Biblio

Since the last few decades, several chaotic encryption techniques are reported by different researchers. Although the cryptanalysis of some techniques shows the feebler resistance of those algorithms against any weaker attackers. However, different hyper-chaotic based and DNA-coding based encrypting methods are introduced recently. Though, these methods are efficient against several attacks, but, increase complexity as well. On account of these drawbacks, we have proposed a novel technique of chaotic encryption of an image using the integer wavelet transform (IWT) and global bit scrambling (GBS). Here, the image is transformed and decomposed by IWT. Thereafter, a chaotic map is used in the encryption algorithm. A key-dependent bit scrambling (GBS) is introduced rather than pixel scrambling to make the encryption stronger. It enhances key dependency along with the increased resistance against intruder attacks. To check the fragility and dependability of the algorithm, a sufficient number of tests are done, which have given reassuring results. Some tests are done to check the similarity between the original and decrypted image to ensure the excellent outcome of the decryption algorithm. The outcomes of the proposed algorithm are compared with some recent works' outputs to demonstrate its eligibility.

In recent years, there is fast growth in the high throughput DNA sequencing technology, and also there is a reduction in the cost of genome-sequencing, that has led to a advances in the genetic industries. However, the reduction in cost and time required for DNA sequencing there is still an issue of managing such large amount of data. Also, the security and transmission of such huge amount of DNA sequence data is still an issue. The idea is to provide a secure storage platform for future generation bioinformatics systems for both researchers and healthcare user. Secure data sharing strategies, that can permit the healthcare providers along with their secured substances for verifying the accuracy of data, are crucial for ensuring proper medical services. In this paper, it has been surveyed about the applications of blockchain technology for securing healthcare data, where the recorded information is encrypted so that it becomes difficult to penetrate or being removed, as the primary goals of block-chaining technology is to make data immutable.

Some of the key challenges in steganography are imperceptibility and resistance to detection of steganalysis algorithms. Zero steganography is an approach to data hiding such that the cover image is not modified. This paper focuses on the generation of stego-key, which is an essential component of this steganographic approach. This approach utilizes DNA sequences and shifting and flipping operations in its binary code representation. Experimental results show that the key generation algorithm has a low cracking probability. The algorithm satisfies the avalanche criterion.

Hiding information is a process to hide data or include it in different digital media such as image, audio, video, and text. However, there are many techniques to achieve the process of hiding information in the image processing, in this paper, a new method has been proposed for hidden data mechanism (which is a text file), then a transposition cipher method has been employed for encryption completed. It can be used to build an encrypted text and also to increase security against possible attacks while sending it over the World Wide Web. A genetic algorithm has been affected in the adjustment of the encoded text and DNA in the creation of an encrypted text that is difficult to detect and then include in the image and that affected the image visual quality. The proposed method outperforms the state of arts in terms of efficiently retrieving the embedded messages. Performance evaluation has been recorded high visual quality scores for the (SNR (single to noise ratio), PSNR (peak single to noise ratio) and MSE (mean square error).

In this paper, a novel DNA based computing method is proposed for encryption of biometric color(face)and gray fingerprint images. In many applications of present scenario, gray and color images are exhibited major role for authenticating identity of an individual. The values of aforementioned images have considered as two separate matrices. The key generation process two level mathematical operations have applied on fingerprint image for generating encryption key. For enhancing security to biometric image, DNA computing has done on the above matrices generating DNA sequence. Further, DNA sequences have scrambled to add complexity to biometric image. Results of blending images, image of DNA computing has shown in experimental section. It is observed that the proposed substitution DNA computing algorithm has shown good resistant against statistical and differential attacks.

In digital communication, the transmission of medical images over communication network is very explosive. We need a communication system to transmit the medical information rapidly and securely. In this manuscript, we propose a cryptosystem with novel encoding strategy and lossless compression technique. The chaos based DNA cryptography is used to enrich security of medical images. The lossless Discrete Haar Wavelet Transform is used to reduce space and time efficiency during transmission. The cryptanalysis proves that proposed cryptosystem is secure against different types of attacks. The compression ratio and pixel comparison is performed to verify the similarity of retained medical image.

The intensity of DNA figuring will reinforce the current security on frameworks by opening up another probability of a half and half cryptographic framework. Here, we are exhibiting the DNA S-box for actualizing cryptographic algorithm. The DNA based S-Box is designed using vivado software and implemented using Artix-7 device. The main aim is to design the DNA based S-box to increase the security. Also pipelining and parallelism techniques are to be implement in future to increase the speed.

