Artificial intelligence (AI) -based cyber security methods have been developed in response to this unprecedented challenge to help artificial intelligence security teams address data breaches and cybersecurity threats.
According to a Capgemini Research Institute survey, nearly 69% of companies perceive artificial intelligence to play an active role in combating various cybercrimes. Changes in cyber attacks are increasing day by day as technology evolves in both directions and continues to grow rapidly. Hundreds of billions of time-varying signals need to be estimated according to the size of your organization in order to measure risk correctly. As a result, companies are considering the introduction of artificial intelligence in cybersecurity.
Threats in the cyber world
The online world is wide and deep. The Internet ecosystem has billions of websites and services on different platforms. As much as it is easy to launch a presence in the online world; maintaining security is not easy and it is a difficult task.
Some of the common cyber threats to indigenous peoples in the online world are:
• Phishing – Fake emails asking for personal and security information.
• Malware, such as ransomware, encrypts files and holds them against ransoms.
• Website Denial of Service (DDOS) attacks, sometimes followed by blackmail.
• Hacking of personal or business artificial intelligence (AI) based cybersecurity methods accounts.
• Information or security breaches within the organization or company.
Cybercrime can be a challenging task for security professionals. Emerging technologies can further enhance security and cyber attacks. Hackers are looking for new ways to break through established protocols and steal critical information, often asking for ransoms.
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Introduction of artificial intelligence in security
Artificial intelligence has become a reliable alternative to facing threats in the cyber world. Machine learning and artificial intelligence are used to monitor illegal and malicious activities by comparing the actions of communities in a similar environment, AI in security systems often used to distinguish between “good” and “bad.” More advanced artificial intelligence systems can only go beyond identifying good or bad performance by analyzing large amounts of data and assisting in the accumulation of related activities that can indicate suspicious behavior by anonymous communities.
Companies use models based on artificial intelligence and machine learning to create a network architecture to prevent cybercrime and attacks. The protective features of artificial intelligence when faced with new or unknown information / behaviors, “learning” based on past behavior, allow for a quick, functional context and insights; including drawing logical conclusions from potentially inadequate subsets of data and providing multiple solutions to a known problem so that security teams can choose the best course of action.
Artificial intelligence approaches improve the overall security architecture and its performance by providing better protection against the increasing complexity of cyber attacks when traditional security systems have proven to be slow and inefficient. Business processes and financial results have already improved in companies that have used artificial intelligence in their internal and external processes. The use of artificial intelligence cybersecurity solutions has also helped accelerate the growth of data-driven data models in various fields.
We believe that artificial intelligence will be able to anticipate events and provide preventive action in the field of cybersecurity in the near future. It is also expected that countermeasures will be widely used to allow companies to breathe easily and stay prepared in the event of a cyber attack.
In addition, in terms of cybersecurity, artificial intelligence is able to identify complex attacks, stop them and prevent future attempts by cybercriminals by verifying their identities and taking action against them. We can also expect advanced automatic detection systems that detect attacks with a high probability without significant operating costs. In addition to this, the availability of root cause analysis of automated software vulnerabilities is also expected, which can determine why a security vulnerability exists and how it can be fixed. Some solutions, such as attacker detection, automatic disruption response, can successfully remove them from the network, or phishing detection never forgets or creates a false warning.
Many new developments are expected in the field of cybersecurity, while machine learning and artificial intelligence remain the preferred option in the fight against cybercrime.
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How artificial intelligence helps fight cybercrime was originally published in Become Human: Artificial Intelligence Magazine In a medium where people continue the conversation by emphasizing and responding to this story.