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Nowadays, the graphical password has gained significant recognition and has become a subject of extensive investigation within the research community. The proliferation of Internet usage has resulted in individuals accessing various web applications from any location worldwide, utilizing personal computers, mobile phones, and other touch-enabled devices. However, individuals frequently employ passwords that are weak and commonly used due to their inability to recall complex passwords. This renders the systems susceptible to various forms of attacks. Hence, there is a requirement for an authentication scheme that possesses qualities such as resilience, ease of memorability, and security. Graphical passwords are significantly more effective than text-based passwords in terms of memorability. Nevertheless, numerous schemes are susceptible to various forms of attacks, such as shoulder surfing attacks, man-in-the-middle attacks, database attacks, random guess attacks, and so forth. Moreover, the compromise between security and usability concerns is evident in different graphical authentication schemes. Therefore, we present a novel graphical authentication scheme that ensures both security and usability. This scheme incorporates random graphical objects blended with a background image, resulting in the generation of a distinct graphical challenge. The objects that have been chosen must undergo verification through the utilization of an object detection algorithm known as YOLOv3. In order to strengthen the security of GPOD (Graphical password with object detection), user data is subjected to encryption and subsequently stored on the server, thereby mitigating the risk of potential database attacks. Additionally, the user data undergoes encryption prior to its transmission to the server in order to alleviate the risk of man-in-the-middle attacks. The proposed GPOD scheme is a straightforward, usable, resilient, shoulder-surf-resistant, and secure graphical authentication scheme. The scheme exhibits excellent performance, with an accuracy rate of up to 94.80% and a login time ranging from 9.61 to 14.56 seconds in two scenarios, respectively. [ABSTRACT FROM AUTHOR]

Data hiding along with the security plays a vital role in the wireless network. In recent years, object detection, Feature Extraction (FE) and correlation based technique are developed to predict the pixels that is suitable for embedding. However, traditional data hiding method still suffered in the selection of less distortion pixels. To overcome these shortcomings, this method proposes (i) Moving Object (MO) detection, (ii) FE, (iii) data hiding, and (iv) data encryption. Initially, the MO in the video are detected using optical flow and tracking the weight of MO. Next, data hiding features are extracted using Optimization Fruit fly Algorithm (OFA) with Differential Evolution (DE) and Opposition Based Learning (OBL) algorithm. Then, a modified data hiding techniques based on correlation, regression and pixel segmentation with Prediction Error (PE) techniques are used for improving the performance. Finally, the hidden data is encrypted using Binary Tree Structure (BTS) to provide additional layer of security. Experimental result shows the proposed method is superior to other state-of-the-art methods in terms of Peak-Signal-to-Noise Ratio (PSNR), embedding capacity and security analysis. [ABSTRACT FROM AUTHOR]

In recent days, cloud computing is a universal computing and conventional paradigm, in which the resources are provided over the Internet based on requirements. With the huge growth of cloud storage and processing, security in Cloud has become the most captivating research domains. Though there are many methods for enhancing security and data confidentiality over cloud, security is the major threat among data owners and users in data storages and data sharing between two parties in Cloud. In data sharing, for assuring security, the data are secured with key and the key is required to be encrypted to keep that not accessible for attacks. With that concern, this work develops a Quantum Cryptography based Cloud Security Model (QC-CSM) that uses Quantum Key Distribution Protocol (QKDP) for sharing the secret key between parties. For ensuring the data owner about the security of their share data over Cloud, Attribute Based Encryption (ABE) is used. Further, the data can be accessed by an authenticated user, who is having the access for decryption through the key from a secure quantum channel. The results show that the proposed model outperforms the existing works by providing a more secure environment and confidential data sharing between entities in minimal time in the Cloud framework. [ABSTRACT FROM AUTHOR]

Smartphones have become small computers that meet many of our needs, from e-mail and banking transactions to communication and social media use. In line with these attractive functions, the use of smartphones has greatly increased over the years. One of the most important features of these mobile devices is that they offer users many mobile applications that they can install. However, hacker attacks and the spread of malware have also increased. Today, current mobile malware detection and defense technologies are still inadequate. Mobile security is not only directly related to the operating system and used device but also related with communication over the internet, data encryption, data summarization, and users' privacy awareness. The main aim and contribution of this study are to collect the current state of mobile security and highlight the future of mobile security in light of the recent mobile security threat reports. The studies in the field of malware, attack types, and security vulnerabilities concerning the usage of smartphones were analyzed. The malware detection techniques were analyzed into two categories: signature-based and machine learning (behavior detection)-based techniques. Additionally, the current threats and prevention methods were described. Finally, a future direction is highlighted in the light of the current mobile security reports. [ABSTRACT FROM AUTHOR]

In recent times, many innovative techniques are enabled in the real-time business environment and becoming more popular day by day in the cloud platform. The IT platform is expecting a whole new level of development by implementing new innovative technologies to a greater extent without employing additional infrastructure. Security is a critical concern in a shared environment in the current era, and it remains unresolved in the cloud. Data replication is also challenging to sustain performance, including data availability, reliability, scalability, bandwidth, access latency, and storage capacity constraints. Hence, data must be replicated to different nodes to achieve greater performance in the shared environment. Once the data is placed on to the backend storage, no proper encryption method is implemented when data is in motion and rest. This research proposes a new method to secure a one-time password in a two-factor authentication mechanism. The research employs, proves, and ensures strong security. The second method proposed in this research is to place the optimal number of replicas on different nodes to offer high availability. The replication using the packing coloring process is performed over multiple servers and optimizes the replica, which leads a path to space efficiency. The final method is a graph-based data encryption strategy that performs encryption on data in backend Redundant Array of Independent Disk (RAID) storage using crypto keys generated by the packing coloring process. The dynamic keystream considered in the proposed research offers better security. This research offers a novel architecture that proves strong security, improved authentication, and optimal replica placement with minimal cost. [ABSTRACT FROM AUTHOR]

Hadoop is one of the biggest software structures for distributing the data to compute and handle big data. Big data is a group of composite and enormous datasets that contains a massive amount of data such as real-time data, social media, capabilities of data management, money laundering, and so on. Also, big data is measured as regards terabytes and petabytes. The main issue of the Hadoop application is unauthorized access. There are several existing techniques introduced to secure the data, but they have data errors, malicious attacks, and take a long time to compute. So the author proposed a novel ChaApache framework to secure the Hadoop application from an unauthorized person also to save processing time of data, and reduce the error rate. The main aim of the developed replica is securing data from an unauthorized person or unauthorized access. Moreover, the developed ChaApache framework is implemented in python, and the Hadoop application contains 512 bits of data, and the data are encrypted by four 32 bits. Furthermore, the proposed model is compared with other existing replicas in terms of computation time, resource usage, data sharing rate, encryption speed, and so on. [ABSTRACT FROM AUTHOR]

