, programs, and networks from digital or cyber-attacks. Cyber attackers attack networks and systems to obtain sensitive information or to destroy information, illegally extort money, access or change information, and interrupt regular business operations among many other reasons.
Cyber-attacks are also carried out to gather crucial confidential information. To secure business operations from cyber-attacks is of utmost importance as cyber-attacks may cause heavy damages to operations and businesses. The implementation of cybersecurity is getting tougher by the day as in today’s day and age we have more devices connected to the internet than people. Hackers and cyber-attackers now have enhanced skills with emerging technologies and are getting smarter by the day.
Zen Monks and Cyber Security
Have you heard of the concept ‘Koan’? Well, ‘Koan’ is a tool that zen monks used to reach enlightenment. The monks used this tool for many years and these Koans are referred to as riddles that need to be solved by letting go of existing beliefs. If you are thinking about how is ‘koan’ related to cybersecurity, read this blog to find out how.
Artificial Intelligence and Deep Learning are the buzz words and these technologies are omnipresent everywhere. Many cybersecurity professionals believe that these innovative technologies are the magic potion required to solve cybersecurity challenges. However, similar to the concept of ‘Koan’ deep learning or any other forms of machine learning is just a tool and not a solution to cybersecurity issues.
AI & Machine Learning in Cyber Security
To broadly understand the application of artificial intelligence in cybersecurity, we have to understand that the main goal is the application of machine learning to solve cybersecurity issues. The application of machine learning to date is limited to identify anomalies. To explain this further, for instance, experts are now using machine learning to detect malicious intentions, behaviour, malware, potential attacks, and hack attempts. The challenge however lies in defining the anomalies and to do so you need to define what could possibly qualify or an anomaly and what is normal. Commonly, nowadays our laptops are connected to multiple networks and any common download could trigger malware in our system.
Machine Learning implementations in cybersecurity challenges can be classified into two scenarios- one where machine learning has made changes and shown results and the other case in which machine learning has been applied but has not shown any improvements or results. Also, it is more likely to not yield any productive output in the future as well.
Machine learning applications can be further divided into two categories – supervised machine learning and unsupervised machine learning. The former category of supervised machine learning algorithms has massive impacts on cybersecurity issues. Supervised application of machine learning proved to be useful and detect cyber threats and malware. The latter category of unsupervised machine learning is where we do not have any useful results. Unsupervised Machine learning uses association rule learning and dimensionality reduction as the primary approaches to analyze huge datasets. However, these algorithms have shown limited results in identifying or detecting cybersecurity threats.
Similar to the concept of Zen Koans, machine learning, and AI is just a tool to reach the desired goal. These tools require the correct knowledge on how to use them and accurate application to bring permanent solutions to cybersecurity challenges.
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