What are the uses of AI in cyber defence

1. What are the uses of AI in cyber defence? The intervention of digitization has definitely had some positive impact, but at the same time, it has also raised certain concerns. The data breach is a common problem faced by most organizations irrespective of their business size. As per Norton, a common data breach can cost a company a loss of approximately $3.86 million. And it can take around 196 days to identify this threat. This time loss can adversely impact the performance of the company and its productivity. Artificial Intelligence can prove to be beneficial here. It can help assess the threats and prohibit them further. In this blog, we will be highlighting how AI is going to be helpful in this process.

2. How is AI creating a difference in the field of cyber defence? Before we go ahead, it is important for you to know that cybersecurity is necessary for your business. Irrespective of the business size, investing in cybersecurity measures is important to ensure data security and gain customers' trust. Despite all the measures, there have been several incidents where we have seen even the best measures fail. But with the rising complexities of cyberattacks, we also have better measures to enhance the security of the system. Technologies like artificial intelligence have proven beneficial in this. Let's understand how AI is helping in this process. How is artificial intelligence being used in the field of cybersecurity? Machine learning is the soul of artificial intelligence. The algorithm enables the computer to analyze the data, learn from the previous data sets, and make decisions accordingly. This feature is used to predict the unusual experience and hence predict the threat to the system. With the help of a machine learning algorithm, it becomes easier to predict cybersecurity threats and prevent such incidents. Many modern security tools are using this system to prevent data threats. There are different types of machine learning algorithms, but there are a few of them which are commonly used: Regression— This is used to detect a correlation between different datasets and understand how the datasets are related to each other. It

3. can be used to detect anomalies by comparing the prediction to an actual call. Clustering—This is used to find out the similarities between the datasets and the groups. It directly works on new data without working on the previous ones. Classification—It learns from the previous observations. Whatever learning it derives from the previous observation, it uses the same to learn new data. It classifies the data into several labels. One example of this is Classify, which categorises legitimate software, ransomware or spyware. This is how artificial intelligence works in a real-life scenario. With this basic implementation, companies can identify the threat. To make the successful implementation of artificial intelligence, it is important to learn all the details of AI. A certification course in artificial intelligence will cover all such details. If you want to enrol for the best artificial intelligence certification program or machine learning certification program, you can connect with the Global Tech Council.