Machine Learning / Security / Contributed

The Possibilities of AI and Machine Learning for Cybersecurity

19 Mar 2019 9:33am, by

Juned Ghanchi
Juned Ghanchi is a co-founder and CMO at IndianAppDevelopers, a mobile development company which offers to hire app developers India for mobile solutions. Juned has 10 years of experience in online marketing, especially in the tech sector.

Whether you admit it or not, artificial intelligence (AI) is here to stay. As per the latest prediction, by 2020 a vast majority of software and app developers will use AI for their products and services. Obviously, the increased role of AI into software solutions will transform the way we work, live and do our businesses.

Just like its definitive role across all facets, AI will also play a significant role in transforming the cybersecurity for the better. AI can play a significant role in detecting and fighting the most recent and sophisticated types of cyber-attacks. As cyber threats are increasingly becoming sophisticated and complex, detecting them, and addressing them is proving to be an excellent challenge for any software and app development company. This is where the preemptive and visionary role of AI in detecting and predicting threats can play a significant role.

AI for Cybersecurity: the Promise and Challenges

While the experts are ready to consider Artificial Intelligence (AI) as the future of cybersecurity, it is essential to evaluate the promises against challenges posed by AI to become a key element in the scheme of things for internet security. Let’s admit here that in spite of all the advantages, AI offers considerable security threats for cyber systems as well.

The best thing about AI is that it can relentlessly decipher the user behavior, use patterns and all sorts of irregularities. By tracking and analyzing all these data and different patterns an AI-based system can quickly detect the cyber threats and vulnerabilities and can give timely alerts to stay safe and address them in time.

On the other hand, just because the automation supported by AI in spite of performing actions that are normally carried out by human intelligence, often remain vulnerable to malicious cyber programs that can imitate AI-based algorithms. A type of AI-powered security programs remaining engaged in its routine tasks of keeping checks and balances can suddenly be exposed by a more advanced hacking program based on machine learning.

But while promises and threats will continue to remain with AI-based security systems, none of them can actually completely outweigh the other. AI will continue to make important value additions by minimizing security tasks with high efficiency of fraud detection. But at the same time, it will continue to remain vulnerable to be exposed by more advanced and sophisticated hacking programs.

More Sophisticated and Complex Cyber Attacks

Every subsequent year is proving to be worse than the previous one in terms of cyber threats and vulnerabilities. Apart from a sharp increase in the instances of cyber-attacks, security threats are increasingly getting complex and multifaceted. In 2016 alone, around 357 million malware programs have been detected all over the globe.

In recent years, an increasing number of connected IoT devices have further contributed to the increase in the complexity it’s of cyber threats. The hacks are now increasingly getting complex and extremely mischievous that even intelligent security systems need to work extra hard for detecting and defusing.

How can AI help Companies Beating Cyber Offenders?

Intelligent systems powered by data-centric algorithms and latest technologies like machine learning can really enhance cybersecurity in multiple ways. Apart from saving a lot of resources, intelligent cybersecurity solutions are more proactive to respond instantly and prevent threats in real-time.

Both AI and machine learning technologies are all about learning about the user behavior patterns, typical signals and triggers and the potential deviations and the vulnerabilities. By detecting all these data, an intelligent cybersecurity system can proactively destroy a threat in its nascent its early stage or can safeguard the system from any potential data breaches or intrusions.

Taking Inspiration from Some AI Adopters in Cybersecurity

There is no dearth of examples of utilizing AI to strengthen cybersecurity. From major and world-famous applications to latest security systems, a plethora of services have been tremendously helped by AI-powered security solutions. Let’s have a look at some of them.

  • Gmail uses machine learning technology to filter emails and provide a safeguard from malicious emails.
  • Google also uses Deep Learning for its plethora of platforms and applications. Deep Learning which is a variant of machine learning can learn about the users in more depth and can help an app address proactively as per the data-driven insights.
  • IBM launched its Watson cognitive learning which extended the power of for machine learning for threat detection and cybersecurity purposes.
  • Balbix is a platform to offer solutions against data breaches and security breaches. It uses AI-powered risk predictions to prevent security threats in real time.

The Future of AI in Cybersecurity

The future of AI in cybersecurity looks to be very promising. But as we have explained, such promise is not to be seen without the accompanying risks. While we have already explained the opportunities, it is time to take a look at the key challenges and vulnerabilities.

First of all, the AI-powered systems are also being utilized by the cybercriminals and hackers, and this poses a high-security threat to machines and their data. When to save repetitive work and all the resources, we depend on AI-powered systems and undermine the combination of machines and human expertise, the automated security systems remain vulnerable to threats.

Conclusion

To answer it positively, yes cybersecurity solutions today are completely ready to meet the new technology demands and look forward to the latest technologies such as AI and machine learning. How the AI and machine learning can be used effectively to safeguard the data and processes, will decide their relevance in the future.

Feature image via Pixabay.

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