SSGAN: Secure Steganography Based on Generative Adversarial Networks

In this paper, a novel strategy of Secure Steganograpy based on Generative Adversarial Networks is proposed to generate suitable and secure covers for steganography. The proposed architecture has one generative network, and two discriminative networks. The generative network mainly evaluates the visual quality of the generated images for steganography, and the discriminative networks are utilized to assess their suitableness for information hiding. Different from the existing work which adopts Deep Convolutional Generative Adversarial Networks, we utilize another form of generative adversarial networks. By using this new form of generative adversarial networks, significant improvements are made on the convergence speed, the training stability and the image quality. Furthermore, a sophisticated steganalysis network is reconstructed for the discriminative network, and the network can better evaluate the performance of the generated images. Numerous experiments are conducted on the publicly available datasets to demonstrate the effectiveness and robustness of the proposed method

A novel semi-fragile forensic watermarking scheme for remote sensing images

Peer-reviewedA semi-fragile watermarking scheme for multiple band images is presented. We propose to embed a mark into remote sensing images applying a tree structured vector quantization approach to the pixel signatures, instead of processing each band separately. The signature of themmultispectral or hyperspectral image is used to embed the mark in it order to detect any significant modification of the original image. The image is segmented into threedimensional blocks and a tree structured vector quantizer is built for each block. These trees are manipulated using an iterative algorithm until the resulting block satisfies a required criterion which establishes the embedded mark. The method is shown to be able to preserve the mark under lossy compression (above a given threshold) but, at the same time, it detects possibly forged blocks and their position in the whole image.Se presenta un esquema de marcas de agua semi-frágiles para múltiples imágenes de banda. Proponemos incorporar una marca en imágenes de detección remota, aplicando un enfoque de cuantización del vector de árbol estructurado con las definiciones de píxel, en lugar de procesar cada banda por separado. La firma de la imagen hiperespectral se utiliza para insertar la marca en el mismo orden para detectar cualquier modificación significativa de la imagen original. La imagen es segmentada en bloques tridimensionales y un cuantificador de vector de estructura de árbol se construye para cada bloque. Estos árboles son manipulados utilizando un algoritmo iteractivo hasta que el bloque resultante satisface un criterio necesario que establece la marca incrustada. El método se muestra para poder preservar la marca bajo compresión con pérdida (por encima de un umbral establecido) pero, al mismo tiempo, detecta posiblemente bloques forjados y su posición en la imagen entera.Es presenta un esquema de marques d'aigua semi-fràgils per a múltiples imatges de banda. Proposem incorporar una marca en imatges de detecció remota, aplicant un enfocament de quantització del vector d'arbre estructurat amb les definicions de píxel, en lloc de processar cada banda per separat. La signatura de la imatge hiperespectral s'utilitza per inserir la marca en el mateix ordre per detectar qualsevol modificació significativa de la imatge original. La imatge és segmentada en blocs tridimensionals i un quantificador de vector d'estructura d'arbre es construeix per a cada bloc. Aquests arbres són manipulats utilitzant un algoritme iteractiu fins que el bloc resultant satisfà un criteri necessari que estableix la marca incrustada. El mètode es mostra per poder preservar la marca sota compressió amb pèrdua (per sobre d'un llindar establert) però, al mateix temps, detecta possiblement blocs forjats i la seva posició en la imatge sencera

A chronology of climatic downturns through the mid- and late- Holocene: tracing the distant effects of explosive eruptions from palaeoclimatic and historical evidence in northern Europe

Geochronological data of the conifer tree rings in a region sensitive to climatic effects of explosive eruptions were analysed for sudden growth reductions in association with extraordinarily cool reconstructed summer temperatures since 5500 B.C. Tree-ring data came from the stems of living trees and subfossil tree remains collected as increment cores and discs, respectively, from an area of northernmost Finnish Lapland (70-68°N to 30-20°E). Calendar year dates when the tree-ring signatures (i.e., growth reductions and reconstructed temperatures) were concurrent were compared with sulphate data from Greenland ice cores. Previous new evidence are in agreement in demonstrating volcanism behind late-Holocene events in 1601 A.D. and 536 A.D., suggesting that the same causal relationship can be implied further back in time. Our data show that earlier events were found to have occurred in the years 330 B.C., 874 B.C., 1464 B.C., 1584 B.C., 2564 B.C. and 2850 B.C. Interestingly, events of lesser magnitude followed the three major events in 542 A.D., 1453 B.C. and 1579 B.C. by a few years. Natural disasters, and grain crop failures, occurred as a result of these events, as has been documented for the summer of 1601 A.D. through Finnish historical data and broadly in the Northern Hemisphere. Climate has surprised humans during historic and likely prehistoric times, causing sudden alterations in agriculture, ecology and economy, and may do so in the future. We argue that the climate change with the most magnified impacts on society may be a negative temperature anomaly that abruptly decreases resource availability over wide spatial scales. </p