Research And Development For GeoSpatial Data Security P. Venkatachalam and B. Krishna Mohan CSRE, IIT Bombay July 2011
Introduction Advancements in sensor technology, satellite remote sensing and field data measurements Large amounts of geospatial data Highspatial resolution and frequent coverage Key applications Military operations and internal security Disaster management and environmental monitoring Rural and urban planning Commercial applications. Involves diverse organizations, data repositories and users with different responsibilities for security purposes.
Need for research in spatial data security and privacy Variety of models and techniques to Manage Access Share geospatial data Geospatial information can be exploited by attackers for Disrupting critical infrastructures Compromising the security and privacy of people, property and systems. Important to address data security, access control Important to address data security, access control and privacy.
Current practices and motivational scenarios in spatial data security High-resolution satellite imagery + Vector data + demographic data + Uncontrolled access Potential for security threats, data misuse and privacy violations. Necessary to extend security mechanisms to Interoperable GIS repositories GIS applications. Role-based access controls for interoperable GIS p repositories are important security requirements.
GIS and Cryptology Cryptology : Si Science that incorporates both hc Cryptography and Cryptanalysis to handle the text based data. Cryptography: Conversion of data into a scrambled code that can be sent across a public or private network. Cryptanalysis: Study of ciphers, ciphertext, or cryptosystems to find weaknesses in them that will permit retrieval of the plain text from the ciphertext, without necessarily knowing the key or the algorithm. Map data represents space with embedded objects that have varying degrees of importance and sensitivity more complex than text encryption
Suggested Research Approaches Spatial Data Indexing and Geometric Transformations Spatial Data Transformations of Geometric Objects Cryptographic Transformation Watermarking Methods for Raster and vector Data Spatial Domain Methods Frequency Domain Methods
Framework for private spatial data outsourcing Private Data Owner Upload Original Transformed Data Dataset P Data set P Transformation Dt Data Server Send The Key Query Service Provider Original Dataset P Authorized User Transformed Data set P Query Result Inverse Transformation
Example Hierarchical Space Division
Hierarchical Space Division (HSD) Spatial Transformation Visualization of North America points
Cryptographic Transformation Employs conventional cryptographic technique CRT provides provable confidentiality guarantees, inherited from the encryption technique CRT does not allow any type of location-based attack such as the general attack. Query processing at the SP becomes difficult. CRT employs R*- tree In CRT, data points a,, b,, c are stored in an encrypted index. To find the result for query q, the root (Node A) is sent to user U, who decrypts A and determines that the MBR of node B intersects q. Then U retrieves node B from the SP and computes the query result as b. The number of communication cat o rounds equals the tree height.
Cryptographic Transformation
Spatial Data Watermarking on Vector and draster Datasets Protect spatial data against illegal distribution and secure their contents t by a. Spatial Domain Methods b. Frequency Domain Methods Requirements Precision should be preserved Positional accuracy should be maintained Good robustness Invisible and blind watermarking Wt k hl t l t th f th i d / Watermark may help to locate the sourceof unauthorised copy / leak of security restricted data.
Research and Development Objectives Development of mathematical and cryptographic algorithms for spatial data security for storage and online data sharing Develop efficient procedures to Secure spatial dataset Support for query processing online Establish robustness of techniques to various attack models. Work on watermarking methods to secure both vector and raster data Develop prototype systems for demonstration of methodology