This paper gives a novel and efficient steganography technique based on hybrid algorithms that improves the various important parameters like PSNR, MSE, IF, capacity, security. It increases the security of the confidential data by using the encryption method and give improved quality of stego images with less error rate. This paper utilizes a grouping of wavelet domain & Salp Swarm based Optimization Algorithm (SSOA) and proposed embedding process for increasing the payload capacity. Initially, the integer discrete wavelet transform is utilized to process the cover image and DWT to extract the hidden image accurately. Furthermore, an edge localization process is proposed to localize the edge region of detail bands efficiently, which can be done by SSO Algorithm. To enhance the quality of the stego pictures, a deep enhanced stacked auto encoder (DESAE) has been proposed. The evaluation result of this technique achieves good image quality and high security. Also, it increases the payload capacity of the existing methods, which confirms the superiority of the proposed method compared to previous related techniques. [ABSTRACT FROM AUTHOR]

The security of digital information is one of the significant problems of the existing world. In this work, we have proposed a dual-layer information hiding mechanism. We have utilized 3-Cell Cellular Neural Network (CNN) system to generate a pseudorandom number generator to fulfill diffusion requirements of a cryptosystem, and then utilizing highly non-linear substitution boxes (S-boxes) to complete the confusion process of cryptosystem design. The encrypted data are the hide in the cover image, the data hiding process comprises three steps, generation of transform matrix from the cover image, embedding matrix from transform matrix and secret encrypted image and the last step is to obtain a stego image. Less computational complexity without affecting the strength of the security scheme is the need of the day. Due to the simplicity and computational efficiency of the diffusion process of a 3-cell cellular neural network, the confusion created by predefined S-boxes, and the data hiding scheme effectively reduces the time for encryption and data hiding. The proposed scheme has been tested using state-of-the-art key performance indicators including information theory-based analysis, Histogram based analysis, analysis based on pixels difference, correlation-based measurements, and distance-based analysis. the results of this analysis show the efficiency and effectiveness of the proposed system. [ABSTRACT FROM AUTHOR]

Due to the widespread accessibility of the Internet, communicating and sharing multimedia content between people is extremely easy today. At the same time, however, a critical issue is the secure transfer of personal and protected material. In this article, we have proposed a new information security mechanism. The proposed system comprises two phases. In the first phase, the digital data is encrypted and in the second phase, the encrypted data is embedded into the cover data. The encryption scheme consists of both diffusion and confusion. For diffusion, we have utilized a logistic chaotic map-based novel diffusion. For confusion pre-defined highly nonlinear S-boxes are used. This mechanism provides dual layers of security to the confidential information, which makes it difficult for the intruder to extract the confidential information. The security analysis of the encryption and data hiding schemes are carried out and tabulated. For implementation on hardware the time analysis is carried out, and the time for encryption and data hiding comes out to be 1.662 seconds, which is reasonable for real-time implementation. The security analysis of encryption and data hiding shows the immunity of the proposed system to withstand different attacks. [ABSTRACT FROM AUTHOR]

Data Security has always been a challenge while sharing sensitive information and a lot of techniques have been developed to achieve it. Security should not hamper the availability of the data and hence, a technique that caters to both is needed. The use of classical and modern encryption technique are very common and are becoming prone to attacks by crypto-analytics. Due to the technological advancement, new ideas of data security comes very rapidly. For this reason the use of blockchain has become profound but the actual security of the data encryption technique always depends on the choice of the key. Stronger key leads to high data security. The paper aims to explore the concept of DNA encoding to propose a data encryption algorithm. It uses a dynamic DNA encoded table which contains different combination of four DNA bases A, C, G, and T but the main feature of dynamic DNA sequence table is its randomness which is changed for different characters in ASCII code in each run time. This randomness in the encryption disables attackers to perform any sort of statistical analysis to decipher the encrypted text or guess the key. [ABSTRACT FROM AUTHOR]

This paper presents a novel encryption method based on individual block ciphering using Catalan random walks. This paper aims to offer some new possibilities of multimedia data protection to realize the rights of participants in the multimedia distribution chain (image, text, video, sound). Also, the emphasis is on advanced analysis of Catalan numbers and their combinatorial representations in multimedia security. The proposed method consists of five phases: conversion, division, selection, encryption, and generation. We presented the application of our method in ensuring the security of multimedia content. The proposed method was implemented in Java. In the experimental testing, we provide the time and space complexity of Catalan keys generation and Maurer's universal statistical test for the proposed method. Also, we state security analysis using machine learning methods and comparative analysis with existing methods of encrypting data into a blockchain. [ABSTRACT FROM AUTHOR]

Reversible Data Hiding in Encryption Domain (RDHED) can be used in different areas such as secure remote sensing or telemedicine. Since data structure is completely changed after a reliable encryption process, custom reversible data hiding methods are not efficient to perform RDHED. In this paper, a reversible method is proposed to embed extra information in the encryption domain by designing two dimensional (2-D) error histogram. According to the proposed method, target pixels are predicted in the encryption domain to design a 2-D error histogram. The obtained histogram is shifted according to a novel pattern for data insertion. 2-D histogram shifting makes it possible to shift bins of the error histogram in various directions. This property augments embedding capacity and improves quality of directly decrypted images. To perform a secure encryption process, an improved Closed-Loop Chaotic Encryption System (CLCES) has been designed. The proposed CLCES performs a sensitive encryption process in a closed-loop system. Extensive experiments have been conducted to evaluate the performance and security of the proposed method. Obtained embedding capacity has been 0.128 bit per pixel by taking average values over 1000 test images and using least square predictor. Results confirm superiority of the proposed method in comparison with other schemes. [ABSTRACT FROM AUTHOR]

