The Natural Language Processing is increasingly used in the understanding and processing of unstructured data generated nowadays. Whether it is used in analytics or generative tasks, its capabilities may be equally used by cybercriminals and security defense tools. The discussion will be around why NLP approaches will increase in performing activities such as: information gathering, impersonation, domain classification, source code vulnerability analysis, phishing, malware family analysis, security incident and event management, security orchestration. We will see some market examples, and discuss why NLP is a driver for automation of security activities.
Key takeaways for delegates attending your session:
1. Deep learning algorithms are the main driver of NLP increase in cybersecurity given the unstructured nature of any information corpus
2. The usage of deep learning for NLP lexical parsing provides the capability to analyse corpuses with non-standard languages, such as binary files, or source codes
3. NLP is a very useful tool to use in the coordination of detection, investigation and response given its capabilities to both analyse and generate information
