A Novel Technique for Secure Data Cryptosystem Based on Chaotic Key Image Generation

أحدثت التطورات في تكنولوجيا المعلومات والاتصالات، خلال العقود الماضية، تغييراً كبيراً في نمط نقل معلومات الأشخاص عبر الإنترنت/الشبكات أو تخزينها. لذا، فإن أحد التحديات الرئيسية هو الحفاظ على هذه المعلومات بصورة آمنة ضد الهجمات. أدرك العديد من الباحثين والمؤسسات أهمية وفوائد التشفير في تحقيق الكفاءة والفاعلية بمختلف جوانب الاتصال الآمن.يتبنى هذا العمل تقنية جديدة لنظام تشفير البيانات الآمن على أساس نظرية الفوضى. تولد الخوارزمية المقترحة مصفوفة مفاتيح ثنائية الأبعاد لها ذات أبعاد الصورة الأصلية والتي تتضمن أرقاما عشوائية تم الحصول عليها من الخريطة الفوضوية اللوجستية أحادية الأبعاد وفق معطيات معاملات التحكم، والتي تتم معالجتها بعد ذلك من خلال تحويل الأجزاء العشرية منها عن طريق دالة إلى مجموعة من الأرقام غير المتكررة التي تؤدي إلى عدد هائل من الاحتمالات الغير قابلة للتوقع (مفكوك ناتج ضرب الصفوف في الأعمدة). يتم إجراء بعثرة مزدوجة للصفوف والأعمدة لقيم الأرقام لعدد محدد من المراحل. بعد ذلك، يتم تنفيذ عمليات XOR بين مصفوفة المفاتيح والصورة الأصلية، والتي تمثل حلاً فعالاً لتشفير البيانات لأي نوع من الملفات (النصية، الصورية، الصوتية، الفيديوية، ... إلخ).أثبتت النتائج أن تقنية التشفير المقترحة تعتبر جدا واعدة وفقا لمعايير القياسات الأمنية حيث أدت إلى تسطيح Histogram للصور المشفرة مقارنة بما هو عليه بالصور الأصلية، في حين أن متوسطات MSE عالية جدا (10115.48) و PSNR منخفضة جدا (8.17)، إلى جانب مؤشر Correlation هو قريب من الصفر و Entropy القريبة من 8 (7.997).The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given control parameters, which is then processed by converting the fractional parts of them through a function into a set of non-repeating numbers that leads to a vast number of unpredicted probabilities (the factorial of rows times columns). Double layers of rows and columns permutation are made to the values of numbers for a specified number of stages. Then, XOR is performed between the key matrix and the original image, which represent an active resolve for data encryption for any type of files (text, image, audio, video, … etc). The results proved that the proposed encryption technique is very promising when tested on more than 500 image samples according to security measurements where the histograms of cipher images are very flatten compared with that for original images, while the averages of Mean Square Error is very high (10115.4) and Peak Signal to Noise Ratio is very low (8.17), besides Correlation near zero and Entropy close to 8 (7.9975)

Entropy in Image Analysis III

Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future

Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution

The evolution of wireless and mobile communication from 0G to the upcoming 5G gives riseto data sharing through the Internet. This data transfer via open public networks are susceptible to severaltypes of attacks. Encryption is a method that can protect information from hackers and hence confidentialdata can be secured through a cryptosystem. Due to the increased number of cyber attacks, encryption hasbecome an important component of modern-day communication. In this paper, a new image encryptionalgorithm is presented using chaos theory and dynamic substitution. The proposed scheme is based on twodimensional Henon, Ikeda chaotic maps, and substitution box (S-box) transformation. Through Henon, arandom S-Box is selected and the image pixel is substituted randomly. To analyze security and robustnessof the proposed algorithm, several security tests such as information entropy, histogram investigation,correlation analysis, energy, homogeneity, and mean square error are performed. The entropy values ofthe test images are greater than 7.99 and the key space of the proposed algorithm is 2^798. Furthermore, thecorrelation values of the encrypted images using the the proposed scheme are close to zero when comparedwith other conventional schemes. The number of pixel change rate (NPCR) and unified average changeintensity (UACI) for the proposed scheme are higher than 99.50% and 33, respectively. The simulationresults and comparison with the state-of-the-art algorithms prove the efficiency and security of the proposed scheme

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

Cyber Security and Critical Infrastructures 2nd Volume

The second volume of the book contains the manuscripts that were accepted for publication in the MDPI Special Topic "Cyber Security and Critical Infrastructure" after a rigorous peer-review process. Authors from academia, government and industry contributed their innovative solutions, consistent with the interdisciplinary nature of cybersecurity. The book contains 16 articles, including an editorial that explains the current challenges, innovative solutions and real-world experiences that include critical infrastructure and 15 original papers that present state-of-the-art innovative solutions to attacks on critical systems

Trusted Artificial Intelligence in Manufacturing; Trusted Artificial Intelligence in Manufacturing