Reversible Data Hiding in Encryption Domain (RDHED) can be used in different areas such as secure remote sensing or telemedicine. Since data structure is completely changed after a reliable encryption process, custom reversible data hiding methods are not efficient to perform RDHED. In this paper, a reversible method is proposed to embed extra information in the encryption domain by designing two dimensional (2-D) error histogram. According to the proposed method, target pixels are predicted in the encryption domain to design a 2-D error histogram. The obtained histogram is shifted according to a novel pattern for data insertion. 2-D histogram shifting makes it possible to shift bins of the error histogram in various directions. This property augments embedding capacity and improves quality of directly decrypted images. To perform a secure encryption process, an improved Closed-Loop Chaotic Encryption System (CLCES) has been designed. The proposed CLCES performs a sensitive encryption process in a closed-loop system. Extensive experiments have been conducted to evaluate the performance and security of the proposed method. Obtained embedding capacity has been 0.128 bit per pixel by taking average values over 1000 test images and using least square predictor. Results confirm superiority of the proposed method in comparison with other schemes. [ABSTRACT FROM AUTHOR]

Data is undoubtedly one of the most significant assets in the current competitive era and to ensure its value is retained, data safety emerges as a principle concern. Another technology asset is the cloud that is proficient in storing data at very little cost or even no cost at all. There are two main challenges that come with storing data in the cloud, safe storage of data and another is encryption of data with as little time and storage space as possible. These challenges have come in the way of various financial and government organizations tapping the benefits of the cloud. A two-step solution is illustrated in this research study in response to the raised issue. The initial part of this study discusses the classification of data into sensitive data and non-sensitive data. This is done to ensure that precious resources are used only to encrypt sensitive data and are not wasted on encryption data that doesn't require encryption. To implement this, a mechanism based on Convolutional Neural Network with Logistic Regression(CNN-LR) is proposed. The next phase of this research work discusses the encryption method that is mainly focused on ensuring time and space complexity while encrypting data. For this, Ellipticcurve Diffie Hellman and Shifted Adaption Homomorphism Encryption (ECDH-SAHE) has been used and for decryption of data, Elliptic-curve DiffieHellman-Shifted Adaption Homomorphism Decryption (ECDH-SAHD) has been used. The proposed approach is titled Sensitive Encrypted Storage (SES). The results from the proposed methods are highly motivating and present great efficiency and capability which shall provide new dimension to the researchers in the future. [ABSTRACT FROM AUTHOR]

This research introduces a novel attribute-based data access model in Blockchain (AB-DAM) Framework in Healthcare Systems to enhance the authentication of the users before data transmission. The proposed AB-DAM strategy and the smart contract assure secure communication. The Data requestor (DR) requests access using a unique ID and password to the Data holder (DH), who processes the request and authenticates the Data user. The information of the DH is embedded in the blockchain using an encrypted master key. The DH does the data encryption process through attribute-based Encryption (ABE), and the encrypted files are uploaded to the Interplanetary File System (IPFS). When the smart contract identifies the user as valid, the DH sends the requested data to the DR through the IPFS. The proposed model obtained the responsiveness and genuine user detection rate value of 24.1578 s and 43.38%, respectively. [ABSTRACT FROM AUTHOR]

Security is an important issue in current and next-generation networks. Blockchain will be an appropriate technology for securely sharing information in next-generation networks. Digital images are the prime medium attacked by cyber attackers. In this paper, a blockchain based security framework is proposed for sharing digital images in a multi user environment. The proposed framework uses reversible data hiding and encryption as component techniques. A novel high capacity reversible data hiding scheme is also proposed to protect digital images. Reversible data hiding in combination with encryption protects the confidentiality, integrity and authentication of digital images. In the proposed technique, the digital image is compressed first to create room for data hiding, then the user signature is embedded; afterwards the whole image is encrypted. For compression, JPEG lossy compression is used to create high capacity. For encryption, any symmetric block cipher or stream cipher can be used. Experimental results show that the proposed blockchain based framework provides high security and the proposed reversible data hiding scheme provides high capacity and image quality. [ABSTRACT FROM AUTHOR]

The security strength of the elliptic curve cryptosystems (ECC) is due to its core operations-based group law. This aspect of the elliptic curve provides key service to ensure security against modern cryptanalysis. However, the excess use of group law in EC based algorithms make it computationally hard for real time applications. In this context, this paper presented a smart-like algorithm based on subgroup co-set operations. The suggested scheme uses all co-sets that generates multiple sequences that can smoothly be adopted in most promising communication architectures of the future such as internet of things (IoT). Besides, the subgroup structure on a small prime with possible embedding is managed to construct efficient substitution box (S-box). Whereas, the performance of the proposed S-box is examined via standardized tests thus found significant for multimedia data security applications. Moreover, a small prime based EC subgroup coset model is designed, that generates a set of experimentally verified independent pseudo random streams. The atypical mathematical model for its application to image data encryption is established, by combining the S-box module (SM) and subgroup coset module (ES-PM). Several statistical tests revealed that the proposed technique is suitable for various cryptographic applications. [ABSTRACT FROM AUTHOR]

Personal Health Record (PHR) is an online electronic application used by patients to store, retrieve and share their health information in a private and secure environment. While outsourcing the PHR into cloud environment, there exist issues in privacy while storing, searching and sharing of health information. To overcome these issues, an efficient retrieval of health records using Multi Keyword Searchable Attribute Based Encryption (MK-SABE) is proposed. To manage the increasing PHR data in the cloud, an Authorized File Level Deduplication technique is adopted. It eliminates redundant files, thereby reducing the communication overhead. Moreover, PHR data is encrypted before outsourcing and to perform searching over encrypted data, the proposed MK-SABE introduces Conjunctive Multi Keyword Searchable Attribute Based Encryption (CM-SABE). This maintains the searchable property after encryption for efficient retrieval of health files using range query. Further to ensure the trustworthiness while sharing the sensitive data, MK-SABE introduces the Location Based Encryption (LBE) and Dynamic Location Based ReEncryption (DLBRE) technique to provide additional security. From the experimental analysis, it is proved that the proposed MK-SABE reduces the storage complexity by 5%, keyword search time by 25% and improves the overall performance of PHR by 40% compared to the existing schemes. [ABSTRACT FROM AUTHOR]

The usage of digital health data such as documents, images and videos has increased drastically in recent years, making them more prone to sophisticated cyber threats. Here arises a great requirement of information security since this digital data is sent through the public network. Many encryption algorithms were utilised to protect digital data from typical attacks. There exist several conventional encryption algorithms such as Data Encryption Standard (DES), Advanced Encryption Standard (AES), International DataEncryption Algorithm (IDEA), etc., which are used for encryption purposes. Still, they take longer execution time, provides poor security and are more vulnerable to several cyber-attacks. The proposed work provides a cryptosystem based on 4D Lorenz type hyper-chaos and Deoxyribonucleic acid (DNA) encoding mechanism to overcome earlier method limitations. The approximated and detailed coefficients of the input image is obtained by applying Integer Wavelet Transform (IWT). Then, the pixels of the Low-Low (LL) band get permuted using a Logistic map. The 4D hyper-chaotic system creates a pseudo-random chaotic sequence using the initial values, quantised to a keystream. The final data gets encoded using the DNA encoding rule. For enhanced diffusion, DNA-XOR is performed to produce the final cipher image. Various performance metrics have been analysed for several images, and the experimental results show that the proposed scheme is effective against brute force attacks. [ABSTRACT FROM AUTHOR]

