AI in Cybersecurity : Pitting Algorithms vs Algorithms

AI-in-Cybersecurity-Pitting-Algorithms-vs-Algorithms

The Cure that is Artificial Intelligence 

AI in cybersecurity has been revolutionizing the way we view defending against dark hat hackers and penetrators that have malicious intent. That’s why it’s essential to have a dedicated approach when it comes to  cybersecurity. From a technology standpoint, it’s necessary to have a holistic approach, when companies understand what algorithms can be used where it creates for a more robust security eco-system.


“Even the largest security team comprised of the most skilled IT professionals can’t sift through the thousands of vulnerabilities to determine which to prioritise. Tools leveraging AI that continuously monitor all assets, proactively predict what vulnerabilities are most likely to be exploited and produce a prioritised list of fixes are entirely necessary to keep up with constantly evolving attack methods.” – Gaurav Banga, CEO and founder of Balbix


It’s important to understand how best to take counter-action measures so that any attack can be located and defended against at record time. Since timing the action is vital, companies need to extend their cyber protocols to ensure that there are no lapses in the measures taken. This happens in small to mid-size companies that focus on cybersecurity from a technology point of view. They don’t create a real value-centred where it can become a valuable resource for the organisation. They instead focus on building measures that revolve around engaging with hackers on a need-only basis.

That’s why algorithms are being designed that perfect the art of security. When cybersecurity is of the essence, it’s essential to have a more proactive role. Algorithms are the single tool that can enable companies to perform better in their cyber-security measures. Additionally, companies can also enhance their existing profiles by leveraging third-party players who can design great solutions for you. This shortens the protocol and enables leaner management of cybersecurity threats.

The evolving nature of Cybercrime

When it comes to cybersecurity, it is a rapidly expanding domain. This is because attacks are getting increasingly sophisticated with more hackers emerging from the roots. That’s why cybersecurity professionals need to have a deeper understanding of how cybersecurity evolves. Cybercrime is shifting towards new trends like crypto jacking and ransomware, with an increasingly alarming rate of expansion.

Cybercrimes have evolved to capturing data from a variety of sources and publishing information on the dark web. Some of the greatest tech companies of all time have been hacked, and countermeasures are being put into place every day. However, there needs to be a more holistic approach towards cybersecurity, which is what Artificial Intelligence in cybersecurity offers. While hackers use their algorithms to hack into systems, cybersecurity professionals use their own. That’s why the algorithm war is being waged with technology being used to its full potential.


“The stereotype of young guys in hoodies has been cast out for some time, but under-representation means the sector is still portrayed as a job for the boys. As just one example only 11% of the cybersecurity workforce are women. But are set to see the needle shift. From the language that determines what we consider to be ‘cybersecurity’ through to the numbers entering the profession, we will start to see more of ourselves engaged in, and reflected in, the cause to keep the digital realm trusted and safe.” – Lydia Ragoonanan, The Director of LORCA


Artificial Intelligence is also enabling technologists to have a more secure internet. A world where data is kept safe, and there are no leaks is a more positive force for business good. Societies can also be safer knowing that hackers aren’t penetrating systems that store sensitive information. Since information is a resource, companies need to employ the best in class, to ensure that there are no leaks or data gaps.

Better prediction through AI

It helps us make better predictions when it comes to crimes. This is a great tool to have as it allows us to find potential weak-spots within the cybersecurity domain. It also enables cyber-experts to plan their next move before an attack has taken place. There may also be day 0 attacks that are passive. These attacks can also be thwarted and removed from the system by running AI algorithms. Since the scale is massive and there are lots of end-points, it’s best to use an AI algorithm to ensure proper security.

Predictive analytics also helps us in gaining the legal perspective. It allows cybersecurity professionals to view hackers from a unique perspective. It brings a greater sense of platform-centric security to the area of cyber. It also allows us to explore new avenues of defending ourselves based on what predictions emerge from the AI model.

The AI, in turn, can also create better systems to actively scout for vulnerabilities. Hackers can be prevented from entering as more and more gateways are blocked-off. They can also maintain a steady resource stream of AI enabled products that will continue to perform the role of cybersecurity threat detection. The overall model becomes better over time, as the AI system learns from the data being presented.