The successful deployment of AI solutions in manufacturing environments hinges on their security, safety and reliability which becomes more challenging in settings where multiple AI systems (e.g., industrial robots, robotic cells, Deep Neural Networks (DNNs)) interact as atomic systems and with humans. To guarantee the safe and reliable operation of AI systems in the shopfloor, there is a need to address many challenges in the scope of complex, heterogeneous, dynamic and unpredictable environments. Specifically, data reliability, human machine interaction, security, transparency and explainability challenges need to be addressed at the same time. Recent advances in AI research (e.g., in deep neural networks security and explainable AI (XAI) systems), coupled with novel research outcomes in the formal specification and verification of AI systems provide a sound basis for safe and reliable AI deployments in production lines. Moreover, the legal and regulatory dimension of safe and reliable AI solutions in production lines must be considered as well. To address some of the above listed challenges, fifteen European Organizations collaborate in the scope of the STAR project, a research initiative funded by the European Commission in the scope of its H2020 program (Grant Agreement Number: 956573). STAR researches, develops, and validates novel technologies that enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, the project researches and delivers approaches that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. This book is co-authored by the STAR consortium members and provides a review of technologies, techniques and systems for trusted, ethical, and secure AI in manufacturing. The different chapters of the book cover systems and technologies for industrial data reliability, responsible and transparent artificial intelligence systems, human centered manufacturing systems such as human-centred digital twins, cyber-defence in AI systems, simulated reality systems, human robot collaboration systems, as well as automated mobile robots for manufacturing environments. A variety of cutting-edge AI technologies are employed by these systems including deep neural networks, reinforcement learning systems, and explainable artificial intelligence systems. Furthermore, relevant standards and applicable regulations are discussed. Beyond reviewing state of the art standards and technologies, the book illustrates how the STAR research goes beyond the state of the art, towards enabling and showcasing human-centred technologies in production lines. Emphasis is put on dynamic human in the loop scenarios, where ethical, transparent, and trusted AI systems co-exist with human workers. The book is made available as an open access publication, which could make it broadly and freely available to the AI and smart manufacturing communities

A Covert Encryption Method for Applications in Electronic Data Interchange

A principal weakness of all encryption systems is that the output data can be ‘seen’ to be encrypted. In other words, encrypted data provides a ‘flag’ on the potential value of the information that has been encrypted. In this paper, we provide a new approach to ‘hiding’ encrypted data in a digital image. In conventional (symmetric) encryption, the plaintext is usually represented as a binary stream and encrypted using an XOR type operation with a binary cipher. The algorithm used is ideally designed to: (i) generate a maximum entropy cipher so that there is no bias with regard to any bit; (ii) maximize diffusion in terms of key dependency so that a change in any bit of the key can effect any, and potentially all, bits of the cipher. In the work reported here, we consider an approach in which a binary or low-bit plaintext image is encrypted with a decimal integer or floating point cipher using a convolution operation and the output quantized into a 1-bit array generating a binary image ciphertext. This output is then ‘embedded’ in a host image to hide the encrypted information. Embedding is undertaken either in the lowest 1-bit layer or multiple 1-bit layers. Decryption is accomplished by: (i) extracting the binary image from the host image; (ii) correlating the result with the original cipher. In principle, any cipher generator can be used for this purpose and the method has been designed to operate with 24-bit colour images. The approach has a variety of applications and, in this paper, we focus on the authentication and self-authentication of e-documents (letters and certificates, for example) that are communicated over the Internet and are thereby vulnerable to attack (e.g. modification, editing, counterfeiting etc.). In addition to document authentication, the approach considered provides a way of propagating disinformation and a solution to scenarios that require ‘plausible deniability’

Aika: A Distributed Edge System For Machine Learning Inference. Detecting and defending against abnormal behavior in untrusted edge environments

The edge computing paradigm has recently started to gain a lot of momentum. The field of Artificial Intelligence (AI) has also grown in recent years, and there is currently ongoing research that investigates how AI can be applied to numerous of different fields. This includes the edge computing domain. In Norway, there is currently ongoing research being conducted that investigates how the confluence between AI and edge computing can be used to hinder fish crime, by stationing surveillance equipment aboard fishing vessels, and perform all the monitoring directly on the vessel with support of AI. This is challenging for several reasons. First and foremost, the equipment needs to be stationed on the vessel, where actors may impose a threat to it and attempt to damage it, or interfere with the analytical process. The second challenge is to enable multiple machine learning pipelines to be executed effectively on the equipment. This requires a versatile computation model, where data is handled in a privacy preserving manner. This thesis presents Áika, a distributed edge computing system that supports machine learning inference in such untrusted edge environments. Áika is designed as a hierarchical fault tolerant system that supports a directed acyclic graph (DAG) computation model for executing machine inference on the edge, where a monitor residing in a trusted location can ensure that the system is running as expected. The experiment results demonstrate that Áika can tolerate failures while remaining operable with a stable throughput, although this will depend on the specific configuration and what computations that are implemented. The results also demonstrate that Áika can be used for both simple tasks, like counting words in a textual document, and for more complex tasks, like performing feature extraction using pre-trained deep learning models that are distributed across different workers. With Áika, application developers can develop fault tolerant and different distributed DAGs composed of multiple pipelines

Law and Policy for the Quantum Age

Law and Policy for the Quantum Age is for readers interested in the political and business strategies underlying quantum sensing, computing, and communication. This work explains how these quantum technologies work, future national defense and legal landscapes for nations interested in strategic advantage, and paths to profit for companies