Implementation of an Enhanced MPF-Based Block Cipher to Encrypt Digital Images

It is well known that avalanche effect errors in received noisy ciphertexts will cause severe error propagation in block-ciphered encryption systems, thus resulting in a large reduction in the achievable throughput. However, little is known about the statistical properties of the underlying error sequences in decrypted plaintexts in block-ciphered systems when channel errors are present. A rigorous study of the statistical properties of the errors in block-ciphered crypto-systems operating in cipher block chaining (CBC) mode is provided. The equivalent channel transition probability is obtained and then used to derive error statistics including both error weight probabilities and gap distributions. The validity of the theoretical analyses is confirmed by the excellent match with results obtained by simulated data encryption standard (DES)-based and advanced encryption standard (AES)-based crypto-systems operating in CBC mode. The error statistics will be valuable in the design and performance evaluation of communication protocols, as well as in error-control schemes for block-ciphered crypto-systems in the presence of erroneous ciphertexts, where errors are intentionally left to enhance security against passive eavesdroppers.

The Consultative Committee for Space Data Systems (CCSDS) recommends AES algorithm as a cryptographic algorithm to maintain confidentiality and data security between spacecraft and ground systems. In implementation, there are several AES algorithm operating modes including Cipher-Block Chaining (CBC), Electronic Codebook (EBC), Cipher Feedback (CFB), Output Feedback (OFB), and counter mode (CTR). One of the operating modes of AES algorithm recommended by CCSDS is CTR because it has advantages in terms of efficiency of implementation and offers a high level of data security. LAPAN-A4 as the next generation of LAPAN satellites also uses CCSDS standard in terms of data exchange between satellites and ground stations including telemetry and telecommand (TTC) data and satellite payload data. In order to protect LAPAN-A4 satellite data, especially TTC data, in this paper AES algorithm was implemented in CTR operating mode on the FPGA which will then be implemented on LAPAN-A4 satellite onboard data handling (OBDH) as one of LAPAN-A4 satellite data security systems. To overcome the limited resource of FPGA, optimization is also done using basic iterative AES hardware reused method, which is to reuse hardware that has been designed n times for same operation for AES algorithm. From the results of implementation and optimization, efficiency of logic gates used is increasing almost a quarter less than the previous research.

Chapter 4 - Domain 3: Security Architecture and Engineering

Recently, massive research works have been accomplished for augmenting privacy and security requirements for cybersecurity applications in wireless communication networks. This is attributed to the fact that conventional security processes are not appropriate for robust, efficient, and reliable multimedia streaming over unsecure media. Therefore, this paper presents an efficient color image cryptosystem based on RC6 with different modes of operation. The proposed cryptosystem is composed of two phases: encryption and decryption. The encryption phase starts by decomposing the color plainimage with few details into its RGB components, which in turn, are segmented into 128-bit blocks. These blocks are then enciphered using RC6 with an appropriate mode of operation. After that, the corresponding enciphered blocks of RGB components are multiplexed for constructing the final cipherimage. This scenario is reversed in the decryption phase. The performance of the proposed cryptosystem is gauged via simulation using a set of encryption quality metrics. The simulation results reveal that the proposed cryptosystem with cipher block chaining (CBC), cipher feedback (CFB), and output feedback (OFB) modes can efficiently and effectively hide all information of the color images with few details even in the presence of some input blocks with similar data. On the other hand, the results show that the electronic codebook (ECB) mode is not effective at all in hiding all details of images. Finally, the obtained results ensure the applicability of the proposed cryptosystem and its efficiency in encrypting images in terms of security, encryption quality, and noise immunity.

