This article addresses the critical issue of securing backup storage for confidential data, a key concern in safeguarding the operations of critical information systems dealing with extensive amounts of sensitive information. The study proposes a novel cryptographic fault-tolerant backup storage system for confidential data, leveraging cryptographic algorithms and protocols. These protocols enable message encryption, ensuring decryption is only possible after a specified time period. The proposed system combines various distributed key generation protocols, proactive secret sharing protocols, asymmetric encryption algorithms, and digital signature algorithms. By employing such cryptographic protocols, it becomes feasible to develop and implement a robust, fault-tolerant service for backing up confidential data.
Due to the sweeping waves of global industry development, the number of containers passing through terminal ports increases every day. Therefore, it is essential to automate the identification process for the container codes to replace the manual identification for more efficient logistics and safer workplace. This paper aims to design and evaluate the performance of such a system. Specifically, automated container codes recognition (ACCR) has been implemented. This is a novel container tracking model based on image processing algorithms and machine learning (ML) algorithms to be applied in ports. There are three steps in this system: character detection, character isolation, and character recognition. The first step is to identify an area with 10 digits and 26 capitals. After detecting the text area, the second step is to separate the characters. Each character is recognized in the last step by the classification method. In particular, features are extracted with the histogram of oriented gradients (HOG) algorithm and support vector machines (SVMs) for training and prediction. The trained ML model is then used to classify characters and digits according to what it has learned. In general, the digital technologies in logistics and container management in ports will benefit from the proposed algorithms.
The recognition of human activity (HAR) the use of cell devices embedded in its exten sively disbursed sensors affords guidance, instructions, and take care of citizens of smart cities. Consequently, it became essential to analyze human every day sports. To examine statistical models of human conduct, synthetic intelligence strategies such as machine studying can be used. Many studies have not studied type overall performance in real-time due to statistics series. To remedy this trouble, this paper proposes a structure primarily based on open supply technology and platforms consisting of Apache Kafka, for messages to flow over the internet, method them and provide shape for existing facts in real-time and formulates the trouble of identifying human pastime by using a smartphone tool as a type hassle using statistics collection by telephone sensors. The proposed version is skilled by some machine learning algorithms. The algorithm that has proven superior and quality results helps a linear vector machines.
This paper describes an adaptation of a polar code decoding technique in favor of the extended Golay code. Based on the bridge provided by a permutation matrix between the code words of these two classes of codes, the Golay code can be decoded by any polar code technique. Contrary to the successive-cancellation list technique which is characterized by a serial estimation of the bits, we propose in this work an adaptation of the simplified successive-cancellation list technique to polar codes equivalent to the Golay code. The simulations have achieved the performance of a maximum likelihood decoding, with the low decoding complexity of polar codes, compared to one of the universal decoders of linear codes most known in the literature.
Over the last twenty years, chaos-based encryption has been an increasingly popular way to encrypt and decrypt data using nonlinear dynamics and deterministic chaos. Discrete chaotic systems based on iterative maps have gotten a lot of interest because of their simplicity and speed. In this paper, three kinds of chaotic maps are utilized to build a digital image encryption strategy depending on a chaotic system. These chaotic maps are the logistic map, Arnold Cat’s map, and Baker’s map. In addition to using the triple data encryption standard (3DES) encryption scheme with the chaotic maps mentioned. The results of the experiments revealed that the suggested digital image encryption technique is both efficient and secure, making it ideal for usage in insecure networks. The transmission control protocol (TCP)/internet protocol (IP) protocol was used for the purpose of transferring data from server to client through the network and vice versa.
