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The world is becoming digitalised at a rapidly fast pace, and this change is going to become even faster in the future. The digitalisation means that everything is moving at a quick speed. This includes things such as businesses, new products and trends. The user gets whatever they want immediately because the service provider has various means to deliver it.

As the benefits and conveniences of this digital age are numerous, it also brings with it several negativities too. One of the most noteworthy and destructive threats it often poses is that our private and sensitive information is at risk like never before. Cyberattacks are very pervasive and affect almost every business, individual, and government bodies alike. 

We all are moving towards an age where cybercriminals can often reach their targets in any part of the world at any time. The dire need for cybersecurity has never been more crucial than as of now. 

How is AI a benefit to cybersecurity?

Though the future seems unwelcoming, there have also been advancements and innovations in technology with significant impacts on cybersecurity. One such game-changer in the cybersecurity industry is tools and techniques developed and supported by both Artificial Intelligence and Machine Learning as its subset.

Artificial Intelligence is not a buzzword in today’s world and is being used widely in several industries. It is also playing a prominent role in the ongoing fight against cybercrime. A frequently overlooked aspect of AI in the context of cybersecurity is that it has to be machine learning, which has to turn the input it receives into algorithms that allow business organizations to learn how to react and respond to different cybersecurity threats.

One of the most significant advantages offered by the perspective provided by ML is that it dramatically improves and enhances the steps companies and enterprises take to recognize any malicious programs and vectors present within the cybersecurity infrastructure.

Following on from this, highlighted below are some of the ways AI and ML are making a difference by giving the much-needed boost to cybersecurity.  

Machine Learning in the detection of cyber threat 

Organizations now can detect a cyber-attack in advance to be able to prevent whatever the attackers are trying to achieve. Machine Learning is a part of Artificial Intelligence, which has proven to be very useful when it comes to identifying cyber threats based on analyzing data and determining a risk before it exploits a vulnerability within your information system.

Machine Learning also enables the computer system to use and adapt algorithms based on the data received, learning from it, and later understanding the continuous improvements required. In other words, it also means that ML is enabling the systems to predict threats and observe any differences with a lot more accuracy than any human can do.

Traditional technology often relies too much on past data and cannot improvise in the way that AI can. Conventional technology can’t keep up with the new mechanisms and tricks often used by hackers as the way AI can. Moreover, the vast volume of cyber threats people have to deal with daily is too much for humans and is best dealt with AI.

Network Security and Artificial Intelligence

With the help of AI, companies now rely on a signature-based approach. This means that the cybersecurity team employs a signature-based approach that targets even the smallest hint of any malicious programs, and then later proceeds to extract some unique fingerprints for every individual threat identified. After the detection process, the IT team is tasked with monitoring all the devices on the network and ensures that the marked signatures do not appear again. 

Behavioural Analytics and AI:

Another significant advancement of security by AI comes from its behavioural analytics ability. It means that the ML algorithms can learn and make a pattern of your behaviour by analyzing how you use your devices and other online platforms. The details can also include everything from your typical login timings and IP address to your typing and scrolling patterns. 

At any time, the AI algorithms notice some unusual happenings or any activities that fall unfamiliar from your standard patterns; it can flag it as being done by some suspicious user or even block the user. Another way to stay secure is to mask your IP address as then no one will be able to keep snooping eyes on your activities.

The events that tick off the AI algorithms can be anything from large online purchases shipped to an address other than yours, a sudden spike while downloading the document from archived folders, or a sudden change in your typing speed.

AI & ML in Phishing Detection and Control

Phishing is the most popular method used by attackers. In this method, hackers try to deliver malicious links. The phishing emails are incredibly prevalent as one in every 99 emails is a phishing attack. However, AI and MI play a leading role in identifying and controlling the phishing attack.

The innovative technology can detect and track more than 10,000 active phishing sources and later respond and remediate much quicker than humans can. Moreover, AI and ML work at scanning phishing threats from all over the world as there are no constraints of its understanding of phishing campaigns to any specific geographical area. Also, AI has made it possible to differentiate between a fake website and a legal one very quickly.

How can AI be integrated into cybersecurity?

With an AI-centric approach to cybersecurity, understanding the fundamental functioning behind the cybersecurity tools being used is easier since the process of how an AI program works to come up with cybersecurity solutions can be divided into four steps, which are as follows:

  • Learn: The AI software helps to propagate security by learning and analyzing tons of structured and unstructured data sources or inputs. AI software then expands its understanding of the threats and cybersecurity risks facing the organizations.
  • Reason: After the process of learning, the AI software begins the process of reasoning. It means that based on the insights that AI has gained, it starts to join the dots and start making connections between the unsolicited IP address, internal threats, and malicious bugs.
  • Augment: In this process, the AI software performs a holistic analysis of all the threats and risks facing the organization. The entire analysis enables the organization’s security team to eliminate useless tasks and saves unnecessary expenses on safety in places where it is not needed. Also, the cybersecurity experts can identify the abnormal behaviours better by cross-checking the threat with the data stored on their systems.
  • Authorize: After finishing the process of learning, reasoning, and augmenting, the software takes the user to the level of authorization. Instead of depending on a single approach of password authentication, the AI software analyzes the keys used to access the network along the way the keys are being entered, among all other factors.
Cybersecurity smartphone | Photo: Biljana Jovanovic via Pixabay

Cybersecurity smartphone | Photo: Biljana Jovanovic via Pixabay

As technology is developing and progressing day by day, criminals are also improving their methods, tactics, and techniques to exploit individuals and organizations. AI-ML is used to detect and control the attacks before it can take place. As AI will see more and more advancement, we are going to witness how far we can secure this technology to promote advances in cybersecurity and threat analytics.

Now you are aware of Artificial Intelligence in cybersecurity, why not install anti-virus software to protect against future personal attacks? 

Author Bio: Rebecca James is an enthusiastic cybersecurity journalist, a creative team leader and editor of PrivacyCrypts. You can find Rebecca on Twitter.

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