Using AI and Cybersecurity
A robust cybersecurity system begins with creating machine learning pipelines that are secure and seamless in their use, because AI-based models are only as good as the data they’re trained on. Building these AI models requires large amounts of high-quality data, which can be difficult to obtain as many companies are reluctant to share their information due privacy concerns.
However, data sharing can be done safely and securely if the right tools and protocols are in place. For example, the patterns created by data from past cyber-attacks can be used to help identify a potential new attack and stop it before it happens. The best part is that building these models has become much easier with the rise of artificial intelligence, which allows us to build end-to-end models with meta cloud utilization and visibility control.
Monitor And Respond To Threats With AI
AI technologies can help make security stronger by taking action against threats as soon as they occur. AI can help detect, respond to and/or block cyberattacks as they happen. This can help reduce the amount of time it takes to recover from a threat or ransomware attack—improving your overall cybersecurity posture in the process
AI needs access to data sources, including network traffic and system logs, which it can use to identify patterns that may indicate an attack. After AI detects an attack, it can then block malicious traffic or quarantine infected systems.
During the start of the COVID-19 pandemic, phishing attacks exploiting fear and uncertainty around the virus increased. Not only that, but with more people working from home, other forms of remote communication have become targets for criminals as well. This has heightened the security risk for many organizations.
AI can help to identify where attacks will occur and what they might look like. You can create models that help you understand where your organization might be most at risk, which will allow you to take steps to mitigate these risks before they cause problems.
Penetration Testing And Security Audits
Penetration testing is the process of attempting to break into a system in order to test its security. Manual penetration tests can be automated using artificial intelligence, which uses exploits to identify vulnerabilities in systems.
It can also be used to audit systems, identify weaknesses and suggest solutions. AI can be applied to auditing smart contracts for vulnerabilities, by identifying the ways in which attackers might exploit poorly-written code. This process makes security auditing more efficient and accurate.
Conclusion for AI and Cybersecurity
It’s important to remember that AI can play a vital role in improving your cybersecurity protection, despite how easily overlooked the technology can be. By utilizing AI run tools to build models, monitor threats and respond to them, as well as automating penetration testing and security audits, you are giving yourself a real-time view of the cybersecurity landscape. This will allow you take necessary steps to mitigate risks before they result in a disaster.
But, the best addition to your cybersecurity setup involves staying atop the latest trends, which you can find at Arruda Group.