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Jul 22 2023 | by Arjun Shenoy CKM

RPA Technology: Enhancing National Security through Automation 

In collaboration with Govini, the American National Defense Industrial Association released its annual Vital Signs report for 2022, which assesses important factors like information security, demand, productivity, supply chain, and emerging technologies that have an impact on the overall health of the defense industrial base.   As the report unfolds, it brings forth the numerous challenges faced by the defense and intelligence industry in protecting national security, safeguarding critical infrastructure, and gathering intelligence in today's rapidly changing world. As the world becomes increasingly complex and unpredictable, the defense and intelligence industries are constantly seeking innovative ways to stay ahead of evolving threats. 

There is no tolerance even for the smallest margin for error or inaccuracy when it comes to the security and defense of the country because the stakes are so high that they might be the precursor to a catastrophe.  

In 2019, the U.S. Army's Asymmetric Warfare Group accidentally released a training manual that contained sensitive information about U.S. military operations. The release was caused by a small human error in the unit's administrative procedures, which resulted in the manual being posted to a public-facing website. Specifically, the error occurred when a member of the unit's administrative staff uploaded the manual to a publicly accessible folder on the Army's official website, rather than to a secure, password-protected folder intended for internal use only. 

The release of the manual was a serious breach of operational security, as it provided potential adversaries with detailed information about U.S. military capabilities and tactics. The Army quickly realized the mistake and removed the manual from the website, but not before it had been downloaded and disseminated by numerous individuals. 

Such occurrences underscore the need for RPA technology. By automating repetitive and normal operations, and lowering the likelihood of human error, UiPath, the market-leading robotic process automation (RPA) tool can play a crucial role in this sector. Here are some use cases: 

Use Case 1: Security Clearance Processing 

  • Multiple stakeholders, including applicants, security officers, reviewers, and administrators, are involved in the security clearance process, which makes it an intricate and multi-stage process. The purpose of the security clearance procedure is to make sure that people who are given access to confidential information or restricted places do not constitute a security risk, and this is how UiPath can be used to automate the security clearance process: 

  • Verifying the applicant's identification and making sure they meet the requirements for clearance is the first stage in the process. This typically entails going over numerous documents, including birth certificates, passports, and driver's licenses. By leveraging Document Understanding (DU) to extract data from these documents, UiPath may be utilized to automate this procedure. DU transforms the text in photos into data that can be further analyzed using machine learning algorithms. 

  • The subsequent stage is typically a background investigation of the candidate. This includes pulling up data from databases such as credit ratings, work histories, and criminal histories. By accessing numerous databases and using API calls or web scraping techniques to retrieve the pertinent data, UiPath can be utilized to automate this procedure. To retrieve criminal records, for instance, UiPath can access databases like the National Crime Records Bureau (NCRB). To learn more about an applicant's internet presence, UiPath can also be used to scrape information from open websites or social networking platforms. 

  • The data is often entered into the security clearance system when the background check is done. This involves entering data into the system and can be made automated using UiPath. The data can also be validated to make sure it adheres to the necessary standards and format. 

  • Finally, it can be used to notify the applicant and the reviewer of the application's status. UiPath can be used to create dashboards and reports that offer a real-time picture of the security clearance procedure, including the number of applications processed, the number of applications that have been approved, and the typical processing time. 

Use Case 2: Threat Detection & Analysis 

Re: Infer, a communications mining tool from UiPath is a potent tool that can boost precision and effectiveness when it comes to threat analysis. UiPath can automate the procedure of gathering and studying substantial amounts of data from numerous sources, including social media feeds, news organizations, and intelligence reports. Re: Infer, on the other hand, is a platform for natural language processing (NLP) and machine learning (ML) that may assist in drawing conclusions and spotting patterns from unstructured data including text, photos, and videos. It can be used to analyze the data gathered by UiPath and extract crucial details like entities, feelings, and themes. Intelligence Units may build a potent automated threat analysis system using UiPath and Re: Infer that can swiftly and accurately analyze massive volumes of data and offer useful insights to decision-makers. 

  • The procedure of gathering data from numerous sources and storing it in a centralized location, such as a database or a data lake, can be automated using UiPath. It makes sense to pre-process the data after it has been acquired to eliminate irrelevant data, duplicates, and inconsistencies. 

  • Decision-makers can better grasp and act on the insights when they are provided visually like graphs, charts, and dashboards. UiPath can be integrated with tools like Tableau, Power BI, or Excel to automate the process of producing visualizations. The system's findings can be configured to send alerts or notifications when particular thresholds are reached. 

Use Case 3: Geospatial Analysis Automation 

Geographic data, including satellite imagery, GPS data, and geospatial databases, are analyzed and interpreted in geospatial analysis. Using UiPath to automate geospatial analysis can help expedite many activities associated with this use case. By facilitating the connection of UiPath with other geospatial programs, tools, and data sources, such as Geographic Information System (GIS Software), online mapping tools, satellite imagery providers, meteorological data sources, and third-party APIs, UiPath Integration Service can further improve geospatial analysis automation. 

  • Custom activities and processes that communicate with GIS applications can be created using SDKs in UiPath. Additionally, geospatial data formats used by GIS software include shapefiles, GeoJSON, and KML, which UiPath can use to automate data processing and analysis tasks. Finally, GIS software may include particular GIS operations that can be used to create automated geospatial models, such as spatial joins, buffer analysis, or raster processing. 

  • To comprehend patterns, trends, and long-term climatic changes, climate analysis includes processing and analyzing vast amounts of climate data. Data collection, cleaning and pre-processing, data visualization, and statistical analysis procedures can all be automated using UiPath to speed up climate analysis. Hourly/Daily data collection, pattern generation, and forecasting models can be built by leveraging out-of-the-box ML packages available. 


By the inclusion of more use cases like Logistics Management, Surveillance & many more, RPA may play a crucial role in strengthening the security of sensitive data by offering a safe, auditable, and traceable mechanism for managing data. Furthermore, it aids organizations in adhering to rigid guidelines and standards governing the handling of sensitive data. 

As the defense and intelligence sectors are predicted to keep expanding, RPA has a tremendous potential to revolutionize the industry given the introduction of new technologies and developments in AI and machine learning. 

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