How AI Improves Cyber Defense and Prevents Cyber Attacks - Stefanini

How AI Improves Cyber Defense And Prevents Cyber Attacks

The role of artificial intelligence in cybersecurity cannot be overemphasized. Machine learning and Al networks have made it possible for security experts to understand and combat cybercrime with greater agility than previous standards. The technology enhances the efficacy of the cybersecurity technologies that are used by companies to keep their sensitive data safe.

When artificial intelligence is added to existing IoT (internet of things) solutions it creates machines that are intelligent enough to analyze data and make smart decisions with little or no human involvement. While IoT is responsible for the interaction among devices through connections, AI enables these devices to learn through data and experience.
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Categories of AI

Artificial intelligence is categorized into three types:

  • Narrow Artificial Intelligence (NAI)
  • Artificial General Intelligence AGI
  • Artificial Super Intelligence (ASI)

Narrow AI (NAI) is a simulation of human intelligence. It is also called a weak AI as it works within a limited context for singular tasks which may be simple or highly complex – like playing a game of chess. On the other hand, AGI, and ASI both are more powerful with the ability to solve a situation and problem similar to a human mind. They can also interpret tone as well as emotion. ASI will ultimately surpass our ability and intelligence. Neither form of these two strong AI exists yet, but as research continues it will quickly influence enterprise security.
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Benefits of AI in Cybersecurity

Let’s have a look at some of the main ways in which AI technology is benefiting the cybersecurity world.

#1. Ability to Process Volumes of Data

One of the biggest advantages of using Al-enabled security is that it is capable of processing big volumes of data rather quickly. This is because it automates the creation of algorithms that detect advanced security threats. The data processed covers everything from files shared to emails exchanged to websites accessed and much more. The in-depth security scanning functionality of Al is incomparable to that of a human scan. The human eye is often too quick to skim or overlook irregularities. On the other hand, AI analysis is always thorough and quick.

#2. Al Learns Over Time

Al uses deep learning to understand and learn the behavior of a network over time. It takes note of the pattern of activities on the network and then clusters them together. Then it goes on to detect incidents or activities that are against the norms. When threats are detected, it becomes easier to quickly identify additional threats with the similar traits and also block them early enough. The constant ability of AI to improve its learning with experience makes it harder for hackers to trick it using the same strategies, which means less opportunities for bad actors to exploit system vulnerabilities.

#3. Better Vulnerability Management

A company/business is faced with numerous threats and risks on a daily basis. Hence it needs to be well-equipped to detect, identify and prevent a variety of attacks for they cause damage. Al can help you assess and analyze whether or not the existing security measures are working effectively and does so much more quickly and efficiently than your security would be able to on their own.

When the loopholes in business networks and computer systems are assessed thoroughly and consistently, it brings forth important security aspects and areas that need to be improved. This makes it possible to manage vulnerabilities and secure systems before major loss or damage is caused.

#4. Securing Authentication Protocols

There are many websites that require users to log in, make online payments, and fill in forms. Such websites/businesses need authentication protocols as a security layer for the site’s backend. Al can further secure the authentication process via physical recognition.

Advanced Al protocols use elements like fingerprint scanners, facial recognition, and reCAPTCHA to identify a person. It then verifies the main data access points and allows access only if the login is proven authentic.

#5. Manages Duplicative Cybersecurity Processes

Cybercriminals keep on changing their tactics but the basic security practices at a company remain the same. So, if you hire someone to look after security threats, they may either get bored with their job or become complacent and miss an important security task that could expose your network.

Al adopts the best of human capabilities while leaving out the shortcomings. This is why it can be relied on to look after duplicative cybersecurity processes which could bore your cybersecurity staff. Al is not only capable of checking basic security threats regularly but also preventing them.  Besides, it analyzes your network carefully to see if there are any errors or loopholes that could prove damaging to your network/business in the short or long term.

#6. Hunts Zero-Day Exploits

One of the biggest challenges for today’s cybersecurity is defending against zero-day attacks and exploits. This sort of attack happens when perpetrators are able to exploit a vulnerability of software by exploiting an unpatched vulnerability. Traditional methods of security like antivirus software can neither detect nor prevent such exploits. However, AI may help.

Here, deep learning architectures may uncover hidden patterns and over time become more context-aware, which is quite helpful to identify zero-day vulnerabilities or attacks.

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Drawbacks of Al-Enabled Cyber Security

While Al offers enormous benefits to cybersecurity, it has its limitations and downsides as well. Let’s have a look at some of them.

1. Cybercriminals Are Also Al-Savvy

Cybercriminals are always looking for ways to understand and crack the cybersecurity solutions (Al or not) that companies and people use to guard their data/network. And since Al knowledge is available to all, these criminals can use it to come up with Al-proof programs that look harmless. In such cases, cybersecurity systems or IT professionals may not pay attention or take action vulnerabilities their AI systems deem as ‘harmless’ threats.  Unless security personnel have protocols for these scenarios, cyber criminals can exploit these vulnerabilities.

2. Not 100% Accurate

Al is a relatively new technology and not advanced enough yet to provide 100% accurate results. So to ensure the protection of your network and its data and applications, Al-based solutions should implement validation protocols when results seem uncertain. This means that when an Al-enabled security solution is doubtful about something, it’ll flag it as potentially threatening. This creates alerts for suspicious activities which can then be investigated by human analysts.

3. It’s Expensive

With the growing prevalence of big data, the use of artificial intelligence is increasing by the day. This places Al experts in high demand, and they may be either unavailable or very hard to find. Since there are growing numbers of cybersecurity Al solutions that companies are seeking to employ need, they may be at the risk of overspending in order to obtain competitive personnel or technology solutions.

The cost of proper cybersecurity solutions are somewhat justified by the value of preventing a data breach. However, companies should recognize that a cybersecurity budget must have limits defined by achievable goals and build up toward more robust systems rather than overspending on the latest and greatest solutions.

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AI is swiftly becoming an integral part of cybersecurity. However, cybercriminals will also use it to jeopardize organizations. They develop specific cyber programs which can impersonate actual algorithms that are based on AI. Such threats make these integrated programs, and human intelligence-dependent roles vulnerable. If sensitive data ends up in the wrong hands, that could be catastrophic. The fact is that AI is not foolproof – certainly not 100% which is the case with every other cybersecurity solution.

Author Bio: I am Harry Miller. I write for and cover topics for internet, lifestyle, entertainment and related news. My prime focus is being objective in all my covered topics and share in-depth information for the readers.

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