USING AI FOR CYBERSECURITY

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Cybersecurity threats continue to plague modern society and the problem will only get worse with time. Recent ransomware attacks in multiple hospitals led to them turning down patients due to a system failure. Threats like these are among the top concerns for industry leaders today. Because AI is very versatile and can be applied in many different areas, experts have called for its use in cybersecurity. The idea of Artificial Intelligence helping out with this is not a new idea. There has always been potential for misuse. However, the threats are beginning to outweigh any such concerns.

At this point it is believed that, deploying AI for cybersecurity solutions will protect organizations from attacks that, could threaten their very existence, and in the case of the hospitals, cost people their lives. Data driven security models have already shown that they can help stop even the most sophisticated ransomware and malware attacks.

BIOMETRIC LOGIN SYSTEMS

There are many steps that can be taken to secure a system using AI. A good first step is utilizing biometric login systems. This can include scanning fingerprints, palm prints, and even a persons retina. These kinds of systems have been proposed to replace passwords because most passwords are not very strong or secure.

High profile data breaches, like the one that happened to Amazon just before Black Friday last year, create problems for people, who don’t have good passwords or who go long periods of time without changing them. They end up becoming readily available on the dark web for just about anyone to steal. This isn’t limited to passwords. Credit card numbers and even social security numbers are at risk as well. Biometric login systems could be used alongside a password which is already the case with most iphones or it can be used on its own for more protection. We are having to move in this direction whether we like it or not.

cybersecurity

An example of a biometric fingerprint scanner from ACCEO.

CYBERSECURITY THREAT DETECTION

At this point everyone has some kind of anti-virus software or anti-malware programs or a combination of the two. However, as time goes on these programs become obsolete and the attacks on them become too sophisticated for them to handle. It does pose a problem for people who don’t want to pay more for higher end software. The only good answer is to continue to develop AI and make the technology more widely available for cybersecurity purposes.

AI systems are being trained to detect malware and viruses with the help of several training sets that include algorithms and codes. Using this data, AI be trained in pattern recognition to help identify malicious behavior in software. Machine learning by itself can analyze path traversals of websites to determine if they are being routed to malicious domains. AI programs can even be trained to analyze the micro behavior of ransomware in order to recognize it before it can do any damage. This is only the beginning of the amazing capabilities of Artificial Intelligence.

LEARNING WITH NATURAL LANGUAGE PROCESSING

This is another area that has seen much progress over the past decade. It has many uses in many areas but it can play a crucial one in cybersecurity. It can automatically scan articles and parse over news sources to keep up to date with the latest threats and learn to combat them. This kind of information will provide key insight into malware attacks, anomalies, and mitigation strategies. Using the information cybersecurity firms can identify risks, calculate timescales, harvest data, and make predictions. Staying updated on current threats is an important way to mitigate these threats before they occur.

AUTHENTICATION FRAMEWORKS

General purpose authentication models are already in use by many companies today. Securing vital data and limiting access to it is an important part of securing our networks. Sophisticated authentication systems make this possible. With the use of AI, it can be taken many steps further.

AI systems can utilize what is referred to as Multi-Factored Authentication for this purpose. With this approach, systems will collect user data to analyze the behavior of the user, application, device, network, and location. Using this information an authentication framework powered by Artificial Intelligence can prove to be much more agile than traditional frameworks. In addition, they will be able to automatically change any users access privileges to ensure security when being accessed remotely.

LIMITATIONS

For the moment, AI is not without its limitations in this area. At this time AI systems can be expensive to build requiring a lot of computational resources such as memory and hardware. Until the cost can be driven down by innovation a lot of people will not have sufficient access to it. The other problem lies with inaccurate data. The data sets utilized must be large which increases the chances of having mistakes and even the smallest of mistakes can have a negative impact on the performance of the algorithm. Finding and collecting precise data sets can be a very tedious and time consuming task.

The other problem is that the technology the hackers are using is becoming more high end as well. Work on AI proof malware is already underway. Now the field of AI is moving so rapidly that it is unlikely that underground hackers will be able to keep up but it could still pose some problems in the short term.

The bottom line is, whether we like it or not AI will be the future of cybersecurity. With a little innovation we can address whatever problems and limitations it faces today. Eventually it is believed that viruses and malware will cease to exist.

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