Hyperchaotic technology-based efficient image encryption algorithm an overview.

Multimedia data encryption is so crucial because the multimedia encryption algorithm needs more time and memory, and it is difficult to implement. Because of this, the hyperchaotic image encryption technique is becoming more and more popular, which uses little memory, time, or energy and offers the highest level of security for low-powered devices. This study offers a comprehensive overview of modern hyperchaotic systems. By focusing on these complex systems' uniqueness and fundamental features, a study of their dynamic behavior is offered. Such systems are now being used more and more in a variety of industries, including finance, secure communication, and encryption, for example. In reality, every field calls for particular performances of unusual complexity. This research then suggests a specific classification based on the crucial hyperchaotic characteristic, Lyapunov exponent, the equilibrium points, dynamical behavior, NPCR, and UACI.

Assessment of Security Trepidation in Cloud Applications with Enhanced Encryption Algorithms

To alleviate crank in routine process in IT related work environment we are maintaining information’s in cloud storage even though we affected by pandemic and other natural disaster still can able to access data by avoiding degrade in target process. Members who posses account in cloud no need to have separate high end configuration devices because even less configured devices could connect to cloud and make use of all services using virtual machine. Applications belong to cloud storage intimidated in the aspect of safety. This paper reviews the various security related issues and its causes along with latest cloud security attacks. We discussed about different technology to protect information resides in cloud and analyzed different enhanced algorithm for encryption for securing the data in cloud due to surge use of devices interacting cloud services

Improved Image Security in Internet of Thing (IOT) Using Multiple Key AES

الصورة هي معلومات رقمية مهمة تستخدم في العديد من تطبيقات إنترنت الأشياء (IoT) مثل النقل والرعاية الصحية والزراعة والتطبيقات العسكرية والمركبات والحياة البرية .. إلخ. كذلك تتميز الصورة بسمات مهمة جدًا مثل الحجم الكبير والارتباط القوي والتكرار الهائل وبالتالي  تشفيرها باستخدام معيار التشفير المتقدم (AES) بمفتاح واحد من خلال تقنيات اتصالات إنترنت الأشياء تجعله عرضة للعديد من التهديدات. مساهمة هذا العمل هي لزيادة أمن الصورة المنقولة. لذلك اقترحت هذه الورقة خوارزمية AES متعددةالمفاتيح (MECCAES) لتحسين الأمان للصورة المرسلة من خلال إنترنت الأشياء. يتم تقييم هذا النهج من خلال تطبيقه على صور RGB bmp وتحليل النتائج باستخدام المقاييس القياسية مثل الإنتروبيا( Entropy ) ،المدرج التكراري histogram) )، الارتباط( correlation ) ، مقاييس نسبة الذروة للأشارة إلى الضوضاء (PSNR) ومتوسط ​​ مربع خطأ (MES). تظهر نتائج التجارب أن الطريقة المقترحة تحقق مستوى عالي من السرية كما أنها واعدة باستخدامها بشكل فعال في مجالات واسعة من تشفير الصور في إنترنت الأشياء.  Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the transmitted image through IoT. This approach is evaluated via applying it on RGB bmp images and analyzing the results using standard metrics such as entropy, histogram, correlation, Peak Signal-to-Noise Ratio (PSNR) and Mean Square Error (MES) metrics. Also, the time for encryption and decryption for the proposed MECCAES is the same time consumed by original single key AES is 12 second(the used image size is 12.1MB therefore time is long). The performance experiments show that this scheme achieves confidentiality also it encourages to use effectively in a wide IoTs fields to secure transmitted image

E‐ART: a new encryption algorithm based on the reflection of binary search tree

Data security has become crucial to most enterprise and government applications due to the increasing amount of data generated, collected, and analyzed. Many algorithms have been developed to secure data storage and transmission. However, most existing solutions require multi-round functions to prevent differential and linear attacks. This results in longer execution times and greater memory consumption, which are not suitable for large datasets or delay-sensitive systems. To address these issues, this work proposes a novel algorithm that uses, on one hand, the reflection property of a balanced binary search tree data structure to minimize the overhead, and on the other hand, a dynamic offset to achieve a high security level. The performance and security of the proposed algorithm were compared to Advanced Encryption Standard and Data Encryption Standard symmetric encryption algorithms. The proposed algorithm achieved the lowest running time with comparable memory usage and satisfied the avalanche effect criterion with 50.1%. Furthermore, the randomness of the dynamic offset passed a series of National Institute of Standards and Technology (NIST) statistical tests