Due to the recent advancement in the field of the Internet of Medical things (IoMT). To facilitate doctors and patients, in the process of diagnosis and treatment, the medical imaging equipment is connected to the IoMT. During communication over the network, these medical images are subjected to various threads. In this work, we have proposed a dual-layer data confidentiality scheme, firstly it encrypts the secret medical images followed by a data hiding scheme. The encryption scheme possesses diffusion and confusion, for confusion the encryption scheme utilizes logistic and tent maps for the generation of S-boxes. For data hiding, it utilizes Hessenberg and singular value decomposition (SVD). The proposed scheme is applied to highly correlated medical images. The proposed technique provides dual security to the confidential information and makes it difficult for the intruder to extract the confidential information. The encryption scheme is evaluated by using the standard performance indicators including statistical analysis, differential analysis, and NIST analysis, etc. The encrypted images have the highest practically achievable entropy of 7.999 which is closest to the ideal value of 8. The data hiding scheme is evaluated by using statistical analysis, Distance-based analysis, analysis based on pixel difference, and information theory. Both the analysis of encryption and data hiding are satisfactory and the results show the strength of the dual-layer security scheme. [ABSTRACT FROM AUTHOR]

To protect the information integrity of the medical images, this paper proposes a secure lossless recovery scheme for medical images based on image block compression and permutation ordered binary (POB) number system, which includes two parts: share generation, and lossless recovery. In the shares generation stage, the region of interest (ROI) of the original medical image and the image block compression coding algorithm JPEG-LS, are firstly adopted to generate the compressed data, which can use limited storage space to place the data repeatedly. Then, after separating the bit-plane, the compressed data are executed by data reorganization and data encryption respectively on the high-plane and the low-plane. Finally, two authentication bits are extracted by 8-bit pixel of two planes to be inserted into the pixel itself, and then the 10-bit pixel is converted into an 8-bit POB value to produce two shares of ShareH and ShareL, respectively. In the lossless recovery stage, data of placing repeatedly can restore the original image. At the same time, three attacks are carried in the two shares, which contain content cropping, content exchange, and text addition. Some comparisons with other schemes present that the proposed scheme implements a better performance under some criteria. Theoretical analysis and experimental results demonstrate that the original image can be recovered losslessly even if two shares are tampered at the ration more than 50%. [ABSTRACT FROM AUTHOR]

Traditional network data security sharing system ignores that many people share data simultaneously, which leads to poor real-time performance. Therefore, the authors designed a network data security sharing system based on blockchain technology. In the hardware design, the PCI encryption card is used to encode the data. The microprocessor is used to access the system's external equipment, and DDR-SDRAM dynamic storage area and NAND flash static memory are used as network data. In the software section of the system, a secure transmission mechanism is established. The cp-abe method is used to encrypt the network shared data, and the multi-person digital envelope technology is used to share the data. These two methods contribute to the design of the network data security sharing system. In the experiment, eight users share the data. The system login response time, key distribution time, data encryption time, and key update time are taken as the experimental objects. Experimental results show that the system response time, key distribution time, data encryption time, and key update time of the system are shorter than those of the comparison method. [ABSTRACT FROM AUTHOR]

The exponential rise in the development of cloud computing environments in the healthcare field, the protection and confidentiality of the medical records become a primary concern for healthcare services applications. Today, health data stored in the cloud is highly confidential information concealed to avoid unauthorized access to protect the patient's information. As cloud-based medical data transmission becomes more common, it receives growing attention from researchers and academics. Despite the potential for misuse, medical data transmitted through unreliable networks can be manipulated or compromised. The current cryptosystems alone are not sufficient to deal with these issues, and hence this paper introduces a new hybridization of data encryption model to shelter the diagnosis data in medical images. The proposed model is developed by combining either 2D Discrete Wavelet Transform 1 Level (2D-DWT-1 L) or 2D Discrete Wavelet Transform 2 Level (2D-DWT-2 L) steganography with the proposed hybrid encryption scheme. The hybrid encryption scheme is built by strategically applying Advanced Encryption Standard (AES) and Rivest–Shamir–Adleman (RSA) algorithms to secure diagnosis data to be embedded with the RGB channels of medical cover image. One of the key novelties is the use of an Adaptive Genetic Algorithm for Optimal Pixel Adjustment Process (AGA-OPAP) that enriches data hiding ability as well as imperceptibility features. To evaluate the efficiency of the proposed model, numerical tests are performed. The results show that the proposed algorithm is capable of safely transmitting medical data. Comparison of results is carried out concerning the datasets with the state-of-the-art algorithm. In terms of various statistical measures, the results showed the superiority of the proposed algorithm, such as peak signal to noise ratio (PSNR), correlation, structural content (SC), structure similarity (SSIM), entropy, histogram, NPCR, UACI and embedding capacity. The proposed model can also prevent attacks, such as steganalysis or RS attacks. [ABSTRACT FROM AUTHOR]

New genome sequencing technologies have decreased the cost of generating genomic data, thus increasing storage needs. The International Organization for Standardization (ISO) working group MPEG has developed a standard for genomic data compression with encryption features. The approach taken in standard MPEG-G (ISO/IEC 23092) to compress genomic information was to group similar data into streams. Taking this into account, one of the protection options considered was to encrypt each stream separately. In this paper, we show that an attacker can use an unencrypted stream to deduce the encrypted content if streams are encrypted separately. To do so, we present two different attacks, one based on signal processing and the other one based on neural networks. The signal-based attack only works with unrealistic settings, whereas the neural network-based one recovers data with realistic settings (regarding read length and coverage). The presented results made MPEG reconsider the encryption strategy, before final publication of the standard, discarding separate streams encryption approach. [ABSTRACT FROM AUTHOR]

