What Is Deep Learning Software And How Can It Help Data Scientists?

Deep learning is the most advanced subset of artificial intelligence. It is also identified as deep neural networks because it takes inspiration from the working of the human brain. The deep learning software ensures that it gets better every time more data is fed into the machine because it can intuitively understand the meaning of new data. It is currently being observed that deep learning is also being applied to AI cybersecurity for predicting and preventing threats known and unknown in zero time before they can occur and cause any damages. The local market is flooded with solutions that protect and respond while waiting for the execution of the attack before they react. The prevention centric approach which has been developed keeps customers protected while dramatically reducing costs at the same time.

The use of AI deep learning technology is offering a predictive threat prevention platform. The multilayer protection provides pre-execution, on execution, and post-execution which is helpful to users and individuals. The methodology used includes a prevention first approach followed by detection and response, automatic analysis and ultimate remediation. This comprehensive approach can be used against any known or unknown threats from any file or file-less attack.

A dramatic increase has been observed in the past few years in the number of infosec vendors. Despite the expectation that the security landscape would improve it has diminished in quality and is presently in a bad condition. Nearly 66% of enterprise players have faced problems of some kind of a threat last year by way of attacks which originated on the endpoint according to a survey conducted by the Pokémon Institute. The report also provided evidence that a 20% year on year increase was being observed in the attacks.

The Pokémon Institute provided a list of the costs associated with each successful attack which increased by 42% year on year with attacks on small and medium-sized businesses costing around $7,120,000 or nearly 2 times the cost per endpoint for large organizations. This was in conditions when a major portion of the respondents estimated that the existing antivirus platform is only effective in blocking 43% of the attacks. The reason for this is because the solutions were only effective against existing malware. The report also highlighted that the biggest threat organizations faced came from zero-day and file-less attacks.

Many reasons have been attributed to this phenomenon but the two main causes are that more than 350,000 machines generated new malware is being released every day making it almost impossible to have an effective solution because security vendors are not accustomed to offering actual security. They are just in the business of selling data management solutions, business intelligence suite’s, methods to analyze data, and various post-execution and post-infection management solutions which is certainly not what security should be all about.

In real-life situations, businesses may encounter circumstances where they may want to prevent things from happening. They may prefer to have a wall to prevent an intruder from getting in rather than having an alarm go off after it is too late. A similar concept must also be applied to cybersecurity. Prevention was the concept of cybersecurity in its primary stages in the form of perimeter security and antivirus programs. However, these solutions will simply about prevention for not letting improper things to happen or enter.

Deep learning in cybersecurity is the most important technology which is currently available. Deep learning has revolutionized practically every field it has been applied to. It is equipped with advanced artificial intelligence and computer science and is motivated by a prevention first approach because the solutions for prevention are the future of cybersecurity. Real-time prevention requires producing high detection rates and low false positives. Real-time prevention with the use of deep learning in AI cybersecurity is specifically designed to secure any type of device and operating system along with any file type. Therefore the present-day real-time technology is essentially a cybersecurity solution which must be implemented for staying a step ahead of the next breach.

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