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    Home » The Use of Artificial Intelligence in Cybersecurity
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    The Use of Artificial Intelligence in Cybersecurity

    VevansBy VevansJune 23, 2022No Comments5 Mins Read
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    Cyber Security and Digital Data Protection Concept. Icon graphic interface showing secure firewall technology for online data access defense against hacker, virus and insecure information for privacy.
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    The Use of Artificial Intelligence in Cybersecurity

    Cyberattacks are a growing problem in today’s enterprise environments. It is therefore necessary to analyze and improve an organization’s cybersecurity posture beyond human intervention.

    Machine learning and AI are becoming increasingly important in information security. These technologies can quickly analyze millions of data sets and track down many cyber threats, from malware threats to suspicious behavior that could lead to a phishing attack.

    These technologies are constantly improving and learning, drawing on past experiences and current to identify new types of attacks that could occur tomorrow or today.

    This post will discuss the good and the bad aspects of AI in cybersecurity. We’ll also share the views of experts and executives.

    Cybersecurity: The Advantages of Artificial Intelligence

    AI has many benefits and applications, including cybersecurity. They also provide a faster response than traditional software-driven or manual methods.

    Here are some benefits and applications of AI in cybersecurity

    Alerting to New Threats

    AI allows for superior predictive Intelligence with natural language processing that curates data by scraping through news articles and studies on cyber threats.

    AI-based cybersecurity systems provide current knowledge about industry-specific and global dangers. 

    Battling Bots

    Bots are a large part of the internet traffic today and can pose a danger. Bots can pose a serious threat to your account, ranging from account takeovers using stolen credentials to data fraud and bogus account creation.

    Automated threats can only be dealt with by using manual responses. Machine learning and AI help to understand website traffic and differentiate between bots (such as search engine crawlers) and bots that are not performing well.

    AI allows us to analyze large amounts of data, and cybersecurity teams can adapt to changing landscapes with our strategy.

    Businesses will be able to answer the questions “What is an average user journey like?” and “What does a risky, unusual journey look like?” by looking at their behavior patterns. We can then identify the intent behind their website traffic and get ahead of bad bots,” Mark Greenwood, Chief Technical Architect & Head Data Science at Netacea, explains.

    Prediction of Breach Risk

    AI systems are used to determine the IT asset inventory, which is a detailed and accurate record of all users and devices with access to different systems.

    AI-based systems are able to predict where and how likely you will be compromised based on your asset inventory and threat exposure. This allows you to plan and allocate resources for areas most vulnerable.

    AI-based analysis provides prescriptive insights that allow you to set up and improve processes and controls to increase your cyber resilience.

    Better Endpoint Protection

    There are more devices being used to work remotely than ever before. AI plays a critical role in protecting all of those endpoints.

    While VPNs and antivirus solutions can be used to protect against ransomware and remote malware attacks, they are often based on signatures. It is important to maintain a current list of signature definitions in order to be protected against new threats.

    This could be a problem if the virus definitions are not up to date, or the vendor isn’t aware of the issue. Signature protection might not be able protect against a new type or variant of malware attack.

    AI-driven endpoint security is a new approach. It establishes a baseline behavior for the endpoint by repeating training. AI can detect unusual behavior and alert technicians. It can also revert to normal after ransomware attacks. This allows for proactive protection, and not waiting for signature updates,” says Tim Brown, SolarWinds’ VP of Security Architecture.

    What Cybersecurity Executives Think About AI

    Capgemini Research Institute examined the role of AI and cybersecurity. Their report Reinventing Cybersecurity With Artificial Intelligence strongly suggests that modern businesses must strengthen their cybersecurity defenses using AI.

    According to the survey, 850 IT security and IT operations executives across 10 countries agreed that AI-enabled responses are necessary as cyberpunks already use AI tech for cyberattacks.

    The report offers some key insights, including:

    • Three-quarters of the surveyed executives believe that AI helps their company respond quicker to breaches.
    • 69% believe that AI is essential to combat cyberattacks.
    • One in five companies believes that AI increases the accuracy and efficiency cyber analysts.

    AI is a better solution to cybersecurity problems for organizations as networks grow and data becomes more complex. The fact is that humans can’t handle the increasing complexity on their own and AI will soon be a necessity.

    Cybersecurity: The downsides of AI

    These are only a few of the many benefits AI has to improve cybersecurity.

    As with all things, AI has its downsides. Organizations will need to invest significantly more in financial and human resources to create and maintain an AI system.

    Therefore, it is necessary to have a variety of different sets of malware codes, benign codes, and anomalies. All of these data sets are expensive and time-consuming.

    AI systems are prone to produce false positives and incorrect results if they don’t have a lot of data. Cybercriminals also have the option of using AI to analyze malware and launch advanced attacks. This is another major problem.

    Adversaries can use AI

    Cybersecurity professionals can use AI to strengthen cybersecurity best practices and reduce the attack surface, rather than constantly being on the alert for malicious activity.

    Cybercriminals could also take advantage of these AI systems to commit crimes. Accenture says adversarial AI causes machine learning models to misinterpret inputs and then behave in a manner that favors the attacker.

    An iPhone’s FaceID access feature, which uses neural networks to recognize faces to identify faces, is vulnerable to adversarial AI attacks. Conclusion

     

    AI is quickly becoming a key technology to improve the performance of IT security teams. AI provides the essential analysis and threat identification needed by security professionals to reduce breach risk and improve security posture.

    Even with its potential drawbacks, AI can drive cybersecurity forward and help organizations build a stronger security posture.

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