Currently, embedded systems can be found everywhere in quotidian life. In the development of embedded systems, information security is one of the important factors. Encryption is an efficient technique to protect information against attacks. However, because of constraints, existing encryption functions are not compatible and do not agree with real-time applications in embedded systems. In this paper, an improved cryptographic approach with a high level of security and high speed is put forward. Our work uses an efficient version of a hybrid scheme comprising an Advanced Encryption Standard (AES) - Elliptic Curve Cryptography (ECC) for medical image encryption, which combines the benefits of the symmetric AES to speed-up data encryption and asymmetric ECC in order to secure the interchange of a symmetric session key. The contribution of this paper consists of the following two main points: First, we put forward an optimized ECC hardware architecture to respect the compromise between area, power dissipation, and speed. Thus, we primarily utilize only two multipliers to develop the Point Addition (PA) block and the Point Doubling (PD) block, which reduces time complexity. Then, a 32-bit multiplier and a 32-bit inverter architecture based on shifts and XORs are proposed to reduce power consumption and area occupancy. Second, for image encryption, we primarily propose to modify the AES by eliminating the mix-columns transformation and replacing it with a permutation based on the shifts of columns, which decreases time complexity while maintaining the Shannon diffusion and the confusion principle. Then, an adjustment of the rearrangement of the general structure is given to enhance the entropy value. The global cryptosystem is implemented using a co-design approach where the modified AES runs on the NIOS II processor, and the scalar ECC multiplication is designed as a hardware accelerator. The suggested cryptographic system spends much less execution time, which is a significant factor for being applied in practice. Security analysis is successfully performed, and our experiments prove that our proposed technique provides the basics of cryptography with more simplicity and correctness. In fact, the results of the evaluation prove the effectiveness, rapidity and high security of the suggested algorithm. [ABSTRACT FROM AUTHOR]

There is a trade-off relationship between the imperceptibility of a watermark and the robustness of a digital watermarking algorithm; to overcome this, we propose a robust digital watermarking encryption algorithm for quick response (QR) code images based on discrete cosine transform (DCT) and singular value decomposition (SVD) through dual scrambling using Josephus ring and cellular automata. Experimental results show that watermark can still be identified from a seriously distorted QR code. The proposed scheme maintains satisfactory image quality, with great robustness to noise, filters, JPEG compression, rotation, cropping, contrast variation attacks, print/scan attacks, and so on. This algorithm can achieve further reform for QR code, which can be widely used to protect the copyright of digital works. [ABSTRACT FROM AUTHOR]

To solve the privacy image problem stored in cloud, we propose a compressive sensing (CS) based image compression, authentication, encryption algorithm in cloud, which can implement computation outsourcing to get rid of the expensive storage and computation costs. To achieve these goals, combined with the logistic-tent-sine chaotic map, a logistic-tent-sine chaotic map (LTSS) is proposed for it has larger chaotic ranges and better chaotic behaviors than simple 1D chaotic map such as a logistic chaotic map. Then, the LTSS chaotic system is employed for image protection algorithm in cloud, which contains three parts: data owner, cloud services and data user. The primary role of the data owner part is to compress and encrypt the image while embedding the owner's Palmprint discriminative and binary features for authentication. The low-frequency part of the image is encrypted using the proposed Binary Data Cyclic Encryption algorithm (BDCE) while the owner's palmprint features are embedded for authentication of the data owner. The high-frequency data are randomized for compression by the CS and following encrypted by the Double Random Phase Encoding (DRPE). For the cloud services, authentication services depend on the key and palmprint features and the high computational compressed sensing reconstruction is implemented in cloud can reduce the user burden. For data users, a user should provide the correct key and right palmprint, and then obtain an image available from the cloud service. The algorithm has better quality compared with the common compressive sensing based algorithms and robust to noise and occlusion for using the discrete wavelet transform. What is more, theoretical analysis and empirical evaluations show that the proposed algorithm can resist to exhaustive attack, differential attack and classical attacks. [ABSTRACT FROM AUTHOR]

Fairly recently, a new audio encryption scheme has been proposed. The cryptosystem is based on a substitution-permutation algorithm using DNA encoding. The key-generation of this proposed scheme is based on a key chaining mode, that generates a new key block for every plain block using the chaotic logistic map. After several statistical tests, handled by the authors of the scheme, they claimed that their cryptosystem is robust. In this paper, we scrutinize the cryptosystem from a cryptanalytic perspective, and we handle several security attacks to evaluate the immunity of the system, and to assess its possible adoption in real-world applications. We demonstrate two successful conventional attacks on the scheme, which are: the chosen ciphertext and chosen-plaintext attacks. The cryptosystem's shuffling process design is scrutinized as well, and a cycle attack is described using the drawn results. Lessons learned from this cryptanalytic paper, are then outlined in order to be considered in further designs and proposals. [ABSTRACT FROM AUTHOR]

H.264/Advanced Video Coding (H.264/AVC) is one of the video compression standards that is 50% more efficient than previously introduced standards. Given that the H.264/AVC standard is considered and used in a variety of video applications, it is essential to provide a suitable solution for video encryption with good security, high encryption speed, and to prevent bitrate increases. In this paper, we propose a method selective encryption of H.264/AVC for the digital rights management (DRM) applications. In this method, discrete cosine transform (DCT) coefficients, which affect the texture and content of the H.264/AVC video during compression, are encrypted after the zigzag scanning and based on Context-Adaptive Binary Arithmetic Coding (CABAC). The experimental results and encryption efficiency analysis demonstrate that the proposed method with the format compliance has good security and high encryption speed and it can prevent the bitrate from rising and is thus usable in industrial and the DRM applications. [ABSTRACT FROM AUTHOR]

With the rapid development of the Internet, there is a pressing requirement for data security protection in Internet. However, in some applications, resource constrained devices in Internet requires that the algorithm for data encryption have high reliability and availability, as well as extremely low latency, and strong robustness in harsh environment. In this work, we propose an efficient batch images encryption/decryption scheme based on DNA encoding and piecewise linear chaotic mapping system (PWLCM). Different from all existing methods, the proposed method can encrypt/decrypt any number of images with different sizes via only single encryption computation, and the computing cost is equivalent to that of encrypting a single image. Experimental results demonstrate that the proposed method has strong robustness to resist the interference of harsh environment, such as noise contamination, JPEG compression, and image content loss. We also investigate the computing cost, encryption effect and the security. Comparing with the state-of-the-art methods, the proposed method has high encryption efficiency, stronger robustness and security. [ABSTRACT FROM AUTHOR]