Enhancing image security via chaotic maps, Fibonacci, Tribonacci transformations, and DWT difusion: a robust data encryption approach

In recent years, numerous image encryption schemes have been developed that demonstrate diferent levels of efectiveness in terms of robust security and real-time applications. While a few of them outperform in terms of robust security, others perform well for real-time applications where less processing time is required. Balancing these two aspects poses a challenge, aiming to achieve efcient encryption without compromising security. To address this challenge, the proposed research presents a robust data security approach for encrypting grayscale images, comprising fve key phases. The frst and second phases of the proposed encryption framework are dedicated to the generation of secret keys and the confusion stage, respectively. While the level-1, level-2, and level-2 difusions are performed in phases 3, 4, and 5, respectively, The proposed approach begins with secret key generation using chaotic maps for the initial pixel scrambling in the plaintext image, followed by employing the Fibonacci Transformation (FT) for an additional layer of pixel shufing. To enhance security, Tribonacci Transformation (TT) creates level-1 difusion in the permuted image. Level-2 difusion is introduced to further strengthen the difusion within the plaintext image, which is achieved by decomposing the difused image into eight-bit planes and implementing XOR operations with corresponding bit planes that are extracted from the key image. After that, the discrete wavelet transform (DWT) is employed to develop secondary keys. The DWT frequency subband (high-frequency sub-band) is substituted using the substitution box process. This creates further difusion (level 3 difusion) to make it difcult for an attacker to recover the plaintext image from an encrypted image. Several statistical tests, including mean square error analysis, histogram variance analysis, entropy assessment, peak signal-to-noise ratio evaluation, correlation analysis, key space evaluation, and key sensitivity analysis, demonstrate the efectiveness of the proposed work. The proposed encryption framework achieves signifcant statistical values, with entropy, correlation, energy, and histogram variance values standing at 7.999, 0.0001, 0.0156, and 6458, respectively. These results contribute to its robustness against cyberattacks. Moreover, the processing time of the proposed encryption framework is less than one second, which makes it more suitable for realworld applications. A detailed comparative analysis with the existing methods based on chaos, DWT, Tribonacci transformation (TT), and Fibonacci transformation (FT) reveals that the proposed encryption scheme outperforms the existing ones

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

Novel reversible text data de-identification techniques based on native data structures

Technological development in today's digital world has resulted in the collection and storage of large amounts of personal data. These data enable both direct services and non-direct activities, known as secondary use. The secondary use of data can improve decision-making, service experiences, and healthcare systems. However, the widespread reuse of personal data raises significant privacy and policy issues, especially for health- related information; these data may contain sensitive data, leading to privacy breaches if compromised. Legal systems establish laws to protect the privacy of personal data disclosed for secondary use. A well-known example is the General Data Protection Regulation (GDPR), which outlines a specific set of rules for sharing and storing personal data to protect individual privacy. The GDPR explicitly points to data de-identification, especially pseudonymization, as one measure that can help meet the requirements for the processing of personal data. The literature on privacy preservation approaches has largely been developed in the field of data anonymization, where personal data are irreversibly removed or obfuscated and there is no means by which to recover an individual's identity if needed. By contrast, pseudonymization is a promising technique to protect privacy while enabling the recovery of de-identified data. Significantly, many existing approaches for pseudonymization were developed long before the GDPR requirements were established, and so they may fail to satisfy its provisions. Therefore, it is worthwhile to offer technical solutions to preserve privacy while supporting the legitimate use of data. This thesis proposes a novel de-identification system for unstructured textual data, known as ARTPHIL, that generates de-identified data in compliance with the GDPR requirement for strong pseudonymization. The system was evaluated using 2014 i2b2 testing data. The proposed system achieved a recall of 96.93% in terms of detecting and encrypting personal health information, as specified under guidelines provided by the Health Insurance Portability and Accountability Act (HIPAA). The system used a novel and lightweight cryptography algorithm E-ART to encrypt personal data cost-effectively and without compromising security. The main novelty of the E-ART algorithm is the use of the reflection property of a balanced binary tree data structure as substitution method instead of complex and multiple iterations. The performance and security of the proposed algorithm were compared to two symmetric encryption algorithms: The Advanced Encryption Standard and Data Encryption Standard. The security analysis showed comparable results, but the performance analysis indicated that E‐ART had the shortest ciphertext and running time with comparable memory usage, which indicates the feasibility of using ARTPHIL for delay-sensitive or data-intensive application