Ever since its inception during the 1950s, artificial intelligence has made tremendous progress in every industry.
Artificial intelligence made its first step when Alan Turing introduced the Turing test in 1950. Later on, with the development of Eliza, Shakey, Roomba, Siri and Alexa, AI turned from fiction to reality.
Tons of research and development through the years has also led to artificial intelligence finding its place in cybersecurity. Artificial intelligence and cybersecurity together form a perfect combo for the detection of cyber attacks and harmful trespasses.
Living in an age of “big data” and the transition to modern web applications has provided enormous resources virtually, that could attract the attention of so-called "bad guys". So it is necessary to secure data in an efficient way.
Artificial intelligence promises to be a great solution for this.
AI-driven systems can ensure more accuracy and can cope up with the time consuming manual security testing procedures.
What we do at Beagle security encompasses the use of this “intelligence” in order to develop a system that can provide better results with reduced false positives and increased accuracy.
Using AI allows us to actively test through the application response, query strings passed in the URL, error messages and HTTP headers, etc.
We use a model that combs through data and detects suspicious activity by clustering the data into meaningful patterns using unsupervised machine-learning and on confirmation from the human analysts, builds a supervised model.
Using this model we are able to develop an efficient security testing system.
It is true that the potentiality of artificial intelligence can develop sophisticated systems but it must also cope with the complications allied with the emerging technologies.
A more detailed version on how learning models can be used in security testing published at https://blog.beaglesecurity.com/blogs/2020/05/26/Artificial-Intelligence-in-Cyber-Security.html
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