cybersecurity

How AI and automation are creating a future with smarter cybersecurity

While cyberspace has made the globe smaller, it has also exposed us to never-before-seen influences that are both diverse and difficult. However, the hacking world has grown at the same rate as security. Furthermore, reports suggest that there has been a 300% increase in cybercrimes with the onset of the pandemic. What is more alarming than this is that more than 77% of companies do not have a cybersecurity incident response plan in place? What is cybersecurity and why is it necessary? Cybersecurity refers to the collection of methodologies, technologies, and procedures used to shield the integrity and availability of computer networks and data against cyber-attacks or unauthorized access.

The necessity of cybersecurity continues to expand as the number of individuals, devices, and programmes in the contemporary organization grow, laterally through the rising deluge of data, most of which is sensitive or secret. The major problem is aggravated by the rising extent and intricacy of cyber attackers and attack tactics. With each day, the number and sophistication of cyberattacks increases. The best solution to navigate through this scenario is relying on automation to enable faster prevention while reducing the volume of threats.

Why is Cybersecurity Automation Important?

As the type and scope of cyber attacks grow, the existing traditional techniques are struggling to detect threats and malware. Cybercriminals are always coming up with new and more sophisticated techniques to get around access restrictions, firewalls, and highly protected networks. The only way to prevent these assaults is to be better prepared than the hackers themselves.

Under-resourced security systems significantly benefit from AI by staying ahead of the threats. The scope of current cybersecurity solutions can be extended to pave the path for the creation of new, stronger ones using AI. Let’s take a look at some of the benefits of integrating AI into cybersecurity.

  • Data Management: The availability of data at every phase of consumer engagement is increasing due to developing technologies. With the rapid collection, monitoring, and study of data, AI applications in cybersecurity play a critical role in data security, accuracy, and abuse prevention.
  • Threat Detection: Threats and other potentially harmful actions could also be detected using AI. Traditional systems are not capable of keeping up with the massive number of viruses produced each month, and hence AI would be of great help. Biometric logins, for example, are used to grant secure access by scanning impressions, retinas, or palm prints. For extra security, they are also being utilized in smartphones these days. Face recognition software, for example, is being utilized to provide security using AI technology. These programmes are especially important on social media platforms since they allow users to stay longer on the platform. For sophisticated cyberattacks, AI-based detection and response systems can assist an organization to improve its threat detection and response capabilities. They assist in the fight against data theft, advanced targeted assaults, ransomware, malware, social engineering, and encrypted attacks.
  • Real-time Authentication: Various degrees of authentication rights exist for different users inside an organization, which are also dependent on the location from which they access the data. When artificial intelligence is applied, the authentication framework may become much more dynamic and real-time, modifying access rights grounded on the user’s network and location. Multi-factor authentication gathers information about a user to analyze their behavior and determine their access rights.
  • Phishing Prevention: Phishing is one of the most common cyber-attacks used by hackers to steal login credentials or infect computers with malware. Artificial intelligence can greatly aid in the recognition and inhibition of phishing attempts. The most prevalent phishing sources may be detected by AI and reported to the system so that defences may be prepared. Moreover, within seconds, AI can also tell the difference between a phony and a real website. It may also evaluate phishing patterns based on a user’s geographic location.
  • Continuous Monitoring: Many critical data centre activities, such as backup power, cooling filters, power consumption, internal temperatures, and bandwidth utilization, may be optimized and monitored with AI. AI’s calculative abilities and continuous evaluation of skills reveal which values would increase the efficiency and security of hardware and infrastructure. Furthermore, AI can lower the cost of hardware maintenance by informing you when the equipment needs to be repaired.

The Limitations of Integrating AI into Cybersecurity

The advantages that we had discussed above are only a small part of AI’s potential in cybersecurity. However, the discussion about AI and cybersecurity automation would be incomplete without talking about the three main drawbacks that are keeping AI from being a widely utilized tool in the sector.

  • Companies would need a massive number of resources, like memory, data, and processing power, to create and operate an AI system. Furthermore, because AI systems are developed by learning data sets, cybersecurity organizations must get a wide range of various data sets containing malware, non-malicious codes, and abnormalities. Obtaining all of these precise data sets might take a long time and need a lot of resources, which some businesses cannot afford.
  • Another disadvantage is that hackers may use AI to test, develop, and upgrade their malware in order to make it AI-proof. In reality, AI-proof malware may be highly damaging since it can learn from existing AI tools and build more complex assaults to breach standard cybersecurity programmes or even AI-enhanced systems.
  • The AI-based security systems are continuously being improved by developers. AI algorithms require a significant amount of time to grow and learn about dangers and how to respond to them. An AI system that isn’t well-developed can be useless and provide a lot of false-positive findings.

Now that we have discussed the limitations of integrating AI into cybersecurity, we have to keep in mind that the pros definitely outweigh the cons. The best way to counteract cyber threats and enhance security is by evolving and becoming smarter using AI.

The Future of AI in Cybersecurity

It is evident that artificial intelligence techniques can be used in a variety of ways in cybersecurity. It is possible that considerable investments and effort would be necessary to deploy the entire suite of instruments. However, since not all software is equally susceptible and interacts with sensitive data “on all fronts,” only a few systems in the world require a full security stack. As a result, each case should be assessed separately to find the most effective defensive solutions that provide dependable data protection at a low cost. Sustainable, adaptive, flexible, and long-lasting cybersecurity solutions need rigorous analysis and study so that an owner does not pay more than what is necessary to safeguard data in the future. The total cost for cybercrime is predicted to reach $6 trillion in 2021, and any organization that values its data will have to consider upgrading and automating its technologies to meet the security demands of today’s world. Thus, it is safe to say that the role of artificial intelligence and automation in cybersecurity is unquestionable.

By Krishnan Jayaraman, Vice President and Business Head – Data Analytics and RPA, Aspire Systems

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