Spatial data: What is it and why is cybersecurity so vital to it?
Spatial data underpins logistics, urban planning, disaster response and national security. Image: REUTERS/Claro Cortes IV CC/FA
- Spatial data is transformative and powerful, underpinning critical systems such as logistics, urban planning, disaster response and national security.
- Cyber risks to spatial data are severe, ranging from privacy breaches and GPS spoofing to denial-of-service attacks.
- Robust cybersecurity is essential through governance, management, intelligence and emerging technologies.
In today’s world, almost everything is connected – our smartphones and cars link to our homes and services around us and at the core of it all is spatial data.
Spatial data is the digital footprint that pinpoints geographic locations. Unlike other data, it is the most valuable type of information for critical applications such as modern logistics, urban planning, climate monitoring, precision agriculture, disaster management and national security.
This sensitive information not only reveals “where” things are but also answers tangential questions, including “when”, “how”, “who” and “why.” It illuminates hidden patterns, forecasts events and discloses relationships.
But just how is spatial data transforming our world? What are the cybersecurity risks and how do we mitigate them?
The transformative power of spatial data
Research and advisory firm Gartner ranked spatial computing as one of the most impactful and transformative emerging technologies. Spatial data is no longer a static map; it’s a dynamic layer of intelligence that is fundamentally transforming our interaction with the physical world.
This transformation is driven by several remarkable technologies, including advanced sensors, global positioning systems, drones, the remote sensing method of light detection and ranging, Internet of Things devices and 5G networks, which constantly collect vast volumes of real-time location data.
This raw location data is then processed using cloud computing, big data analytics and artificial intelligence (AI), which, when combined, provide the foundation for detecting, predicting and interpreting complex spatial queries.
The synergy between technology and advanced computing enables powerful applications, such as digital twins – virtual replicas of physical environments.
Why cybersecurity matters for spatial data
1. Confidentiality breaches and privacy invasion
The World Economic Forum has extensively highlighted the growing risks to individual and corporate privacy.
Unauthorized access to location data can reveal an individual’s daily routine, home address, places of work or visits to sensitive locations. On a corporate level, it can expose the travel patterns of executives, the locations of critical assets or facilities or critical supply chain routes.
This can lead to targeted social engineering, cyber espionage, physical threats or even a geopolitical invasion of privacy.
2. Spoofing and manipulation
A more serious threat than data leakage or data loss is the malicious alteration of geospatial data, which can deceive critical systems and individuals, potentially compromising their integrity and accuracy.
A prime example is global positioning system (GPS) spoofing, where attackers broadcast false satellite signals to trick a receiver into calculating an incorrect location. The consequences of exploiting this vulnerability are severe, as it could mislead aircraft, ships and autonomous vehicles, potentially leading to catastrophic consequences.
Hence, a cyberattack can cascade across entire industries and services reliant on precise location data, disrupting everything from global supply chains to emergency response. Ultimately, this threat extends far beyond service interruption, posing a direct and significant risk to public safety.
3. Availability attacks
A cyber attack on the availability of spatial data can paralyse modern operations. Jamming GPS signals can ground flights, halt port operations, disable location-based emergency services or even worse, disconnect the entire network.
As highlighted in a recent Forum article, a space agency was interrupted for three days to contain a cyberattack breach and secure its data. Such incidents forced the agency to disconnect its network and interrupt its services.
For any organization or service that relies on geographical location data, a denial-of-service attack is a direct attack on its core operations.
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How to secure associated risks
1. Data governance
As data is a valuable asset, we cannot overlook the sovereignty of spatial information. Regulatory bodies must develop robust controls and policies tailored to the unique characteristics of geolocation data. Furthermore, organizations must classify their spatial data, recognizing that not all of it carries the same level of risk.
For instance, the location of a retail store is far less sensitive than the coordinates of critical infrastructure or the real-time tracking of things or individuals. Ultimately, professionals who manage this data require specialized training to comprehend the unique characteristics of spatial data and to apply targeted cybersecurity best practices.
2. Data management
Technology and systems act like protective shields for data. They keep information safe from unauthorized access, use, changes or destruction, and provide the foundation needed to enforce security policies at every stage of the data lifecycle.
A foundational step is using strong encryption to protect data both while it’s being transferred and while it’s stored. This is supported by granular access controls that ensure only authorized people can view, change or analyse sensitive spatial data.
Furthermore, mechanisms for regular integrity checks, tamper detection and recovery plans must be in place to identify any unauthorized alterations, thus ensuring data accuracy, availability, integrity and reliability.
3. Data intelligence
Threat intelligence plays a critical role in transforming the security of geolocation data from a reactive into a proactive, evidence-based defence. It provides clear, specific information about potential attackers and the methods they employ, allowing an organization to anticipate and counter threats more effectively.
This knowledge helps prioritize fixing the most critical security weaknesses, detect attacks faster using known warning signs and create more targeted safety policies.
Emerging trends in securing spatial data
- AI: AI algorithms can analyze vast amounts of data to identify patterns and anomalies that might indicate a sophisticated cyberattack, enabling faster and more proactive threat detection.
- Blockchain: The blockchain is known for powering cryptocurrencies, which offer a decentralized and immutable ledger. This makes it incredibly difficult to alter spatial information, providing a high degree of data integrity for transactions and other sensitive information.
- Safe data analysis: Techniques such as differential privacy and masking that enable organizations to analyse location information without revealing individual, critical assets or compromising sensitive data.
Globally, we embrace the power of spatial data to build more innovative, efficient and sustainable societies; the importance of robust cybersecurity measures cannot be overstated.
Recognizing the unique vulnerabilities associated with location-based information and proactively implementing strong security practices is essential to unlocking the full potential of spatial data while safeguarding our digital future.
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Akshay Joshi
October 3, 2025