There is currently a big debate raging about whether Artificial Intelligence (AI) is a good or bad thing in terms of its impact on human life. With more and more enterprises using AI for their needs, it’s time to analyze the possible impacts of the implementation of AI in the cyber security field.
The positive uses of AI for cyber security
Biometric logins are increasingly being used to create secure logins by either scanning fingerprints, retinas, or palm prints. This can be used alone or in conjunction with a password and is already being used in most new smartphones. Large companies have been the victims of security breaches which compromised email addresses, personal information, and passwords. Cyber security experts have reiterated on multiple occasions that passwords are extremely vulnerable to cuber attacks, compromising personal information, credit card information, and social security numbers. These are all reasons why biometric logins are a positive AI contribution to cyber security.
AI can also be used to detect threats and other potentially malicious activities. Conventional systems simply cannot keep up with the sheer number of malware that is created every month, so this is a potential area for AI to step in and address this problem. Cyber security companies are teaching AI systems to detect viruses and malware by using complex algorithms so AI can then run pattern recognition in software. AI systems can be trained to identify even the smallest behaviors of ransomware and malware attacks before it enters the system and then isolate them from that system. They can also use predictive functions that surpass the speed of traditional approaches.
Systems that run on AI unlock potential for natural language processing which collects information automatically by combing through articles, news, and studies on cyber threats. This information can give insight into anomalies, cyber attacks, and prevention strategies. This allows cyber security firms to stay updated on the latest risks and time frames and build responsive strategies to keep organizations protected.
AI systems can also be used in situations of multi-factor authentication to provide access to their users. Different users of a company have different levels of authentication privileges which also depend on the location from which they’re accessing the data. When AI is used, the authentication framework can be a lot more dynamic and real-time and it can modify access privileges based on the network and location of the user. Multi-factor authentication collects user information to understand the behavior of this person and make a determination about the user’s access privileges.
To use AI to its fullest capabilities, it’s important that it’s implemented by the right cyber security firms who are familiar with its functioning. Whereas in the past, malware attacks could occur without leaving any indication on which weakness it exploited, AI can step in to protect the cyber security firms and their clients from attacks even when there are multiple skilled attacks occurring.
Drawbacks and limitations of using AI for cyber security
The benefits outlined above are just a fraction of the potential of AI in helping cyber security, but there are also limitations which are preventing AI from becoming a mainstream tool used in the field. In order to build and maintain and AI system, companies would require an immense amount of resources including memory, data, and computing power. Additionally, because AI systems are trained through learning data sets, cyber security firms need to get their hands on many different data sets of malware codes, non-malicious codes, and anomalies. Obtaining all of these accurate data sets can take a really long time and resources which some companies cannot afford.
Another drawback is that hackers can also use AI themselves to test their malware and improve and enhance it to potentially become AI-proof. In fact, an AI-proof malware can be extremely destructive as they can learn from existing AI tools and develop more advanced attacks to be able to penetrate traditional cyber security programs or even AI-boosted systems.
Solutions to AI limitations
Knowing these limitations and drawbacks, it’s obvious that AI is a long way from becoming the only cyber security solution. The best approach in the meantime would be to combine traditional techniques with AI tools, so organizations should keep these solutions in mind when developing their cyber security strategy:
Employ a cyber security firm with professionals who have experience and skills in many different facets of cyber security.
Have your cyber security team test your systems and networks for any potential gaps and fix them immediately.
Use filters for URLs to block malicious links that potentially have a virus or malware.
Install firewalls and other malware scanners to protect your systems and have these constantly updated to match redesigned malware.
Monitor your outgoing traffic and apply exit filters to restrict this type of traffic.
Constantly review the latest cyber threats and security protocols to get information about which risks you should be managing first and develop your security protocol accordingly.
Perform regular audits of both hardware and software to make sure your systems are healthy and working.
Following these steps can help mitigate many of the risks associated with cyber attacks, but it’s important to know that your organization is still at risk of an attack. Because of this, prevention is not enough and you should also work with your cyber security team to develop a recovery strategy.
As the potential of AI is being explored to boost the cyber security profile of a corporation, it is also being developed by hackers. Since it is still being developed and its potential is far from reach, we cannot yet know whether it will one day be helpful or detrimental for cyber security. In the meantime, it’s important that organizations do as much as they can with a mix of traditional methods and AI to stay on top of their cyber security strategy.