Securing digital medical images is increasingly becoming a major concern due to the rapid growth of the amount of medical images transferred over a network and stored on the web servers. However, the enormous size of multimedia and the huge volume of exchanging medical images have motivated the development of low computational complexity methods. This paper presents a lightweight selective encryption scheme to encrypt the edge maps of medical images. The edge map is firstly extracted by an edge detection method. Then, a chaotic map is used to generate a large key space. We propose a one-time pad algorithm to respectively encrypt the significant detected image blocks. The experimental results have proven that the proposed encryption scheme provides an acceptable percentage of encrypted image data. It can also effectively perform image encryption and decryption in a lightweight manner, which makes the scheme a good candidate for real time applications. Moreover, the security analysis demonstrates that our scheme has a robust resistance against various security attacks. [ABSTRACT FROM AUTHOR]

Numerous seismic datasets are routinely acquired, stored and transferred via different systems and networks. Significant reduction of data sizes with encryption would significantly reduce storage media and transmission costs and security. This study presents a novel approach for compressing and encrypting numerical data in descriptive bitmap images. The method depends on the Steim method for bit-packing and the 128-bit numerical system for encryption and bitmap manipulations for compression. The method produced encrypted data capsules in a WebP image file. For seismic data, it is found that the size of the WebP image comprises ~20% of the corresponding binary size with a bit-rate of ~5.6 b/s which is smaller than that of the Steim form, 27% and 8.9 b/s, respectively. The size of the redundant data is reduced to ~0.1% with a bit rate ~ 0.04 b/s. Regarding the compression speed, it is found that the code compresses data with a rate of ~11,118 samples/s or ~ 44 Kbytes/s in average. For the first time, this study provides an unconventional use of an image file to hold a big amount of 128-bit encrypted data in a compressible form. It is proven that the data in the WebP format, regardless of being encrypted, occupies the least amount of storage space among other image formats, that can be easily handled, stored, and shared through clouds and devices safely with a lower cost. [ABSTRACT FROM AUTHOR]

This study combines Cryptography (Twofish and Triple data decryption (3DES)) algorithms and Steganography (Least Significant Bits) to solve the problem of attacking or hacking biometric template for a malicious act, which has become a huge problem in the iris recognition system. Twofish and Triple data encryption are good and secured cryptography algorithms which are used to change readable secret data (plain image) into an unreadable format (cipher image) while least significant bits (LSB) is a steganography algorithm which embeds ciphertext/image directly into a cover image to produce an image known as stego image. In this work, Hough transform, Daugman rubber-sheet model and Log Gabor filter were used for iris image segmentation, normalization and feature extraction and the iris template generated was encrypted using 3DES and Twofish algorithms. The cipher image was then embedded into a cover image to produce stego image using LSB. The result of this work slightly changes the master file after embedding the secret image (stego file) that cannot be identified by the physical eyes and only a JPEG image was used as the master or cover file. The two levels of security technique provide high embedded capacity and eminence stego images that will able to withstand attackers. [ABSTRACT FROM AUTHOR]

The application of deep learning-based face detection in the privacy and security of intelligent cloud platforms is studied, in order to resolve the risk of private photo leakage on such platforms. Five key feature points of human faces (two eyes, two noses and two corners of mouth) are sought using the multitask cascaded convolution network (MTCNN). The algorithm utilizes the intrinsic links among Proposal Network (P-Net), Refine Network (R-Net) and Output Network (O-Net) to improve their face detection performances substantially. Since many existing data encryption methods, such as DES, RSA and AES, are applicable only to test data instead of digital images, the encryption of eigenvalues is achieved with a combination of chaotic logic diagrams and RC4 stream ciphers. Meanwhile, the MTCNN-generated face coordinates and user passwords are hash-converted and double-encrypted using hash table. The results show that the face detection accuracy of MTCNN reaches 95.04%, and that the image encryption method is suitable for network transmission. The chaotic logic diagrams increase the security of S-box initialization in the RC4 algorithm. The hash structure accelerates the file reading, whereas the hash conversion improves the security of critical data. In conclusion, the proposed encryption scheme is computationally fast and highly secure. [ABSTRACT FROM AUTHOR]

Steganography, the hiding technique used to secure sensitive data (i.e., images, audio) while communication takes place. In this paper, the message is embedded in color image in frequency domain exploiting Genetic Algorithm (GA) which provides the robustness i.e., the algorithm can withstand against any rigorous testing and brutal attack except destruction of the stego image. The fragmentation of 8-bit binary stream of each color component to 4-bit and applying Genetic Algorithm (GA) to increase the robustness of the scheme. Random Multiple bits are chosen to embed secret message which increases security along with the payload. The use of transform domain, hash function based random pixel and bit selections for data hiding, secrete data encryption and more over use of Genetic Algorithm (GA) for optimization is the novelty of the proposed work. Perspective and meticulous statistical analysis has been done to immune the algorithm from any attack. The algorithm proposed here is tested with benchmark tools like StirMark 4.0, Confusion Matrix (Receiver Operating Curve Characteristic (ROC) curve) along with steganalysis and statistical tools. Visual disturbance and distortion in stego image is also very insignificant here. [ABSTRACT FROM AUTHOR]

In this paper, a novel color image encryption scheme based on fractals, substitution box and hyper chaotic dynamic is proposed. In the first step, fractal images are generated by Julia fractal set as keys. Then, the substitution box is constructed by Hilbert fractal, and the original image pixels are replaced with the values of the S-box. In the next step, using the Logistic map, the location of the pixels is scrambled to reduce their correlation. In the following, Chen hyper-chaotic system is used to change the pixels values of fractal images as well as index production to select fractal images. Finally, each pixel of three original image layers with the corresponding pixels in the three selected fractal images and the previous encrypted pixel value are encrypted with XOR operation. Both experimental results and security analyses indicated that the proposed method yields high encryption effect, larger secure key space and is high sensitive to the secret key and the plain image. In addition, the algorithm could resist against diverse typical attacks. [ABSTRACT FROM AUTHOR]

Multimedia communication is revolutionizing all major spheres of human life. The advent of IoT and its applications in many fields like sensing, healthcare and industry, result exponential increase in multimedia data, that needs to be shared over insecure networks. IoT driven setups are however constrained in terms of resources as a result of their small size. From data security point of view a conventional algorithms cannot be used for data encryption on an IoT platform given the resource constraints. The work presented in this paper studies the performance of SIMON cryptographic algorithm and proposes a light-weight-cryptography algorithm based on SIMON for its possible use in an IoT driven setup. The focus is on speed enhancement benefitting from software prospective, making it different than common studies mostly reflecting hardware implementations. To achieve performance in practical prospective, the contribution looks into SIMON cipher's characteristics considering utilizing it for internet of things (IoT) healthcare applications. The paper suggests further improvement to implement the original SIMON cryptography in order to reduce the encryption time and maintain the practical trade-off between security and performance. The proposed work has been compared to Advanced Encryption Standard (AES) and the original SIMON block cipher algorithms in terms of execution time, memory consumption. The results show that the proposed work is suitable for securing data in an IoT driven setup. [ABSTRACT FROM AUTHOR]

