What are the challenges of Cyber Security Analytics?
In today’s era, a wide variety of technologies are available in the market. Every individual wants to use that not only in a professional way but also in personal life. But as technologies increase, the risk for organizations or individuals also increases. Because intrusive hacking is becoming both more sophisticated and widespread, the organization’s security team has to collect and use the historical data on accounts, machines, and equipment that may have been attacked to predict, identify and prevent the potential new threats this all can be possible with cyber security analytics.
What are the Solutions Cyber Security Analytics?
With Xenonstack Support, security analytics is divided into four sectors; users will predict attacks and prevent them before something serious.
- In digital security analytics, by using a dataset containing the historical data of protocol used, type of attacks, source IP address, source port number, destination IP address, and destination port number, the entity can build, deploy, and refresh the models to predict incoming threats in real-time.
- Our prediction model allows analysts to monitor intrusion vectors and take action as soon as possible and protect the system from serious causes.
- In Digital Security One can protect the database, computer system, and websites from attack by doing analysis. Like which CIA traits violated, assets targeted, penetration data, and other information sources.
- Through this, an entity can find threats or attacks at an earlier stage and take action as early as possible.
- In-Network Security analytics, one can build accurate and predictive models on real-time data to better understand the customer to get the information about their attacks, Vulnerabilities, events logs, and authentication user can bring clarity of the network connectivity.
- As a result, we have given the demo of the dashboards for user reference. You will be confident after getting the results for events logs, attack prediction results, etc. By seeing the dashboards, you will get information about how our machine learning models work.
- In Communication Security analytics, one can build accurate and predictive models on real-time data. To better understand the customer to get the information about their communication of message delivery, encryption for TLS and Non-TLS between the networks.
- And here, the user will see the prediction on messages delivered through mails that are authenticated.
- As a result, we have given the demo of the dashboards for reference. You will be confident after getting the results for encryption of messages, authentication, spam filters using our machine learning model. Users can easily get all the information about communication network security by applying our models.
Click on the button and request us to give you a demo of our machine learning model for cyber security analytics. Here you will get insights related to attacks, network security, communication, digital security, and data security. Our model will provide you with the accurate prediction of attacks and message delivery for our security analytics model with narrative addition.
Below are the security analytics dashboards for every four sectors, for users to predict attacks and prevent them before something serious.