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Cybersecurity risk management in land administration systems is crucial for maintaining the integrity of spatial cadastral data, which faces increasing threats owing to the digital transformation of LAS. This research validates the findings of this preliminary step in the form of a cyber risk management methodology that combines BPMN 2.0 with model business processes implemented by a compliance-based approach using EBIOS Risk Manager. A practical case of land parcel subdivision in Indonesia is analysed to serve as a proof of concept for our proposed methodology. Vulnerabilities are identified and are characterised by a concentration of manual tasks and the absence of systematic controls, resulting in significant risks to data integrity. These findings underscore the urgent need for a proactive approach to strengthen the cyber resilience of LAS. This study attempts to develop a fit-for-purpose reference methodology for cyber risk management specifically tailored to LAS to identify and treat vulnerabilities, threats, risks, and impacts.

This paper presents the results from a quality and usability analysis of participatory land registration (PaLaR) in Indonesia’s rural areas, focusing on data quality, cost, and time. PaLaR was designed as a systematic community-centered land titling project collecting requisite spatial and legal data. PaLaR was piloted in two communities situated in Tanggamus and Grobogan districts in Indonesia. The research compared spatial data accuracy between two approaches, PaLaR and the normal systematic land registration approach (PTSL) with respect to point accuracy and polygon area. Supplementary observations and interviews were undertaken in order to evaluate the effectiveness of the spatial and legal data collection, as well as logical consistency of the data collected by the community committee, using a mobile application. Although the two pilots showed a lower spatial accuracy than the normal method (PTSL), PaLaR better suited local circumstances and still delivered complete spatial and legal data in a more effective means. The accuracy and efficiency of spatial data collection could be improved through the use of more accurate GNSS antennas and a seamless connection to the national land databases. The PaLaR method is dependent on, amongst other aspects, inclusive and flexible community awareness programs, as well as the committed participation of the community and local offices.