How AI can help predict cyber-attacks?

Today, when you look around the living style of a modern man which is dominated by live streaming, smartphones, and social networks, it reminds of the technology-based shows telecasted on the Discovery channel. It has predicted that the era of the 21st century will be furnished with flying cars and airborne robots will be part of our daily lives. 

(Image Credits: Insights)

Currently, we are the midst of the 4th industrial revolution, and technology is evolving even faster. Similarly, as the past industrial revolutions that saw the widespread adoption of out-sized numbers of world-beating technologies, the current revolution of technology is about to bring incredible benefits and tremendous risks too. Let us give this new revolution the name of “technology tsunami”. Why so? Because current is the era of digitization and globalization and as it is increasing enormously like a tsunami.

Capgemini said, “69% of enterprises believe that AI will be necessary to respond to cyber-attacks!

Cyber-attacks are designed to be hidden but Artificial Intelligence acts as a shield and it is responsible for the prediction of 85% of cyber-attacks. AI has shaken the cybersecurity business with its shocking shield measures, client security protection and reaction at a quicker rate. On the other hand, programmers are giving the tough test by utilizing the AI (or man-made brainpower) for network breach.

Natural Language Processing

You might have seen the text translators or similar apps in your smartphones or simply you must have used Google Translate website on the web. Did you ever think how the human-written text is recognized and translated in the desired language in just a few seconds? Yes, this is because of Artificial Intelligence. NLP is used in data recognition and text conversion.

To give you some notable examples:

  • Google Translate goes through 100 billion words per day.
  • Facebook uses machine translation to translate text in posts and comments automatically, in order to break language barriers and allow people around the world to communicate with each other.
  • eBay uses Machine Translation tech to enable cross-border trade and connect buyers and sellers around the world.
  • Microsoft brings AI-powered translation to end-users and developers on Android, iOS, and Amazon Fire, whether or not they have access to the Internet.
  • Systran became the 1st software provider to launch a Neural Machine Translation engine in more than 30 languages back in 2016.

Text Analysis

Investigative discovery: Distinguish examples and signs in emails or composed reports to help recognize and solve violations.

Subject-matter expertise: Arrange content into important subjects so you can make a move and find trends.

Social media analytics: Track awareness and feeling about explicit points and recognize key influencers.

Quicker attacks with more powerful outcomes

The present most refined assaults require talented professionals to direct research on their objective and distinguish people of intrigue, comprehend their social network and see after some time how they communicate with digital platforms.

Not exclusively will AI-driven attacks be substantially more custom-fitted and therefore progressively successful, their capability to comprehend means will be significantly harder to identify. Conventional security controls will be weak against this new danger, as they can just spot unsurprising, pre-displayed action. Artificial intelligence is continually advancing and will turn out to be perpetually resistant to the arrangement of dangers that remains to the legacy security approaches.

Sentiment Analysis

The classification of the sentiment of a text, comment, or article is a challenging task even for a real human. This is where NLP comes into the picture. A sentiment analysis model of NLP can tell us what kind of polarity a text has- very positive, positive, neutral, negative, very negative. You might be familiar with the below Facebook reactions!

With the use of sentiment analysis, we can classify things like the reviews of our company or its products. Another use of sentiment analysis is to poll people’s opinions based on their comments and social media posts.

Customer Service Automation

The above screenshot of client support automation given by DigitalGenius is somewhat unique in relation to the reply bot. It utilizes their restrictive NLP and AI to produce answers to generate answers and naturally fill case information. Those with certainty appraisals observed above—are automated, while the rest get sent to a human operator. This sort of automated help saves money for organizations. It additionally speeds up to help clients, who leave feeling more satisfied.

Recognition has started already!

AI is well and truly placed to bridge the gap between the massive amount of data being generated on a daily basis and the limited cognitive capacity of the human mind. From the most cutting-edge applications to simple tasks, AI has unlimited potential to turn data and processes from burden to boon. Remember, AI can play its own game and as due to the advancement of technology, the time is now! Happy reading!

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