Logging and monitoring, machine learning and AI - Cybersecurity ControlsFree text search: 'Cybersecurity Controls - Logging monitoring' on projects Free text search: 'Cybersecurity Controls - Logging monitoring' on results/demos
The process of recording activities happening on an IT system, including OT systems operated via IT. Monitoring and logging typically occurs on network level, where packages are being sent over TCP/IP (internet protocol) and captured at the edges, in the controlling entities (routers and gateways) or as an in-line device (such as a firewall, ids or ips). Network traffic typically records origin and destination IP address, the type of application, and contents. Some of the traffic could have been encrypted.
Network traffic can be captured via a monitoring port on network devices. This results in the recording of all events that have been instructed to be logged. During the monitoring phase, this near real time data can be evaluated and analyzed. On the basis of the traffic patterns can be detected that allow the understanding of how applications (such as ransomware) arrives inside the organization or on how confidential data might leave the organization.
Logging also happens on the device level, allowing to identify the activities taking place on the device (types of applications being used and identities of people accessing the devices). This allows to identify a user with a certain transaction, or allows better for the detection of data manipulation or data theft to take place. With Machine Learning techniques some behavioral actions on a network will be detected prior to the malicious action of theft or abuse taking place. On the basis of patterns and pattern recognition, actions and events which are being used by criminals can be detected and indicating that an incident is taking place.
By utilising similar data from the outside, incidents happening in other locations, in other factories and companies can be recorded and similar patterns (signatures) can be signaled amongst trusted partners. This allows for preventative instructions inside the intrusion prevention systems, which will be able to block IP addresses, block users and applications.
Finally the monitoring and logging is important for forensics. Once an incident has happened, the recorded sessions allow to understand what exactly happened, collect evidence and use as a means for future preventive actions.
In Digital Manufacturing Platforms a logging facitlity should be enabled allowing to record the manipulations and transactions that have happened inside the platform itself, and recording the access and identity of the persons who have been controlling the platform itself.