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You are here: Home / Security / Impact of Artificial Intelligence and Machine Learning on Cybersecurity
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Impact of Artificial Intelligence and Machine Learning on Cybersecurity

Technology experts are defining new concepts for putting efforts of security and intelligence service to counter threats using artificial intelligence and machine learning. The powerful combination of AI and ML is used as a defense to boost skills for countering cyber-attacks.

AI in cybersecurity

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AI has a very deep impact on cybersecurity technology; hence, the developers and companies are finding new ways to implement machine learning based functions in every software, platform and tool out there across the globe.

AI is applied to compute power, collect data and increase the storage capabilities which helps to exploit and analyze the weaknesses to help mitigate further attacks.

The security experts are shifting trends in cybersecurity technology to keep us all safer as a result of smarter computers.

1) Cloud Services

With the help of cloud computing, the businesses have shifted from large servers and equipment to cloud platforms like AWS and Microsoft Azure.

Companies have limited their pieces of hardware to worry less about the trust issues of storing all the critical data in the cloud but this can also generate a new range of potential threats and vulnerabilities.

The latest AI and machine learning systems are based on software algorithms making it easier for the companies to deploy them across their cloud infrastructure and services.

Some of the best antivirus tools are more relying on AI for scanning servers and search malware instances.

The software algorithms are smart enough to detect malicious software based on self-learning skills. Small and large businesses can secure their cloud environment to protect against the most typical means of malware penetration and so it is always advised to have top of the line security by your cloud provider.

2) Language Processing

There is always a downside to using smarter technologies. A question arises whether machine learning algorithms will become smart enough to eliminate the need for human input entirely?

This is not true as even most of the strongest AI cybersecurity tools require human world collaboration. Natural language processing and trend analysis are getting better by machine learning systems, yet, they require a human touch for better interpreting spoken and written text.

The deep learning methods have performed outstandingly in solving some challenging NLP problems by enabling the machines to understand an unstructured text.

NLP helps to classify and analyze web pages, emails and speech transcripts. The deep learning methods have performed outstandingly in solving some challenging NLP problems by enabling the machines to understand an unstructured text. NLP helps to classify and analyze web pages, emails and speech transcripts.

Predictive analysis helps to detect potential weak nodes in the network of unaware system users which can further train a neural to flag people who likely keep their password on a sticky note.

3) Recognition and Analyzes

Machine learning is all about taking data from the past and using it to your benefits in future and hence you cannot simply turn on an AI system and start expecting from it to add an extra layer of defense to your network and software.

Months and months of activity logs are fed into the AI algorithms at identifying anomalies and threats and achieving competence. It begins by setting a baseline of normal performance and further calculating new events by creating patterns which help the machine to recognize a hacker or a threat to the system.

AI tools are best at recognizing attacks from the scratch and send off alerts to the correct people at the time is of the essence when it comes to cybersecurity because the hackers are very fast to infiltrate a corporation’s system.

Takeaway

We can possibly conclude that there are many actions at which computers are better than humans. ML algorithms cannot detect anomalies perfectly and hence AI alone cannot detect an unusual cyber-attack. In general, humans should always be alerted during threat detection as you do not want any machine learning system to gain too much control over the decision-making process.

Nowadays, AI is already being incorporated into many security tools and solutions and becomes the new market standard. After all, AI is just a powerful tool used for both improving securities as well as boosting the crime. It varies from individual to individual who learns to use it better.

Author Bio:

Ella Adanet is a Business Consultant at Tatvasoft UK which is a big data company in London. She is passionate to learn new things always. Her focus is often in technology with a special interest in the area of the Asp .net, Big Data, and Java.

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Filed Under: Security

About Harris Andrea

Harris Andrea is an IT professional with more than 2 decades of experience in the technology field. He has worked in a diverse range of companies including software and systems integrators, computer networking firms etc. Currently he is employed in a large Internet Service Provider. He holds several professional certifications including Cisco CCNA, CCNP and EC-Council's CEH and ECSA security certifications. Harris is also the author of 2 technology books which are available at Amazon here.

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