The Pros and Cons of Enlisting AI for Cybersecurity

    Artificial Intelligence (AI) is the faculty of a computer system to learn and reason, therefore, mimicking human intelligence. Over the course of the past several years, AI has become an indispensable part of cybersecurity measures. AI can predict cyberattacks with matchless precision, helps to create better security features that can bring down the number of cyberattacks and mitigate its impact on IT infrastructure.

    Artificial intelligence is a powerful cybersecurity tool for enterprises. It is rapidly turning into a sophisticated protective gear for enterprise cybersecurity, and many enterprises are adopting it at a rapid pace. Statista, in a recent post, noted that in 2019 approximately 83% of organizations based in the United States consider that without AI, their organization fails to deal with cyberattacks.

    AI can provide an IT firm with unparalleled real-time monitoring, security threat detection, and prompt action. AI cybersecurity solutions can react faster to cybersecurity threats with more accuracy than any human. It can also free up cybersecurity professionals to focus on more critical tasks in the organization.

    Read more: Becoming a Cybercriminal Keeps Getting Easier

    Advantages of AI in Cybersecurity

    Apart from the few advantages mentioned earlier, there are several more reasons for enterprises to embrace AI in cybersecurity. Let’s explore some of the notable pros and cons of pairing cybersecurity with AI. 

    The ability to process large volumes of data

    Implementing AI in cybersecurity helps organizations process an enormous amount of data with utmost precision and efficiency. AI automates the creation of machine learning algorithms that can detect a wide range of cybersecurity threats emerging from spam emails, malicious websites, third-party applications, or shared files.

    Greater adaptability

    The applications and programs driven by AI learn using machine learning algorithms and deep learning. Through these procedures, AI can easily understand many IT trends and make changes to its algorithms in accordance with the latest available data or information. Similarly, AI in cybersecurity is familiar with sophisticated data networks that can quickly identify security threats and eliminate them with little human intervention.

    AI in cybersecurity does not replace cybersecurity professionals. Instead, it helps cybersecurity professionals to detect and easily solve malicious network behaviors quickly. The further advancements in AI and machine learning by human interference will make AI more intelligent and, in the future, offer help to humans in return.

    Early detection of novel cybersecurity risks

    An IT network or infrastructure can face two types of cybersecurity risks. First, a novel, unknown threat, and second, a known threat that has already breached the network. Hackers are specialized in breaching undetected data networks, and AI-powered cybersecurity solutions can eliminate or mitigate these advanced hacking techniques to greater lengths.

    Hackers are always in a hot pursuit to devise new forms of cyberattacks and make them less detectable. Some of the cyberattacks include crypto-jacking, malware attacks on the Internet of Things (IoT) or smartphone devices, and cross-site scripting.

    Also read: Email Security Tips to Prevent Phishing and Malware

    AI offers a complete, real-time cybersecurity solutions

    Hackers don’t have regular working hours, and they launch their cyberattacks from different time zones. Therefore, real-time monitoring of your enterprise’s IT infrastructure is necessary to detect malicious cyber threats and data network security breaches.

    Using an AI-enabled third-party cybersecurity solution, your enterprise can eliminate the extra cost incurred on the work shifts of IT security professionals. It is also a feasible option as these cybersecurity solutions come at a reasonable monthly price. In addition, AI cybersecurity solutions mitigate human intervention and provide a detailed yet definitive detection of cyber threats and enhanced diagnostic capabilities, making them a reliable choice for enterprises.

    The integration of AI in the cybersecurity domain allows enterprises to make more productive use of capital and human resources. Your enterprise should allow the AI-powered cybersecurity applications to perform security diagnostics and permit the cybersecurity professionals to review legitimate cyber threats diagnosed by the applications. This procedure helps your enterprise to effectively utilize the capital, along with the time and talents of your IT staff.

    Ward off spams, phishing and redundant computing procedures

    Machine learning algorithms can be used effectively to guard your enterprise against spamming and phishing. Phishing is a sort of cyberattack intended to steal your sensitive yet confidential data. For instance, hackers can impersonate a legitimate organization or person by stealing personal details such as credit cards, banking, and login credentials.

    AI-enabled cybersecurity solutions can easily identify suspicious and malicious emails to alert you and protect your enterprise. It can also help eliminate redundant computing processes that can save time for your IT analysts.

    Also read: How to Prevent Third-Party Vulnerabilities

    The Drawbacks and Challenges of AI in Cybersecurity

    Along with the advantages, AI-powered cybersecurity solutions also present a few drawbacks and challenges. Getting to know about them will help you to implement more sophisticated cybersecurity systems and strategies.

    AI benefits hackers

    The advancement in AI can also benefit hackers as it enables them to perform highly sophisticated and large-scale cyberattacks. In addition, AI can also help hackers effectively explore and exploit vulnerabilities in a data network or a computer system.

    The breach of privacy

    AI-powered devices like biometric systems can be a threat to our sensitive and confidential data. These devices can transfer our data to third-party vendors that can be misused, violating the privacy of both individuals and enterprises.

    Higher cost for talents

    Currently, AI-based technologies are in the nascent stage, and therefore, the cost of creating a talent pool is very high. Moreover, the current developing stage of AI technology also brings down its reliability.

    More data, more problems

    Today, AI-enabled enterprises collect and process more data than ever before. However, entrusting our private and sensitive data with third-party enterprises may lead to privacy violations.

    Also read: Facial Recognition Crosses a Line with Mask Removal Features

    AI-Human Combination is the Solution

    Machine learning systems designed to augment enterprise cybersecurity have brought more automation in the cybersecurity process, less burnout, more accurate threat detection, more protection, and prompt repair.

    However, without human intervention, the efficiency of AI-powered cybersecurity solutions stands as an unanswered question.

    In the realm of cybersecurity, human touch and AI technology complement each other. A cybersecurity expert team should support the AI cybersecurity system. The AI system, in turn, can help the team learn where potential security vulnerabilities may linger and understand how those can turn into springboards for a cyberattack.

    Human touch is needed to ensure AI cybersecurity systems aren’t causing security problems instead of solving them. More than giving privileges to AI cybersecurity systems, it is always better to strike a balance between artificial intelligence and human inputs.

    AI-enabled enterprise cybersecurity systems also have certain limits. Generally, these systems can be used as an additional tool or smart assistant. Never let these cybersecurity systems replace your experienced cybersecurity specialists because it is they who understand, among other things, the underlying business context of your enterprise.

    To make the case clear for human intervention in AI-based cybersecurity systems, let’s consider an instance of physical security at an automatic security gate. An automated security gate can ward off unauthorized access and allow only authorized persons to a property. But keeping human guards along with the automatic high-security gate will provide extra safety, surveillance, and deterrence.

    Machine learning algorithms make split-second decisions on the cybersecurity of your enterprise. But these decisions are driven by data and algorithms. Placing human cybersecurity experts alongside the AI cybersecurity system can help ensure the system isn’t being manipulated or making wrong decisions based on faulty logic.

    Read next: What is Artificial Intelligence as a Service (AIaaS)?

    Kashyap Vyas
    Kashyap Vyas
    Kashyap Vyas is a writer with 9+ years of experience writing about SaaS, cloud communications, data analytics, IT security, and STEM topics. In addition to IT Business Edge, he's been a contributor to publications including Interesting Engineering, Machine Design, Design World, and several other peer-reviewed journals. Kashyap is also a digital marketing enthusiast and runs his own small consulting agency.

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