Secure data transmission over the public channels have high impact and increasingly important due to theft and manipulation in contents. The requirement of public/ private organizations to develop an efficient scheme to provide security to their contents. We developed a digital contents encryption scheme based Arnold scrambling and Lucas series, which is very simple to implement but almost impossible to breach in this article. We perform encryption at standard images by using Lucas series at different iterations of scrambled images of Arnold transform. Numerical simulation analyses performed to analyze the efficiency and effectiveness of the projected structure. [ABSTRACT FROM AUTHOR]

The traditional digital data security mechanisms follow either cryptography or authentication. The primary point of contention with these mechanisms remains either memorizing or securely storing the user's credentials. The proposed work addresses this critical issue by presenting a fingerprint biometric-based mechanism to protect users' digitized documents. In our approach, biometric features are extracted from the user's fingerprint captured with a fingerprint biometric sensor. The extracted features are then used to generate a unique code utilizing the convolution coding principle. This unique code is further used to generate a cryptographic key for encryption and decryption of the user's document. A sedulous investigation to our approach which includes experimentation with a variety of standard fingerprint images as the database starkly reveals a staggering 95.12 % true positive and 0 % as false negative. Further, the advantages of our approach are that it generates a unique key for each user and eliminates the storage of any biometric template or key. In addition, it is faster and accurate enough to develop any robust data storage security system. [ABSTRACT FROM AUTHOR]

A visually secure multiple image encryption using chaotic map and compressive sensing is proposed. The existing image encryption algorithms transform a secret image into a random noise like cipher image which can lead to cryptanalysis by an intruder. In the proposed method, compressive sampling is done using a chaos based, key controlled measurement matrix. An image dependent key generation scheme is used to generate the parameters of the chaotic map. The secret images are transformed into wavelet coefficients, and scrambled along a zigzag path, so that the high correlation among them can be reduced and thereby provide increased security level. The sparse coefficients are measured using the chaotic map-based measurement matrix, whose initial parameters are obtained from the keys generated. Then the reduced measurements are embedded into the sub-bands of the wavelet transformed cover image. Therefore, the proposed algorithm is highly sensitive to the secret images and can effectively withstand known-plaintext and chosen-plaintext attacks. Additionally, the cipher image and the secret images are of same size and do not require additional transmission bandwidth and storage space. [ABSTRACT FROM AUTHOR]

Biometric authentication is being vastly used in identity verification for several IoT applications, nowadays. The security and privacy of the biometrics templates used in the authentication process becomes mandatory as it contains rich personal information of the user. Cancelable Biometric System (CBS) is a template securing approach using repeated distortions/transformations at feature/signal level. It is an effective template securing approach which provides non-invertibility, revocability and diversity to the users enrolled with the cancelable template database. The cancelable template database containing cancelable biometric templates of the users is typically stored in a trusted standalone server. To meet the growing demand of IoT applications, cloud computing with provision to store and process even large database, is being largely deployed. However, the security and privacy of the data stored in the cloud is uncertain. In this paper, we have proposed a novel partial DCT-based CBS with privacy and security preservation for providing authentication services in various IoT applications. We have also devised techniques for session key agreement, data encryption and data integrity in the proposed framework to solve the issues of confidentiality, integrity, and availability (CIA) during cancelable template enrolment and authentication. The experimental results and analysis prove that proposed approach performs user authentication with high accuracy and minimal overhead while preserving security and privacy of sensitive cancelable biometric templates. [ABSTRACT FROM AUTHOR]

Multimedia file like audio demands special encryption technique due to its large data capacity without compromising correlation between it's original and encrypted version (closer to zero). Most of the popular block cipher techniques work on multiple rounds whereas the proposed scheme guarantees the necessary low correlation between the original and the encrypted file without multiple rounds. The unique feature is that the consecutive blocks use different keys derived from the original one using the proposed key chaining algorithm and experimental results show that the correlation between the consecutive keys is also close to zero. The used encryption technique is based on DNA encoding with logistic chaotic map using the generated chain of keys. Furthermore, the concept of channel shuffling is introduced to make the encrypted data more secure. The experimental results confirm that the correlation between the original and ciphered block is close to zero and number of samples change rate value is close to 100. Again correlation between the two consecutive ciphered blocks is also close to zero, which conforms the acceptability of proposed scheme. [ABSTRACT FROM AUTHOR]

The primary requirement of Secure Signal Processing (SSP) is to protect the identity and content of the transmitted data. To this end, various encryption techniques are employed. Homomorphic encryption in general and Paillier cryptosystem in particular is found to be one such algorithm suitable for image processing applications. It offers additive privacy homomorphism. In this paper, the Paillier encryption is employed for watermarking of six different compressed images in ASWDR (Adaptively Scanned Wavelet Difference Reduction) domain. The results are found to be encouraging both in terms of visual quality and the correlation coefficient values. The proposed watermarking scheme ensures robustness towards selected image processing attacks. The encryption parameters like NPCR (Number of Pixels Change Rate), UACI (Unified Average Changing Intensity) and Encryption Speed are evaluated. The proposed technique is compared with the one in SPIHT (Set Partitioning in Hierarchical Trees) domain. The experimental results obtained for ASWDR compression are better placed in comparison to those obtained by SPIHT compression. The proposed scheme is further analyzed in view of other recent schemes carried out by using RSA as an encryption tool in DWT domain. It is concluded that our proposed scheme is better placed in comparison to this scheme. [ABSTRACT FROM AUTHOR]

The exponential growth in the medical images is making the healthcare industry move towards cloud-based paradigm, which has vast storage and high end processing facilities. However, moving medical images containing highly sensitive data to third-party cloud servers brings in serious security threats. Even though encrypting medical images before outsourcing using traditional encryption schemes seem to be a feasible solution, that can not support encrypted domain processing. In this paper, we propose an affine Hill cipher based scheme for encrypted domain medical image fusion. The random vectors used in this scheme are carefully designed to preserve the randomness and security properties when operations are performed on the encrypted data. The proposed scheme offers data privacy and supports encrypted domain processing with no additional storage burden at the cloud side and very low computational burden at the healthcare provider side. The security of the proposed scheme is evaluated through extensive cryptanalysis in terms of resistance against various statistical attacks. The performance of the proposed scheme is analyzed by comparing various metrics of encrypted domain MR-CT/PET image fusion results with those of plaintext domain fusion. The values of structural similarity index, normalized correlation coefficient and structural content are 1 and the image quality index is 0.999, which show that the proposed encrypted domain image fusion provides same accuracy levels as that of plaintext domain image fusion. [ABSTRACT FROM AUTHOR]

