New challenges and threats
Posted: Thu Feb 06, 2025 3:06 am
Cybersecurity in the Age of Artificial Intelligence
Maxim Bolshakov, Head of Security at EdgeCenter | 09/17/2024
In an era of rapid technological development, artificial intelligence is becoming an integral part of our daily lives. Its applications span a wide range of areas, from medicine and finance to transportation and entertainment. However, along with new opportunities, AI also brings new challenges, especially in the area of cybersecurity. How exactly is the cyber threat landscape changing in the era of AI, and what measures should be taken to protect data and systems?
AI can be used for both defense and attack. On the benin mobile database hand, AI systems help detect and prevent cyberattacks by analyzing huge amounts of data and identifying anomalies in real time. On the other hand, attackers are also actively using AI to create more complex and difficult to detect attacks.
One example is the use of AI to develop phishing attacks. With machine learning, attackers can create realistic fake messages and websites that are difficult to distinguish from the real thing. Another example is the automation of attacks using botnets that can adapt to real-time defenses.
AI can also be used to create malware that can bypass traditional defenses. Such programs can hide in systems for long periods of time, collecting data or causing damage before being detected.
Tools and methods of protection
To effectively protect yourself in the AI era, you need to take a comprehensive approach that includes the following measures:
Machine learning and data analysis. Modern cybersecurity systems use machine learning to analyze network traffic and identify anomalies that may indicate cyberattacks. These systems are able to adapt to new threats and improve their effectiveness as they accumulate data. For example, systems can automatically update their models based on new malware samples, allowing them to respond to threats more quickly.
Automation and orchestration. Using automated incident response solutions can significantly reduce the time it takes to detect and eliminate threats. Orchestration of various security systems ensures their coordinated operation and increases overall efficiency. This includes automatic software updates, regular vulnerability scans, and automatic patching.
Maxim Bolshakov, Head of Security at EdgeCenter | 09/17/2024
In an era of rapid technological development, artificial intelligence is becoming an integral part of our daily lives. Its applications span a wide range of areas, from medicine and finance to transportation and entertainment. However, along with new opportunities, AI also brings new challenges, especially in the area of cybersecurity. How exactly is the cyber threat landscape changing in the era of AI, and what measures should be taken to protect data and systems?
AI can be used for both defense and attack. On the benin mobile database hand, AI systems help detect and prevent cyberattacks by analyzing huge amounts of data and identifying anomalies in real time. On the other hand, attackers are also actively using AI to create more complex and difficult to detect attacks.
One example is the use of AI to develop phishing attacks. With machine learning, attackers can create realistic fake messages and websites that are difficult to distinguish from the real thing. Another example is the automation of attacks using botnets that can adapt to real-time defenses.
AI can also be used to create malware that can bypass traditional defenses. Such programs can hide in systems for long periods of time, collecting data or causing damage before being detected.
Tools and methods of protection
To effectively protect yourself in the AI era, you need to take a comprehensive approach that includes the following measures:
Machine learning and data analysis. Modern cybersecurity systems use machine learning to analyze network traffic and identify anomalies that may indicate cyberattacks. These systems are able to adapt to new threats and improve their effectiveness as they accumulate data. For example, systems can automatically update their models based on new malware samples, allowing them to respond to threats more quickly.
Automation and orchestration. Using automated incident response solutions can significantly reduce the time it takes to detect and eliminate threats. Orchestration of various security systems ensures their coordinated operation and increases overall efficiency. This includes automatic software updates, regular vulnerability scans, and automatic patching.