Additionally, there is greater focus being given to the AI systems present within the platform. There is a stronger approach to enabling AI systems to express their reach fully. This gives them greater control over systems while allowing an automatic response after detection mechanism. In other words, the AI system can detect and respond to threats without needed intervention.

As the software becomes sophisticated, the scope of AI increases as well.

Enhancing the scope of AI in Cybersecurity

Companies need to explore the full potential of AI in their cybersecurity infrastructure. AI can enable better cybersecurity, with a stronger focus on outreach. Research indicates that 64% of alerts go unnoticed, and only 23% of companies respond only during a crisis. The nature of cybersecurity needs to evolve and create a more comprehensive approach to security management.

This also means that there needs to be a greater focus on AI in cybersecurity. BY introducing new tools and sophisticated algorithms, it’s going to be a battle of who has a broader reach. When AI can go through entire systems’ files and detect threats before they emerge, the whole ecosystem becomes that much more enhanced. Additionally, there is greater scope available to the teams at large, as AI is providing more information on a feedback basis.

There are more tools available to cyber-teams who can then feed in that data back into the AI algorithm. This strengthens the platform that much more and enables for greater Machine Learning integration. Currently, about 20% of C-suite executives are using ML to enhance their AI offering. That’s why there needs to be an enhancement of scope when it comes to AI and its reach. AI needs to have a broader range and a more coherent process when it comes to threat detection.


“To realise the full potential of AI, we must integrate its various forms to offset the limitations of each. No one approach will be sufficient because each approach is optimised for one specific set of problems at the expense of others.” – Scott Lathrop, Senior Researcher AI.


When it comes to the scope of AI, companies need to look at their existing systems. They need to analyze how ready they are when it comes to Artificial Intelligence and their cybersecurity measures. Added to that, there is a need for cybersecurity professionals to enhance the reach within each company. The company needs to become more activated when it comes to cybersecurity measures. It also needs to add more significant control over factors that go outside of cybersecurity.

AI in cyber policies

For the proper implementation of policies and AI enabled security measures, AI can also be used as a tool to form better regulations. The device can be used to enhance the scope of work of the AI platform and enforce stricter guidelines at the same time. When employees make a mistake or share a file that they’re not supposed to, the AI system automatically detects that as an anomaly and stops them from doing so.

This is a lesser talked about the function is the area of cyber-compliance. AI can be used as a tool to reinforce and dictate the terms through which companies can leverage their employee compliance. From using specific pathways to ensuring localised compliance, AI can enable companies to become safer from a non-technological way. They can also allow companies to create more value for their employees by making them more reliable. The safety net of AI and cyber-compliance enables employees to experiment more and create innovative solutions. This can aid in business development without seeing any hindrance from lengthy procedures and protocols. It can automatically detect when a mistake has been done and then attempts to fix it automatically.

This is also a more significant way for employees to know when they’ve made an error and attempted to fix the mistake at a faster rate. Cyber governance is an emerging field within the AI and cybersecurity space, with greater emphasis on covering the more substantial ground. All employees and end-points become activated and are more aware of the potential challenges in the domain.


“A big driver of customer adoption is the need for security and compliance solutions in an age of increasingly sophisticated cybersecurity threats, as well as complex information protection needs due to regulations like the GDPR. As we speak to customers about the future of work, we know security and compliance are some of the highest organisational priorities, and we hope these new offerings will help them achieve their security and compliance goals.” – Ron Markezich, Corp VP Microsoft.


AI can help in forming these cyber-policies and enforcing them from a technological standpoint. This takes human error out of the picture and creates a more robust platform for companies to review. AI dashboards can also be used to ensure that there are no gaps in the technology sphere. There are also areas where AI can enforce more significant control over specific models. This is where AI can indeed take over and develop innovative solutions.

