Secure Dissemination and Protection of Raster Data using Merkle Hash Tree based Cryptowatermarking

Abstract

Due to rapid development in the Internet and other communication technologies, it becomes quite easy to copy and distribute multiple illegal copies of high value and sensitive data. Raster data is one of the high voluminous data and it requires huge efforts to sense and generate this data. Therefore, ownership protection as well as its integrity become one of the key problems in spatial information service. There are lot many schemes are available for watermarking and encryption individually, but if both are combined gives manifold advantages. This paper presents a cryptowatermarking scheme by combining watermarking and encryption to protect the copyright of raster data as well as to provide security dissemination level. We have proposed a scheme by employing double transposition, LSB substitution watermarking and Merkle Hash Tree for encryption and watermarking. It has been observed that the proposed scheme is not only robust against encryption attacks, but also has transparency, strongness, large data hiding capacity and correct extraction of watermark.

A cloud‐based solution for trustless indigenous data sovereignty: Protecting Māori biodiversity management data in Aotearoa New Zealand

“…In mapping, there is the additional burden of learning to understand the world from above. The god-trick (Haraway, 1988;Harley, 1989;Monmonier, 2018) offer good examples and frameworks for understanding how knowledge and power are embedded into maps, and there are several examples of how modern technologies and algorithms continue this trend (Kitchin & Dodge, 2014;Martin et al, 2023;Martin & Schuurman, 2017, 2020. In the specific case of indigenous knowledge, we recognize there are additional barriers to technological adoption with emergent technologies, similar to those reported by Tudge (2011) andSieber et al (2016).…”

“…Cryptographic hash functions produce this value by transforming the data contents into a fixed-length string, where even the slightest of changes results in a different hash value. This value can be used by the receiver to verify data content and has been proposed in data sovereignty solutions (Nugraha & Sastrosubroto, 2015), and for spatial data confidentiality (Chaudhari, 2020). While this technique promises a higher level of confidence, an adversary can replace both the geospatial data and their corresponding hash with a new set.…”