Endpoint detection and response
In 2013, Anton Chuvakin of Gartner coined the term "endpoint threat detection and response" for "tools primarily focused on detecting and investigating suspicious activities (and traces of such) other problems on hosts/endpoints". Now, it is commonly known as "endpoint detection and response".
According to the Endpoint Detection and Response - Global Market Outlook (2017-2026) report, the adoption of cloud-based and on-premises EDR solutions are going to grow 26% annually, and will be valued at $7273.26 million by 2026. According to the Artificial Intelligence (AI) in Cyber Security Market report by Zion Market Research, the role of machine learning and artificial intelligence will create a $30.9 billion cyber security market by 2025.
In 2020, source code for a widely-used EDR tool was made available by Comodo Cybersecurity as OpenEDR. The Commons Clause license they applied makes it available for free and more trustworthy, but explicitly does not claim to meet the commercial reuse requirements of open-source.
Endpoint detection and response technology is used to protect endpoints, which are computer hardware devices, from threat. Creators of the EDR technology based platforms deploy tools to gather data from endpoint devices, and then analyze the data to reveal potential cyber threats and issues. It is a protection against hacking attempts and theft of user data. The software is installed on the end-user device and it is continually monitored. The data is stored in a centralized database. In an incident when a threat is found, the end-user is immediately prompted with preventive list of actions.
Every EDR platform has its unique set of capabilities. However, some common capabilities include the monitoring of endpoints in both the online and offline mode, responding to threats in real-time, increasing visibility and transparency of user data, detecting store endpoint events and malware injections, creating blacklists and whitelist, and integration with other technologies.
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