Cryptography is the method of transforming the original texted message into an unknown form and in reverse also. It is the process of hiding and forwarding the data in an appropriate form so that only authorized persons can know and can process it. Cryptographic process secures the data from hijacking or transmutation, it is mainly used for users data security. This paper justifies the encryption and decryption using DNA(Deoxyribo Nucleic Acid) sequence. This process includes several intermediate steps, the perception of binary-coded form and generating of arbitrary keys is used to encrypt the message. A common key should be established between the sender and receiver for encryption and decryption process. The common key provides more security to the sequence. In this paper, both the process of binary-coded form and generating of arbitrary keys are used to encrypt the message. It is widely used in an institution and by every individual to hide their data from the muggers and hijackers and provides the data securely, and confidentially over the transmission of information.

The Internet has changed business, education, healthcare, banking etc. and it is the main part of technological evolution. Internet provides us a connecting world to perform our day to day life activities easily. Internet is designed in such a way that it can uniquely identify machine, not a person, on the network hence there is need to design a system that can perform entity identification on the Internet. Currently on Internet, service providers provide identity of a user with user name and password and store this information on a centralized server. These servers become honey pot for hackers to steal user’s personal identity information and service provider can utilize user identity information using data mining, artificial intelligence for economic benefits. Aim of Self sovereign identity system is to provide decentralized, user centric identity system which is controlled by identity owner that can be developed along with distributed ledger technology i.e. blockchain. In this paper, we intend to make an exhaustive study on different blockchain based self sovereign identity implementations (such as Sovrin, Uport, EverID, LifeID, Sora, SelfKey) along with its architectural components and discuss about use case of self sovereign identity.

ARtect is an Augmented Reality application developed with Unity 3D, which envisions an educational interactive and immersive tool for architects, designers, researchers, and artists. This digital instrument renders the competency to visualize custom-made 3D models and 2D graphics in interior and exterior environments. The user-friendly interface offers an accurate insight before the materialization of any architectural project, enabling evaluation of the design proposal. This practice could be integrated into learning architectural design process, saving resources of printed drawings, and 3D carton models during several stages of spatial conception.

Experimentation focused on assessing the value of complex visualisation approaches when compared with alternative methods for data analysis is challenging. The interaction between participant prior knowledge and experience, a diverse range of experimental or real-world data sets and a dynamic interaction with the display system presents challenges when seeking timely, affordable and statistically relevant experimentation results. This paper outlines a hybrid approach proposed for experimentation with complex interactive data analysis tools, specifically for computer network traffic analysis. The approach involves a structured survey completed after free engagement with the software platform by expert participants. The survey captures objective and subjective data points relating to the experience with the goal of making an assessment of software performance which is supported by statistically significant experimental results. This work is particularly applicable to field of network analysis for cyber security and also military cyber operations and intelligence data analysis.

Advancements in the AI field unfold tremendous opportunities for society. Simultaneously, it becomes increasingly important to address emerging ramifications. Thereby, the focus is often set on ethical and safe design forestalling unintentional failures. However, cybersecurity-oriented approaches to AI safety additionally consider instantiations of intentional malice – including unethical malevolent AI design. Recently, an analogous emphasis on malicious actors has been expressed regarding security and safety for virtual reality (VR). In this vein, while the intersection of AI and VR (AIVR) offers a wide array of beneficial cross-fertilization possibilities, it is responsible to anticipate future malicious AIVR design from the onset on given the potential socio-psycho-technological impacts. For a simplified illustration, this paper analyzes the conceivable use case of Generative AI (here deepfake techniques) utilized for disinformation in immersive journalism. In our view, defenses against such future AIVR safety risks related to falsehood in immersive settings should be transdisciplinarily conceived from an immersive co-creation stance. As a first step, we motivate a cybersecurity-oriented procedure to generate defenses via immersive design fictions. Overall, there may be no panacea but updatable transdisciplinary tools including AIVR itself could be used to incrementally defend against malicious actors in AIVR.

Web technology has evolved to offer 360-degree immersive browsing experiences. This new technology, called WebVR, enables virtual reality by rendering a three-dimensional world on an HTML canvas. Unfortunately, there exists no browser-supported way of sharing this canvas between different parties. As a result, third-party library providers with ill intent (e.g., stealing sensitive information from end-users) can easily distort the entire WebVR site. To mitigate the new threats posed in WebVR, we propose CanvasMirror, which allows publishers to specify the behaviors of third-party libraries and enforce this specification. We show that CanvasMirror effectively separates the third-party context from the host origin by leveraging the privilege separation technique and safely integrates VR contents on a shared canvas.

