A Low Computational Cost RGB Color Image Encryption Scheme Process based on PWLCM Confusion, Z/nZ Diffusion and ECBC Avalanche Effect

In this work, three sub-processes are serially integrated into just one process in order to construct a robust new image encryption scheme for all types of images, especially color images. This integration architecture aims to create a robust avalanche effect property while respecting the constraints of confusion and diffusion that have been identified by Claude Shannon as properties required of a secure encryption scheme. The performance of the proposed encryption scheme is measured and discussed with several analyses, including computational cost analysis, key space analysis, randomness metrics  analysis, histogram analysis, adjacent pixel correlation, and entropy analysis. The experimental results demonstrated and validated the performance and robustness of the proposed scheme

A Low Computational Cost RGB Color Image Encryption Scheme Process based on PWLCM Confusion, Z/nZ Diffusion and ECBC Avalanche Effect

In this work, three sub-processes are serially integrated into just one process in order to construct a robust new image encryption scheme for all types of images, especially color images. This integration architecture aims to create a robust avalanche effect property while respecting the constraints of confusion and diffusion that have been identified by Claude Shannon as properties required of a secure encryption scheme. The performance of the proposed encryption scheme is measured and discussed with several analyses, including computational cost analysis, key space analysis, randomness metrics  analysis, histogram analysis, adjacent pixel correlation, and entropy analysis. The experimental results demonstrated and validated the performance and robustness of the proposed scheme

Cryptanalysis of an Image Cipher using Multi entropy Measures and the Countermeasures

The use of same keys or equivalent keys should not be occurred in cryptographic communications because a cipher system utilising such keys to secure messages can be attacked even it possesses excellent cryptographic characteristics for extracting intelligible information from encrypted messages. Identification of crypts formed with such keys is an important task of traffic analysis of cryptographic communications to check the applicability of two-messages-on-same-key (TMSK) attack. To avoid its applicability, adequate safeguards are required. In the paper, we cryptanalyze stream encryption based cipher system and propose an intelligent identification methodology using multi-entropy measures and soft decision criteria for identification of encrypted images of same or equivalent keys. Experimental test results show that the crypts formed with same keys can be identified successfully with high precision. We also present the countermeasures against TMSK attack

Implementation of the advanced encryption standard algorithm on an FPGA for image processing through the universal asynchronous receiver-transmitter protocol

Communication among end users can be based either on wired or wireless technology. Cryptography plays a vital role in ensuring data exchange is secure among end users. Data can be encrypted and decrypted using symmetric or asymmetric key cryptographic techniques to provide confidentiality. In wireless technology, images are exchanged through low-cost wireless peripheral devices, such as radio frequency identification device (RFID), nRF, and ZigBee, that can interface with field programmable gate array (FPGA) among the end users. One of the issues is that data exchange through wireless devices does not offer confidentiality, and subsequently, data can be lost. In this paper, we propose a design and implementation of AES-128 cipher algorithm on an FPGA board for image processing through the universal asynchronous receiver transmitter (UART) protocol. In this process, the advanced encryption standard (AES) algorithm is used to encrypt and decrypt the image, while the transmitter and receiver designs are implemented on two Xilinx BASYS-3 circuits connected with a ZigBee RF module. The encrypted image uses less memory, such as LUTs (141), and also consumes less chip power (0.0291 w), I/O (0.003), block RAM (0.001 w), data, and logic to provide much higher efficiency than wired communication technology. We also observe that images can be exchanged through the UART protocol with different baud rates in run time

Implementation of FPGA in the Design of Embedded Systems

The use of FPGAs (Field Programmable Gate Arrays) and configurable processors is an interesting new phenomenon in embedded development. FPGAs offer all of the features needed to implement most complex designs. Clock management is facilitated by on-chip PLL (phase-locked loop) or DLL (delay-locked loop) circuitry. Dedicated memory blocks can be configured as basic single-port RAMs, ROMs, FIFOs, or CAMs. Data processing, as embodied in the devices’ logic fabric, varies widely. The ability to link the FPGA with backplanes, high-speed buses, and memories is afforded by support for various single ended and differential I/O standards. Also found on today’s FPGAs are system-building resources such as high speed serial I/Os, arithmetic modules, embedded processors, and large amounts of memory. Here in our project we have tried to implement such powerful FPGAs in the design of possible embedded systems that can be designed, burned and deployed at the site of operation for handling of many kinds of applications. In our project we have basically dealt with two of such applications –one the prioritized traffic light controller and other a speech encrypting and decrypting system

Cyber Security

This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security

Machine Learning in Sensors and Imaging

Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens