UPDATE: TQL Says Data Breach Was Not Malware Or Ransomware Attack Fixed
Machine learning is of rising importance in cybersecurity. The primary objective of applying machine learning in cybersecurity is to make the process of malware detection more actionable, scalable and effective than traditional approaches, which require human intervention. The cybersecurity domain involves machine learning challenges that require efficient methodical and theoretical handling. Several machine learning and statistical methods, such as deep learning, support vector machines and Bayesian classification, among others, have proven effective in mitigating cyber-attacks. The detection of hidden trends and insights from network data and building of a corresponding data-driven machine learning model to prevent these attacks is vital to design intelligent security systems.
UPDATE: TQL says data breach was not malware or ransomware attack
We have not had to recover our data after a ransomware attack but if our whole environment was encrypted, we have several ways to recover it. Zerto is the last resort for us but if we ever have to do that, I know that we can recover our environment in hours instead of days.
We use Zerto to enable our hot site configuration. We have two data centers. One of them is in one of our corporate buildings, which is our primary, and then we have a co-location center rack that we rent for our hot site backup or app. We use Zerto to replicate our servers and our VMs between those two sites. So, primarily, it is there in case of a disaster or malware attack, etc.
Endpoint attacks: unauthorized access to user devices, servers, or other endpoints, usually by malware infection. Malware attacks: introducing malware into IT resources, which enables attackers to take control of systems, steal data, and cause harm. Attacks using ransomware are also among them. Vulnerabilities, exploits and attacks: using software flaws in the organization's software to compromise, sabotage, or obtain illegal access to systems Advanced persistent threats: These are sophisticated, multi-layered threats that encompass both network and other assault types.
Attackers' main goal in a network attack is to breach the corporate network perimeter and obtain access tointernal systems. Once inside, attackers frequently mix different attack tactics, such as corrupting anendpoint, dispersing malware, or taking advantage of a flaw in a network system.