In order to achieve extraction perceptual features from the encryption speech as a search digest for the content-based encryption speech retrieval, we present a retrieval algorithm of encrypted speech based on short-term cross-correlation and perceptual hashing in this paper. Firstly, the study encrypts the speech file and uploads the encrypted speech data to the encryption speech database in cloud server. Secondly, the sample speech clips are obtained by the cutting operation from the speech file for scrambling encryption. The perceptual hashing sequence of the encrypted speech is constructed by extracting the short-term cross-correlation of the encrypted speech signals as the search digest. These perceptual hashing sequences are uploaded into the hashing index table of cloud server. Finally, the Hamming distance algorithm is used for the matching retrieval operation during the search. The experimental results show that the proposed algorithm of encrypted speech perceptual hashing has a better discrimination, robustness and compactness, and the perceptual hashing sequences can be extracted directly from the encrypted sample speech. Meanwhile, the encryption speech signal has high recall and precision ratios after various content preserving operations. In the whole retrieval process, the downloading and decrypting operations of speech data are not necessary. [ABSTRACT FROM AUTHOR]

In this paper, a different cryptographic method is introduced by using a Power series transform. A new algorithm for cryptography is produced. The extended Laplace transform of the exponential function is used to encode an explicit text. The key is generated by applying the modular arithmetic rules to the coefficients obtained in the transformation. Here, ASCII codes used to hide the mathematically generated keys to strengthen the encryption. Text steganography is used to make it difficult to break the password. The made encryption is reinforced by image steganography. To hide the presence of the cipher text, it is embedded in another open text with a stenography method. Later, this text is buried in an image. For decryption, it is seen that the inverse of the Power series transform can be used for decryption easily. Experimental results are obtained by making a simulation of the proposed method. As a result, it is stated that the proposed method can be used in crypto machines. [ABSTRACT FROM AUTHOR]

The idea of digitizing documents to be archived or shared has given rise to a variety of new data types such as 3D meshes. The sharing of this data type between remote users, using high-speed computer networks and remote multimedia databases, poses great security problems. As a solution, we propose, in this paper, a new crypto watermarking algorithm. The originality of this work lies in joining cryptography with digital watermarking to secure 3D multiresolution meshes. To this end, three steps should be executed. The first is the watermark preparation. It consists, firstly, in applying the Secure Hash Algorithm 1 algorithm to generate an electronic signature of the mesh source. Secondly, the logo undergoes an encryption using Advanced Encryption Standard algorithm. To end this step, the signature and the encrypted logo pass through a convolutional encoder to obtain a codeword. As for the second step, it is called mesh preparation and it consists in applying a spiral scanning method to the mesh to split it into Groups Of Triangles. For each Group Of Triangles, a wavelet transform is applied to generate the corresponding Wavelet coefficients vector. Finally, embedding data occurs using the cylindrical coordinate system, a modulation and the least Significant Bit method. The experiment of our algorithm proves that it allows a very high insertion rate without influencing the mesh quality. Our algorithm also minimizes the amount of memory used. Moreover, it is robust against the most popular attacks. Our results show that our algorithm presents an improvement in comparison with recently published results. [ABSTRACT FROM AUTHOR]

Rapid growth in the use of digitized images in commercial, business, government and medical use has led to the need for protecting the images against eavesdroppers and securely transmit them in the network. Images pertained to finance, medical and crime investigation fields are expected to be confidential because of its sensitivity. As reported in the literature most of encryption algorithms developed for gray images is only applied for color images. An exclusive system to exploit color spaces has been proposed that functions in a multilayered model. It is named as HybRid multilAyereD chaotic ImAge eNcrypTion (RADIANT) system to process sensitive color images especially applicable for medical and forensic domains. In the first layer, logistic mapping is done to perform chaotic masking, followed by DNA encoding in the second layer. This layer objective is to increase confusion diffusion level by substitution permutation. In the third layer, ECC over GF(p) that focus on spatial domain is adopted for encryption as it has been identified as a prominent encryption technique being popular for its mathematical strength. The proposed RADIANT system is hybrid in nature as it operates on both symmetric and asymmetric cryptosystem combination. Experimental results obtained by testing with bench mark images ascertain an ideal measure for MSE, PSNR that makes it more suitable for signal processing activities involving sensitive color images. [ABSTRACT FROM AUTHOR]

An image cryptosystem using chaotic compressive sensing is designed to achieve simultaneous compression - encryption. Compressive sensing requires a measurement matrix to compressively sample a sparse signal and to guarantee its recovery at the receiver. In this paper, a new one-dimensional chaotic map is proposed which is used to construct the chaotic measurement matrix. Performance analysis demonstrates that the proposed chaotic map is highly chaotic, ergodic, highly sensitive to the initial conditions and suitable for chaotic compressive sensing. The parameters of the chaotic system are used as the secret key in the construction of measurement matrix and also the masking matrix. The sparse representation of the image is obtained using discrete wavelet transform. The sparse coefficients are then compressively sampled and encrypted using the chaotic measurement matrix and masking matrix. A parallel compressive sensing framework is employed which greatly improves the efficiency of the proposed chaotic compressive sensing scheme. Simulation results shows that the proposed scheme has good security performance against various attacks and better reconstruction performance, when compared with the commonly used random measurement matrix. [ABSTRACT FROM AUTHOR]

In today's digital world, security is a preeminent element in the transmission of digital images. In this paper, image encryption algorithm is proposed using fractional transform and scrambling along with multimodal biometric keys. For unauthorized persons, it is very difficult to retrieve the biometric keys. Firstly, both iris and fingerprint binary codes are XORed and given to the original image. This randomized image is secured using fractional order as a key. The significant feature of fractional transforms benefits from its extra degree of freedom that is provided by its fractional orders. The fractional order is calculated from the iris key. To make the encryption more confusing, scrambling is used to shuffle the position of pixels. Experimental results like histogram analysis, correlation analysis, peak signal-to-noise ratio, mean square error, structural similarity index measure, spectral distortion, information entropy, key sensitivity analysis, differential attacks and spoofing attacks verify the efficacy of proposed algorithm. [ABSTRACT FROM AUTHOR]