In recent years, the technology that exploits HPC (High Performance Computing) has evolved enormously, including previously unexpected fields, with the development of artificial intelligence to support cybersecurity.
The enormous rapid calculation capacity has made many technological developments possible, giving an economic and innovative boost worldwide.
The turning point: machine learning and deep learning
But the turning point is machine learning (ML) which, with the use of software for detecting potential illegal activities, encodes what characterizes a threat by learning to recognize it. Deep learning is therefore an effective method for detecting cybersecurity problems. Deep learning techniques, in fact, can efficiently process a large amount of information present in cybersecurity datasets, resisting attacks.
Read also the interview with the team of Deep Instinct, the solution that uses deep learning as a tool to prevent, anticipate and counter potential new malicious threats.
Learning over a period of time allows deep learning systems to achieve ever more accurate performance, thanks to the creation of a neural network that simulates the behavior of the human brain in analytical learning. ML techniques can be used to analyze variants and attribute them to the right malware family, and spam and phishing detection includes a wide range of techniques designed to reduce the waste of time and the potential risk caused by unwanted emails.