there are three main ways that software robots can help alleviate threats across cybersecurity domains like digital identity and access, software and product security, data identification and protection, etc.:
● Compensate for the anticipated shortage of cybersecurity professionals;
● Considerably reduce the average time to detect threats;
● Limit employee involvement in the management of personally identifiable information (PII).
The fact that all the activity of software bots is tracked and safely logged is an additional argument for the contribution of RPA to reduce cyber security risks, because it allows to avoid PII data meddling. In order to better grasp these directions of robot assistance let us now zoom in on some examples of RPA security-related application areas.
The discovery and inventory applications work in highly predictable, repetitive, rule based way, so they are perfect candidates for robotic process automation. Software robots can continuously monitor the inventory and update it whenever they discover risky areas. Risk classification can also be automated by applying cognitive learning to previously detected data.
Because of their rule based nature, all subprocesses of certification are open to automation. Replacing manual validation checks of precertification data, campaign checks during access certifications and reviews, certification configuration management, as well as post certification reconciliation and reporting with automated processing diminishes unauthorized access and PII data looting. The outcome is an increase in the operational and cost efficiency gains by up to 45%.
Leveraging RPA can boost the efficiency of checking the suitability of access data. Consequently, during the review process managers are freed to focus on higher-risk access concerns, e.g., malicious attacks. Whenever bots notice inconsistencies while validating access data, they can also be trained to promptly inform users by email.
Robots can be deployed to detect sensitive data, and either validate it or remove it if stored in unauthorized locations. Cognitive learning can refine the automated processing by categorising confidential information.
Another way in which robotic process automation reduces cyber security risks is by capturing threat intelligence. If an antivirus system alert is encountered, bots can prevent the actual intrusions and/ or the spread of viruses across the business computer network. By running a fast-paced analysis of the encountered malware alerts, bots are able to select the most relevant information bits and, based on this, make response decisions as to when and how to address the threats. For instance, detected hostile users’ data access can be remotely disabled or locked via email or SMS.
By using security automation to deal with operational tasks, you remove the human element from the process, which has some significant advantages. Many of the functions performed by an IT security worker can be automated, which include the prevention of threats, detection of threats, and the remedy of threats. Often the day-to-day processes are repetitive in nature and can take too long to complete manually. Paired together with an increase in the number of alerts and small security teams, organizations cannot perform efficiently and become at risk of successful attacks. Automation will remove these challenges, as the software is designed to handle the massive amounts of manual work, can respond quickly to alerts and can function without direct user involvement. The bottom line is that automating your cybersecurity will improve the productivity and value of the security team.
Combining machine learning (ML) and artificial intelligence (AI) is how RPA can enable automation – taking human effort out of the equation. But which cybersecurity tasks can be automated with an RPA, and how does it benefit system security?