Source: medium.com
Machine Learning for Cyber Security (MLSecOps)Category: Data, automation, machine-learning, artificial-intelligence
SecOps (Security Operations), aims at combining and advancing collaboration between the security and IT operations teams by using automation and practices in a related way to how DevOps links development and operations teams. SecOps was born from a requirement to recognize and acknowledge threats quicker and correctly handle the increasing volumes of security issues in applications.
The code shown below is used to find the cluster of IPs which is to be blocked and then save the cluster number in a variable.
The code to block the IPs is given below: To detect the DoS attack in real time, instead of repeatedly running ML Code manually, Jenkins is used to automate this process.
The purpose of this job is to send an email to the security team with the generated data of suspicious IPs and the graph representing the cluster of IPs.
The code shown below is used to find the cluster of IPs which is to be blocked and then save the cluster number in a variable.
The code to block the IPs is given below: To detect the DoS attack in real time, instead of repeatedly running ML Code manually, Jenkins is used to automate this process.
The purpose of this job is to send an email to the security team with the generated data of suspicious IPs and the graph representing the cluster of IPs.
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