This study implements the Advanced Encryption Standard (AES) algorithm in a web-based image encryption system utilizing an ephemeral key generated by an API. The research is motivated by the increasing threats to digital data security, such as identity theft and information manipulation, as well as the weaknesses of static key usage in AES encryption. The developed system consists of a client-side web application and a RESTful API server. The client side, built with HTML, CSS, and JavaScript, receives image input, requests the API for a key, and performs AES-256 encryption in Cipher Block Chaining (CBC) mode with a unique Initialization Vector (IV). The server side generates a random 256-bit key, stores it temporarily for approximately 30 seconds, and sends the key ID to the client. Testing was conducted on images sized 50 KB, 200 KB, and 1000 KB to measure encryption time. The results show that encryption time increases linearly with image size, with minimal overhead that does not affect performance. The ephemeral key approach enhances security by limiting the opportunity for unauthorized access to the key, while client-side encryption ensures that raw image data is never transmitted to the server. These findings demonstrate that implementing AES with ephemeral keys effectively improves the security of web-based image encryption.

Modern cryptographic systems in cloud and IoT environments must balance strong security with real-time performance, yet existing methods often require trade-offs that sacrifice speed for security or introduce latency through conservative designs. This paper presents RNS-AES-CBC-HMAC, a hybrid framework that integrates Residue Number System (RNS) arithmetic with AES-256 and HMAC-SHA256 to deliver both performance and robust security. Using a balanced modulus set $\{2^n - 1,\, 2^n,\, 2^n + 1\}$ for constant-time, carry-free arithmetic mitigates side-channel risks, while AES-256 in Cipher Block Chaining (CBC) mode ensures confidentiality and HMAC-SHA256 provides message integrity with minimal overhead. Implemented in Python 3.10 with PyCryptodome 3.18.0 and tested on an AMD Ryzen~5~2500U, the framework achieved encryption/decryption latencies of $55$--$593\,\mu\text{s}$ for 4--15 character payloads, representing 99\% improvement over previous RNS-based hybrids. It scales linearly in time and memory $\mathcal{O}(n)$, consumes only $21\,\text{KB}$, and produces ciphertext entropy of $7.999\,\text{bits/byte}$, surpassing NIST SP~800-22 standards. This dual-layer architecture effectively counters both passive and active threats, making it suitable for low-latency IoT edge devices and high-throughput cloud systems, merging theoretical number systems with practical cryptography for real-world deployment.

In this paper, the authors analyze the applicability of artificial intelligence algorithms for classifying file encryption methods based on statistical features extracted from the binary content of files. The prepared datasets included both unencrypted files and files encrypted using selected cryptographic algorithms in Electronic Codebook (ECB) and Cipher Block Chaining (CBC) modes. These datasets were further diversified by varying the number of encryption keys and the sample sizes. Feature extraction focused solely on basic statistical parameters, excluding an analysis of file headers, keys, or internal structures. The study evaluated the performance of several models, including Random Forest, Bagging, Support Vector Machine, Naive Bayes, K-Nearest Neighbors, and AdaBoost. Among these, Random Forest and Bagging achieved the highest accuracy and demonstrated the most stable results. The classification performance was notably better in ECB mode, where no random initialization vector was used. In contrast, the increased randomness of data in CBC mode resulted in lower classification effectiveness, particularly as the number of encryption keys increased. This paper provides a comprehensive analysis of the classifiers’ performance across various encryption configurations and suggests potential directions for further experiments.

This paper presents a 3 in 1 standalone FPGA system which can perform color image blur detection in parallel with compression and encryption. Both blur detection and compression are based on the 3-level Haar wavelet transform, which is used as a common building block to save the resources. The compression is based on performing the hard thresholding scheme followed by the Run Length Encoding (RLE) technique. The encryption is based on the 128-bit Advanced Encryption Standard (AES), which is considered one of the most secure algorithms. Moreover, the modified Lorenz chaotic system is combined with the AES to perform the Cipher Block Chaining (CBC) mode. The proposed system is realized using HDL and implemented using Xilinx on XC5VLX50T FPGA. The system has utilized only 25&#x0025; of the available slices. Furthermore, the system can achieve a throughput of 3.458 Gbps, which is suitable for real-time applications. To validate the compression performance, the system has been tested with all the standard <inline-formula> <tex-math notation="LaTeX">$256\times 256$ </tex-math></inline-formula> images. It is shown that depending on the amount of details in the image, the system can achieve 30dB PSNR at compression ratios in the range of (0.08-0.38). The proposed system can be integrated with digital cameras to process the captured images on-the-fly prior to transmission or storage. Based on the application, the blurred images can be either marked for future enhancement or simply filtered out.

