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

Defending Against Firmware Cyber Attacks on Safety-Critical Systems

In the past, it was not possible to update the underlying software in many industrial control devices. Engineering teams had to ‘rip and replace’ obsolete components. However, the ability to make firmware updates has provided significant benefits to the companies who use Programmable Logic Controllers (PLCs), switches, gateways and bridges as well as an array of smart sensor/actuators. These updates include security patches when vulnerabilities are identified in existing devices; they can be distributed by physical media but are increasingly downloaded over Internet connections. These mechanisms pose a growing threat to the cyber security of safety-critical applications, which are illustrated by recent attacks on safety-related infrastructures across the Ukraine. Subsequent sections explain how malware can be distributed within firmware updates. Even when attackers cannot reverse engineer the code necessary to disguise their attack, they can undermine a device by forcing it into a constant upload cycle where the firmware installation never terminates. In this paper, we present means of mitigating the risks of firmware attack on safety-critical systems as part of wider initiatives to secure national critical infrastructures. Technical solutions, including firmware hashing, must be augmented by organizational measures to secure the supply chain within individual plants, across companies and throughout safety-related industries

A Short Survey on Perceptual Hash Function

The authentication of digital image has become more important as these images can be easily manipulated by using image processing tools leading to various problems such as copyright infringement and hostile tampering to the image contents. It is almost impossible to distinguish subjectively which images are original and which have been manipulated. There are several cryptographic hash functions that map the input data to short binary strings but these traditional cryptographic hash functions is not suitable for image authentication as they are very sensitive to every single bit of input data. When using a cryptographic hash function, the change of even one bit of the original data results in a radically different value. A modified image should be detected as authentic by the hash function and at the same time must be robust against incidental and legitimate modifications on multimedia data. The main aim of this paper is to present a survey of perceptual hash functions for image authentication.Keywords: Hash function, image authentication*Cite as: Arambam Neelima, Kh. Manglem Singh, “A Short Survey on Perceptual Hash Function†ADBU-J.Engg Tech, 1(2014) 0011405(8pp

Two-Factor Biometric Identity Verification System for the Human-Machine System Integrated Deep Learning Model

The Human-Machine Identity Verification System based on Deep Learning offers a robust and automated approach to identity verification, leveraging the power of deep learning algorithms to enhance accuracy and security. This paper focused on the biometric-based authentical scheme with Biometric Recognition for the Huma-Machinary Identification System. The proposed model is stated as the Two-Factor Biometric Authentication Deep Learning (TBAuthDL). The proposed TBAuthDL model uses the iris and fingerprint biometric data for authentication. TBAuthDL uses the Weighted Hashing Cryptographic (WHC) model for the data security. The TBAuthDL model computes the hashing factors and biometric details of the person with WHC and updates to the TBAuthDL. Upon the verification of the details of the assessment is verified in the Human-Machinary identity. The simulation analysis of TBAuthDL model achieves a higher accuracy of 99% with a minimal error rate of 1% which is significantly higher than the existing techniques. The performance also minimizes the computation and processing time with reduced complexity

Foundations, Properties, and Security Applications of Puzzles: A Survey

Cryptographic algorithms have been used not only to create robust ciphertexts but also to generate cryptograms that, contrary to the classic goal of cryptography, are meant to be broken. These cryptograms, generally called puzzles, require the use of a certain amount of resources to be solved, hence introducing a cost that is often regarded as a time delay---though it could involve other metrics as well, such as bandwidth. These powerful features have made puzzles the core of many security protocols, acquiring increasing importance in the IT security landscape. The concept of a puzzle has subsequently been extended to other types of schemes that do not use cryptographic functions, such as CAPTCHAs, which are used to discriminate humans from machines. Overall, puzzles have experienced a renewed interest with the advent of Bitcoin, which uses a CPU-intensive puzzle as proof of work. In this paper, we provide a comprehensive study of the most important puzzle construction schemes available in the literature, categorizing them according to several attributes, such as resource type, verification type, and applications. We have redefined the term puzzle by collecting and integrating the scattered notions used in different works, to cover all the existing applications. Moreover, we provide an overview of the possible applications, identifying key requirements and different design approaches. Finally, we highlight the features and limitations of each approach, providing a useful guide for the future development of new puzzle schemes.Comment: This article has been accepted for publication in ACM Computing Survey