Cybersecurity

NLP for Cybersecurity: Detecting Threats and Protecting Data

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The increase of cybercrime has been dramatic over the past decade with more cybercriminals able to access private information and data using different technologies and techniques. This makes it such a challenge to fight against these cyber threats or cybersecurity, as there seem to be so many different utilities at criminals’ disposal.

However, there have been big developments in cybersecurity with artificial intelligence (AI) playing a huge role in attempting to halt these cyber attacks. Natural language processing (NLP) is one piece of AI that has been used recently to combat attempts to steal personal data. NLP for cybersecurity allows security professionals to analyse vital information from textual data that can bolster a business’s cybersecurity.

Further advancements in NLP technology should eventually see the near elimination of cyberattacks, as more cybersecurity mechanisms are being created every day. With that being said, let’s explore some of the ways that NLP is benefitting cybersecurity and helps prevent future cyberattacks for good.

Key Components of NLP

Before diving into how NLP cybersecurity can be used to protect data from cyber threats, it is essential to have a basic understanding of the technology. Let’s look at a few of these essential NLP cybersecurity components and how they are used to analyse data:

  • Tokenization: Analysing data is the future of performance and efficiency. When NLP cybersecurity is broken down into smaller pieces of information, it can be useful when dealing with large databases, as it can be split into smaller parts.
  • Named Entity Recognition (NER): This is a form of categorisation analysis by looking at information such as names, locations and organisations. It can help with finding out which pieces of information are relevant.
  • Sentiment Analysis: Every piece of textual data has an emotional tone that is being expressed. It can identify threats that are hidden behind different layers of language.
  • Topic Modelling: Topics and themes can be picked out from a collection of documents. This can be used to identify trends or continuous discussions related to security threats.
  • Part-of-Speech (POS) Tagging: This assigns grammatical tags to words in a sentence or paragraph. It can help with understanding the syntactic structure of the text and can detect any suspicious patterns.

How NLP Cybersecurity is Used

Threat Intelligence

Analysing data from a wider range of sources can help with gathering more useful textual data that will help combat cyber attacks. NLP can identify patterns and extract all the relevant information from news articles, social media, forums and IoT (Internet of Things) to offer the best analysis possible. This can help with monitoring any potential threats to an individual’s or business’s private data and allow for better planning to help stop future attacks, which is why it is now used in technology like blockchain.

Phishing Detection

Both phishing emails and websites are some of the most popular cyber attacks that are being carried out by criminals looking to steal private information. NLP cybersecurity can be used to identify these phishing attempts by analysing emails and websites that contain words that are associated with phishing attempts. The technology can then identify if something seems suspicious and will recommend that you avoid it by alerting you of the issue.

Anomaly Identification

Being able to spot any anomalies in communication patterns can play a big part in helping prevent cyber attacks. Cybercriminals will often carry out bank scams to steal private information and assets from their victims. Banks follow strict communication protocols when talking with customers and to prevent any cyber threats, NLP cybersecurity can detect if there are any anomalies in these communications. For example, if there are any typos or grammatical errors that are out of the ordinary, this form of AI can pick them out and alert you if it’s considered suspicious.

Incident Recovery

If you have fallen victim to a cyber attack, you need to respond quickly to fully recover. NLP helps dramatically with the forensic analysis process to track down and identify any crucial information that can be used to help respond to a cyber attack. It can dig through logs, incident reports and transcripts of communication to locate anything that can stop you from being victimised in the future.

Challenges of NLP in Cyber Threat Intelligence

While NLP cybersecurity models have a plethora of positives in regards to detecting threats and protecting data, it’s important to remember that they are AI so their intelligence derives completely from people training the data. Due to cybercriminals being very persistent with trying to retrieve the data that they want, it means that NLP models must be updated regularly to ensure that they stay ahead of any potential threats. This means that they will require human interference every so often to help with these updates.

NLP cybersecurity systems and chatbots can also be used by cybercriminals to instantly create human-like text and use that to send several phishing emails to victims in a much shorter time frame. This makes technology like ChatGPT beneficial to scammers almost as much as normal users. Alternatively, these scammers have the potential to create their own chatbots that trick users into exposing personal information. You can check the legitimacy of any chatbot online, so that you can keep safe from this.

Businesses will need to ensure that all of their employees are clued up to NLP and how it is used in cybersecurity, so that their guard is raised when it comes to cyber attacks. This can be time consuming and give workforces less time to complete day-to-day tasks, such as collecting overdue debt from customers. In this instance, having credit insurance in place will protect you.

Conclusion

The emergence of NLP has offered hope in counteracting the threats caused by cyberattacks like phishing emails and bank scams. Analysing textual data and picking out the key information and anomalies can help individuals and businesses be notified of anything that is considered to be suspicious. These pieces of information are often overlooked by individuals who are not aware of the existing cyber threats, so these AI technologies can be very beneficial to them.

NLP cybersecurity technology has the ability to drastically change the cybersecurity scene, and this will become more and more evident as it develops over the coming years. It presents a viable option for protecting our virtual environment and building a safer place where our assets are kept out of the hands of hackers. Essentially, the possibilities are endless.

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