Data encryptor safeguards communications

With the increasing importance of data security in digital image transmission and storage, this research presents an implementation of an image encryption and decryption program using the Advanced Encryption Standard (AES) algorithm combined with Message Authentication Code (MAC) for enhanced security. The program utilizes AES in CipherBlock Chaining (CBC) mode to ensure confidentiality and integrity of the image data. The unique key and initialization vector (IV) enhance the security of the encryption process. Additionally, the inclusion of MAC ensures data integrity and prevents unauthorized modifications during transmission or storage. The program offers a user-friendly web-based interface for easy usability. The implemented solution provides a high level of security for image data and can be applied in various applications requiring secure image transmission and storage. The effectiveness and reliability of the program are demonstrated through experimental results and evaluation.

With the development of high-speed network technologies, there has been a recent rise in the transfer of significant amounts of sensitive data across the Internet and other open channels. The data will be encrypted using the same key for both Triple Data Encryption Standard (TDES) and Advanced Encryption Standard (AES), with block cipher modes called cipher Block Chaining (CBC) and Electronic CodeBook (ECB). Block ciphers are often used for secure data storage in fixed hard drives, portable devices, and safe network data transport. Therefore, to assess the security of the encryption method, it is necessary to become familiar with and evaluate the algorithms of cryptographic systems. Block cipher users need to be sure that the ciphers they employ are secure against various attacks. A Fully Connected Neural Network (FCNN) model was initially used to assess how well the models were classified. Then, all models, including encoder models, were assessed using True Positive (TP) measures for successful classification of the discovered encoder and False Positive (FP) measures for imprecise categorization. The accuracy value, retrieval, loss, precision value, and F1 score were then calculated using a confusion matrix to assess the model's efficacy (abbreviated as F1). ECB results with an accuracy of 85% and CBC results with an accuracy of 88% were produced, and the parameters of the FCNN model were tweaked to provide better results. These results helped to identify the encryption algorithm more precisely and evaluate it.

A novel method for one-way hash function construction based on spatiotemporal chaos

This research presents a technique for concealing messages within images by combining AES encryption in Cipher Block Chaining (CBC) mode with Least Significant Bit (LSB) embedding. A key feature of this method is the dynamic generation of the encryption key based on intrinsic statistical properties of the image—specifically, the standard deviation of the RGB channels—This eliminates the necessity for external key exchange, making the encryption process inherently dependent on the image itself.

Security is one important issue regarding data and information today. Steganography along with cryptography is used to hide and secure information. It is already an established practice to put watermark and to secure a single document using encryption. However, for large information requiring multiple documents has not received any attention. Here a program which can do steganography to multiple PDF documents to increase its steganography capacity is proposed, it is named MPDFStego. One of the steganography technique chosen in this research is the Least Significant Bit (LSB). LSB technique can be applied to Portable Document Format (PDF) by making use of its Tj Operator. Secret text is encrypted using Advanced Encryption Standard with 128-bit key size in Cipher Block Chaining (CBC) mode before it is embedded into the PDF document(s). Recompression and decompression of the PDF document(s) are done outside MPDFStego, with the help of QPDF tool. Testing and evaluation show that the MPDFStego is capable of hiding the secret text into one or many PDF documents (s).

The field of secure digital communication and data security has placed significant emphasis on the issue of image encryption. The present work introduces a unique methodology for improving image encryption by utilizing the Advanced Encryption Standard (AES) cipher in the Electronic Codebook (ECB) mode. The suggested methodology leverages the inherent resilience of AES while integrating a novel DNA-segment-based augmentation to reinforce the encryption process. This technique aims to mitigate the constraints associated with the Electronic Codebook (ECB) mode in picture encryption, with the ultimate goal of attaining an elevated standard of security and confidentiality. The efficacy of the suggested methodology is assessed through extensive experimentation, illuminating its potential to offer a sophisticated kind of image encryption that is well-suited for contemporary data security concerns.