Artificial Intelligence (AI) and Machine Learning have almost become the common buzzwords in the tech world. The implications of these technologies on every aspect of digital applications, services and solutions is huge. Most notably, they have now become part of the technologies used to improve cybersecurity measures and techniques.
While AI is all about mimicking human intelligence in performing many tasks, Machine Learning is more about learning from the user behaviour and accordingly providing solutions befitting to the context and requirements. In all regards, AI and machine learning for apps and security systems are here only to extend the capabilities of the machines by incorporating certain aspects of human intelligence. For fraud detection, preventing malware attacks and ensuring optimum data security, they can really play a huge role.
But the question is, whether these technologies have still become well equipped enough to deal with the most formidable security challenges. Well, as both of these technologies are still at their nascent state, they still need to evolve and improve to fit into the needs of modern IT security. Here through the length of this post we are going to explain the promises of these technologies for cybersecurity.
AI for Cybersecurity: Promise vs Challenges
When most IT experts and cybersecurity strategists consider AI to be the most promising technology for the future of cybersecurity, we need to evaluate and measure these promises against the challenges they offer. In spite of the formidable role AI plays for the security systems of our time, they also pose significant security threats as well. The security threats posed by the AI powered systems and algorithms often make security experts to approach these solutions with caution and apprehensions.
The ultimate reason for which AI is looked upon as a forward-looking technology is that it helps deciphering the user behaviour patterns and anomalies on a continuous basis. By simply allowing the security algorithms and systems to analyse user behaviour data and insights, AI and Machine Learning helps taking preventive measures to combat the security threats and vulnerabilities. By detecting threats and deciphering threat signals in real time AI based security systems can provide timely alerts to mitigate security loopholes and threats.
Another important aspect of utilising AI for cybersecurity is the way it allows automation. For the vast majority of day to day activities that cybersecurity experts need to carry out, there is little or no need of any human intelligence or creative output. These actions are often repetitive and doesn’t require any human understanding. This is exactly where AI can boost efficiency and productivity of a security system by taking care of all these tasks that are needed to be taken care of.
In spite of all these positive factors, AI systems at the same time remain vulnerable to security glitches and threats. When AI based solutions are utilised by the hackers or the intruder computer programs, the threats are likely to be more proactive, robust and continuous in nature. Since, AI and Machine Learning algorithms can always be utilised by the malicious cyber programs and security systems alike, the challenges always remain in balance with the promises.
AI and Machine Learning for Cloud Infrastructure
We all know that enterprise systems largely have shifted to cloud and thus has been proved as a blessing for the companies. Nobody can be doubtful about the benefits of cloud computing such as unrestricted access to data and applications irrespective of locations and devices, real time collaboration with remote teams, non-local data storage creating more space and flexibility, etc. But at the same time, cloud computing because of the excessive dependence on network for accessing data also made data vulnerable to security threats and breaches.
Now, AI and Machine Learning solutions developed and deployed for cloud systems can address these security threats and vulnerabilities in a more proactive manner. A Machine Learning systems working within the cloud infrastructure can constantly update the security measures and the database of security vulnerabilities so that any new threat can be quickly detected and addressed without the slightest delay.
How can AI help Companies Beating Cyber Offenders?
As of now, we have only focused on the gross role of AI and Machine Learning in improving cybersecurity measures. Now, we need to get closer and look at the specific ways AI based cybersecurity solutions can deal with threats.
Primarily, the AI based security systems focus on improving the database of security threats and vulnerabilities to take on evolving threats. Secondly, the AI based security systems constantly learn about the user behaviour patterns, anomalies in user behaviour and the signals and triggers associated with the security threat perception.
Real Life Instances of AI in Cybersecurity
Through some years, AI and Machine Learning have been deployed and put to use for a variety of cybersecurity measures and tasks. From globally popular applications to the latest security solutions and services, AI has played a great role in modern security solutions across different contexts. Let’s have a look at some noteworthy examples.
- Gmail now incorporated machine learning for filtering malicious emails to prevent cyber threats to penetrate into the systems of the users.
- Google now makes use of Deep Learning which is a variable of Machine Learning for vast majority of apps and platforms. Google uses this technology for its services to learn about security threats in depth.
- IBM with the Watson cognitive learning uses the machine learning technology for detecting cybersecurity threats and vulnerabilities.
- Balbix has emerged as a popular platform to prevent data and security breaches through AI-powered real-time risk prediction capabilities.
In the end, though the entire picture of AI for cybersecurity is not as rosy as it is popularly perceived, there are tremendous promise for these technologies to play a vital role in security systems and solutions. Though still now the importance of human security experts in any system remains unquestionable, AI and Machine Learning are likely to make security measures and tools more dynamic and proactive.
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