Ncryption operation. Such solutions typically use scrambling encryption to encrypt the data, as well as the watermark information is embedded through shifting histogram [22] or modifying the pixel value [23]. This kind of method not just encrypts the general information, but additionally balances the security of encryption and the robustness of watermarking. However, the existing techniques are applicable to raster information but can’t be applied to vector maps as a result of differences in data representation and storage structure. As pointed out above, it is obvious that the invariant based CEW is superior for the other two schemes when it comes to balancing encryption security and watermark robustness. Depending on this, Ren et al. [24] analyzed the organization structure and storage structure of vector maps and proposed a CEW technique by deriving two invariants: the sum of inner angles and also the storage direction of two adjacent objects. This approach has high robustness against geometric attacks. However, the watermark embedding positions may be impacted by the number of vertices of each object, so this process has tiny resistance to the vertex addition and deletion. To sum up, the above CEW approaches nevertheless have the following shortcomings: (1) handful of algorithms can be applied straight to vector maps, and (two) couple of algorithms for vector maps are resistant to vertex attacks. Hence, this paper proposes a novel invariant based CEW method for vector maps to solve the above issues. To construct a CEW scheme for vector maps, the organization structure and storage structure with the vector maps areconcludes the paper and gives directions for Guadecitabine supplier additional operate. two. Connected Performs 2.1. ISPRS Int. J. Geo-Inf. 2021, ten, 718 Vector Map Data3 ofA vector map consists of a variety of information layers, and each layer consists of attrib information and geometry information [25,26], as shown in Figure 1a. The attribute information presents taken fully into account. Furthermore, in light of handful of algorithms for information maps points, storage data like ID, Text and Name. The geometryvector (e.g., which can be polyli resistant to is employed to decide the geolocation encryption, and vector it with and polygons) vertex attacks, we construct on the permutationinformation ofcombine maps, as sho the watermarking in Figure 1b. Points scheme to most fundamental element of geometry data, polylines will be the achieve better robustness to vertex attacks. The remainder of this paper is organized as follows. Section 2 specifics vector maps produced up permutationof vertices, and polygons are composedlogistic chaotic map and Points data, of a Erastin In Vitro series encryption of vector maps, the principle with the of closed polylines. usually normalization course of action of vector maps.just like the 3position ofthe fundamental concept along with the polyli the utilized to describe straightforward objects Section introduced parking lot, even though course of action of represent the complex objects, including 4 verifies the effectiveness and and polygons the algorithm proposed within this paper. Section roads, rivers, buildings and lakes versatility of proposed algorithmvector map is represented by Formula (1), (two) and (three), a The organizational kind of by implementing numerous experiments. Finally, Section 5 concludes the paper and gives directions for further perform. the number of vertices is represented by .2. Associated Operates two.1. Vector Map Data= | [1, ||]A vector map consists of a number of information layers, and every single layer consists of attribute = , | [1, | |] information and geometry information [25,26], as shown in Figure 1a. The attribute information presents the storage infor.