Strengthening models of defense

The core need for is to improve the impact of cases that we have right now in the corporate field. We don’t have the sophisticated tools necessary to create better defence mechanisms for core products. From consumer data to lengthy procedures, the cost of cyber compliance rises daily. Companies must conform to cyber compliance laws and regulations that govern handling better data. That’s where the idea of using AI to fight hackers came from.

Hackers are using sophisticated technologies, but AI has ensured that the fight is meek. This is because AI is being used continuously to strengthen all areas of the business. When businesses are readier to fight at scale, they are better prepared across all corners. Usually, it takes one legacy computer or one insecure network to allow hackers to gain entry. This is the reason why this is so helpful. Technology can be executed and revived without needing much enhancement, with cybersecurity platforms being developed each year.

Strengthening core models also relies on enhancing the technology itself. This means that technology has to get more sophisticated and advanced to keep up with changing needs. AI can be repeatedly iterated upon, but a concrete solutions model must be designed to keep the system current. There are various consultants and third-party integrations that allow for greater reach in the AI domain, but it’s essential to have a coherent approach to AI in cyber.

Additionally, companies need to understand the value that AI can bring to the table. That’s when they start to strengthen existing resources to enable a more robust environment. AI in cyber is essential to execute correctly, as the reach must be congruent with the overall goals of the organization. AI shouldn’t be seen as a fit-and-forget model. It needs to have an overarching goal that companies need to fulfil.

  • Cloud, VPN, and AI cybersecurity

With the rise in cloud adoption over many years, there have been new challenges emerging in the AI cybersecurity space. More companies are launching new tools to create better solutions to enable greater communication. Cloud has been a single platform that has changed how we perceive networking and technology, with AI the following suit. This has led to an increase in the adoption of additional technologies such as VPNs and Machine Learning. AI, in this new domain, must remain one step ahead of the hackers so that it can protect emerging technologies and platforms.

From a cloud perspective, the level of inter-connectivity is incredible. There are more devices connected to the cloud than ever before, making the job of cybersecurity that much more difficult. This has led to an inevitable rise in the adoption of AI and made cybersecurity scalable across the cloud. The cloud is also made more secure when AI is a safety net for all transactions and data servers. At the end-point, there can be increased protection along with more security for third-party and vendors.

VPNs are also designed to be a layer of protection when it comes to anonymity and remains protected. However, as the rise of VPN continues, there is a greater need for cybersecurity as well. As more users deploy VPNs, they become increasingly at risk for hackers to take advantage of. This can lead to more problems emerging while depending on the VPN tunnel to stay encrypted and secure.

  • AI to research hacking behavior

A more comprehensive approach would be to enforce AI  across the board. Companies can remain stress-free as the AI technology enables for greater security. The technology can also access platforms across the network and ensure that they’re well protected. The core dashboard can provide all the necessary information needed, which ultimately leads to a more coherent platform. Cyber compliance officers can govern the domain with an increasing sense of confidence in the technology offering.

AI cybersecurity also offers a unique approach to the domain. While many companies are building better algorithms, a handful of them is deconstructing hackers’ attempts. They’re using AI as a form of research to uncover how and why sure pirates get away. They can also use AI to design better traps and testing mechanisms for hackers to take the bait. They can then study the attempt from a more technical level and uncover new insights that they may have missed. AI experts can then design better security measures after thoroughly analyzing how hackers got away with the information stored.

Using AI in the research space helps to strengthen certain areas as well. Companies can run audits to ensure that their organization is protected from all intrusion, and then design solutions that can keep them protected. This is a great way to ensure that all corrective measures are being put in place, especially when it comes to compliance with all regulations. Cybersecurity can be strengthened when companies invest in AI research.

Conclusion

AI in cybersecurity is an emerging concept that is being redefined by algorithms. Companies are pushing to create the most comprehensive tool to defend against hackers. From spyware to trojans, there is a dire need for more proactive scanning and protecting. Otherwise, companies are on the backfoot when it comes to defending against these attempts.

Additionally, there is a massive scope in the extension of AI to enter newer domains. Using Machine Learning and Big Data, AI is opening up borders for extending the range for what cybersecurity officers can do with the given resources. From talent to technology, there are many areas where AI can enable cybersecurity officers to enhance their reach.