Artificial intelligence is being adopted more and more into cybersecurity with benefits that include faster detection, better protection, and reduced human involvement. This post will explore what are the role of artificial intelligence in cybersecurity, how AI has already transformed the field of cybersecurity so far, and how AI may continue to change security in the future.
What’s the Problem?
Cybersecurity has always been a priority for internet users around the world. However, many people fail to realize precisely what cyberattacks are or where they come from (cyberspace). Cybersecurity has been a significant problem for the past three decades, with no signs of slowing down in the age of IoT, smart cities, and 5G. Cybercriminal activity occurs constantly and affects both large businesses and individual users (“cybercrime”).
A recent study by Techradar.pro has shown that there are now over 600 new malware threats are created and detected after every minute. It is a staggering number that suggests that cybercrime is increasing while cybersecurity is staying stagnant.
Benefits Of Artificial Intelligence in Cybersecurity
Highlighting the importance of artificial intelligence (AI) in cybersecurity, it’s important to note that AI has been a major factor in most new developments in the field and will continue to be so. ThinkML, a blog dedicated to artificial intelligence and machine learning, has also published several studies on artificial intelligence and ways to deal with cybersecurity. Artificial intelligence allows organizations to construct Intelligent Agents to handle specific security issues. An Intelligent Agent, for example, may detect weaknesses concealed in millions of coding lines. It can detect irregularities in the user’s login. It may also detect a different strain of the virus for which no evidence exists.
In the past couple of years, many advancements have been made concerning AI that has transformed many aspects of cybersecurity, including:
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Detection
Artificial intelligence predicts future events, including hacking attempts and network intrusions before they even happen. It helps increase detection rates significantly. One study by Cisco shows that machine learning can increase malware detection rates compared to traditional rules-based systems.
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Response
AI can take ‘action’ once an attack is detected. AI can detect security events in real-time and implement actions to remediate the attack. It also helps reduce the time to identify and respond to a threat.
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Prevention
Like response and detection, prevention is an action that AI takes once an intrusion has been detected. AI then implements recommendations to prevent future attacks.
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Augmentation
Artificial intelligence can augment human intelligence by empowering people to protect systems better. For example, an AI-powered cybersecurity analyst could augment the efforts of an expert analyzing a security event generated by AI.
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Projection
In the past couple of years, it has become more common to use AI instead of humans to search for vulnerabilities and report potential risks. It is done through automated techniques that feed information into a more advanced AI model to detect and potentially prevent future attacks before they happen. Organizations are seeing significant benefits in this space regarding time and cost savings for most projects.
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Forensics
AI can be used to help with forensics after an attack occurs. An AI-powered system can aid security analysts by collecting information and storing it in a manner that allows them to trace better, monitor, and identify breaches.
AI is playing a prominent role in cybersecurity, likely increasing in the years ahead. However, organizations don’t use artificial intelligence extensively as several challenges to overcome.
Some of the significant challenges with artificial intelligence in cybersecurity include how well software can discern between human behavior and mechanical behavior; how well software can adjust over time; what happens when an attack cuts off the power or internet access for an area for extended periods; and whether artificial intelligence can perceive new types of attacks.
What are Artificial Intelligence Techniques Being Used to Help with Cybersecurity?
We’re already starting to see these artificial intelligence techniques employed by organizations, and as these techniques are developed, they will likely see increased use. The following sections break down each technique and how it works.
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Natural language processing – Natural language processing(NLP) is based on the idea that software analyzes text to extract information about the context of the text (i.e., what the words mean). It’s currently used by various applications, from spam filters to credit card companies looking for fraudulent purchases.
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Machine learning – Machine learning uses algorithms to “learn” about the attributes of an object so that it can predict what will happen next. It’s currently used to help create computer models from fraud detection to medical imaging and self-driving cars.
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Sentiment analysis – Sentiment analysis is a technique used by language recognition software that analyzes human language to determine the positive or negative emotions expressed in text. This data is then used to determine whether something is positive or negative and how similar it is to other comments or documents. These applications include online opinion polls, automatic speech recognition, and direct marketing campaigns.
Artificial Intelligence-Based Security Tools for Organizations
As AI continues developing, many new advances will be made in cybersecurity. Companies and government agencies are starting to realize the incredible benefits of AI for many facets of IT security. While there is no doubt about it, advanced technologies about cybersecurity will continue to grow in number and complexity with each passing year.
There are security tools that protect the network to prevent its intrusion. These may include firewalls, access controls, and intrusion prevention systems. There are also security tools that protect the data itself. These may include encryption and other measures to secure the data at rest. Finally, there are security tools that have an impact on both above aspects. These may include anti-malware protection or content filtering software on computers and anti-phishing software on mobile devices such as smartphones or tablets with Wi-Fi capabilities. As we move into a digitalized era with more incredible technological advancement, these security tools will advance similarly.
Conclusion
Artificial intelligence is the only technology that can replicate human-level reasoning and adapt to market changes at a fast pace. In other words, it can handle all tasks that humans might be doing within an organization while providing the same degree of security to the network. Without it, any attempt at preventing cybersecurity breaches is futile.