Knowledge graph machine learning has been touted as the next wave in cybersecurity, but how can you use these tools to improve your organization’s security? The advancement of cloud computing security and AI continues to push the boundaries of Industry 4.0. Despite the rise of advanced cyber crimes against enterprises, machine learning applications are among the most significant developments in cyber security.
When we think about cybersecurity, we often think of data breaches caused by hackers that steal information, encrypt it and then send it to an outside party. In the US, data breaches have occurred in 45% of organizations. Nearly half of US businesses had a data breach in the previous year, according to the 2021 Thales Data Threat Report. It leads to a concern that organizations are not being proactive enough in protecting themselves from being hacked. In addition, global internet users witnessed 52 million data breaches in Q2 2022. Data breaches are far more likely to happen than you realize if you have not taken the time to review your security policies and procedures yet. This article discusses the impact of machine learning on cybersecurity, and it helps to secure your enterprise.
- Knowledge Graphs Integrate Data Into Different Analytics Tools
Knowledge graphs are a powerful tool for cybersecurity. They provide a single source of truth and can be used to feed data into various analytics tools. Knowledge graphs are created by combining multiple sources of information, such as text, images, videos and sound files, into one coherent entity that provides context and meaning on an ongoing basis. It allows users to make decisions based on their own experiences without having access to all the information needed to make accurate judgments about what is relevant at any given moment or place within an organization’s network infrastructure (e.g., servers).
- Faster Response To The Security Breach
When a security breach happens, it’s frustrating and can be devastating. Responses to the breach often need to be immediate, but traditional security teams only have access to human resources departments and maybe threat detection tools as a resource. Human errors cause over 80% of all security incidents in the retail industry. It has led to the implementation of machine learning programs that detect and mitigate risks before they become threats. Machine learning can get better at predicting the behavior of a user or customer.
- Securing Your Enterprise With Machine Learning And Knowledge Graphs
Machine learning is a powerful tool that can be used to protect your network from cyberattacks. Machine learning algorithms can identify patterns in large amounts of data and make predictions about future events, like whether or not someone will click on a link or open an email attachment. Knowledge graph machine learning can improve cybersecurity by giving analysts new insights and visibility into network activity. They enable companies to create an autonomous system that can learn from data without human intervention. These systems will continuously monitor the networks for anomalies, then use the information they collect to make predictions about future attacks. When these systems detect an anomaly, they can also share this information with security tools within your organization so that administrators can take action before it’s too late.
- Identifying Vulnerable Areas And Forecast Where Assaults Will Occur
Cybercriminals constantly change methods and technologies. Instead of defending against the previous assault, systems must generate predictions. This entails examining external data to assess whether attackers will likely target your company. Many new attacks use outdated code or known OS vulnerabilities. Machine learning can assist in detecting these problems and suggest improvements.
Conclusion
A rise in cybercrime has been correlated with the increasing number of corporate digitalization initiatives. Ransomware assaults are occurring at a rate of once every 11 seconds now, causing an average disruption of 21 days for businesses. Given the growing role of machine learning in today’s online universe, it’s safe to say that its impact on cybersecurity will grow in the coming years. Any enterprise that doesn’t effectively utilize tools like knowledge graphs and machine learning will likely suffer from massive security problems in the years to come.