New technologies, such as augmented reality (AR) are used to enhance human capabilities and extend human functioning; nevertheless they may cause distraction and incorrect human functioning. Systems including socio entities (such as human) and technical entities (such as augmented reality) are called socio-technical systems. In order to do risk assessment in such systems, considering new dependability threats caused by augmented reality is essential, for example failure of an extended human function is a new type of dependability threat introduced to the system because of new technologies. In particular, it is required to identify these new dependability threats and extend modeling and analyzing techniques to be able to uncover their potential impacts. This research aims at providing a framework for risk assessment in AR-equipped socio-technical systems by identifying AR-extended human failures and AR-caused faults leading to human failures. Our work also extends modeling elements in an existing metamodel for modeling socio-technical systems, to enable AR-relevant dependability threats modeling. This extended metamodel is expected to be used for extending analysis techniques to analyze AR-equipped socio-technical systems.

Unilateral spatial neglect (USN) is a higher cognitive dysfunction that can occur after a stroke. It is defined as an impairment in finding, reporting, reacting to, and directing stimuli opposite the damaged side of the brain. We have proposed a system to identify neglected regions in USN patients in three dimensions using three-dimensional virtual reality. The objectives of this study are twofold: first, to propose a system for numerically identifying the neglected regions using an object detection task in a virtual space, and second, to compare the neglected regions during object detection when the patient's neck is immobilized (‘fixed-neck’ condition) versus when the neck can be freely moved to search (‘free-neck’ condition). We performed the test using an immersive virtual reality system, once with the patient's neck fixed and once with the patient's neck free to move. Comparing the results of the study in two patients, we found that the neglected areas were similar in the fixed-neck condition. However, in the free-neck condition, one patient's neglect improved while the other patient’s neglect worsened. These results suggest that exploratory ability affects the symptoms of USN and is crucial for clinical evaluation of USN patients.

Analyzing multi-dimensional geospatial data is difficult and immersive analytics systems are used to visualize geospatial data and models. There is little previous work evaluating when immersive and non-immersive visualizations are the most suitable for data analysis and more research is needed.

This paper investigates the effects of real time visual biofeedback for improving sports performance using a large scale immersive mixed reality system in which users are able to play a simulated game of curling. The users slide custom curling stones across the floor onto a projected target whose size is dictated by the user’s stress-related physiological measure; heart rate (HR). The higher HR the player has, the smaller the target will be, and vice-versa. In the experiment participants were asked to compete in three different conditions: baseline, with and without the proposed biofeedback. The results show that when providing a visual representation of the player’s HR or "choking" in competition, it helped the player understand their condition and improve competition performance (P-value of 0.0391).

Despite advances regarding autonomous functionality for robots, teleoperation remains a means for performing delicate tasks in safety critical contexts like explosive ordnance disposal (EOD) and ambiguous environments. Immersive stereoscopic displays have been proposed and developed in this regard, but bring about their own specific problems, e.g., simulator sickness. This work builds upon standardized test environments to yield reproducible comparisons between different robotic platforms. The focus was placed on testing three optronic systems of differing degrees of immersion: (1) A laptop display showing multiple monoscopic camera views, (2) an off-the-shelf virtual reality headset coupled with a pantilt-based stereoscopic camera, and (3) a so-called Telepresence Unit, providing fast pan, tilt, yaw rotation, stereoscopic view, and spatial audio. Stereoscopic systems yielded significant faster task completion only for the maneuvering task. As expected, they also induced Simulator Sickness among other results. However, the amount of Simulator Sickness varied between both stereoscopic systems. Collected data suggests that a higher degree of immersion combined with careful system design can reduce the to-be-expected increase of Simulator Sickness compared to the monoscopic camera baseline while making the interface subjectively more effective for certain tasks.

The availability of commercial fully immersive virtual reality systems allows the proposal and development of new applications that offer novel ways to visualize and interact with multidimensional neuroimaging data. We propose a system for the visualization and interaction with Magnetic Resonance Imaging (MRI) scans in a fully immersive learning environment in virtual reality. The system extracts the different slices from a DICOM file and presents the slices in a 3D environment where the user can display and rotate the MRI scan, and select the clipping plane in all the possible orientations. The 3D environment includes two parts: 1) a cube that displays the MRI scan in 3D and 2) three panels that include the axial, sagittal, and coronal views, where it is possible to directly access a desired slice. In addition, the environment includes a representation of the brain where it is possible to access and browse directly through the slices with the controller. This application can be used both for educational purposes as an immersive learning tool, and by neuroscience researchers as a more convenient way to browse through an MRI scan to better analyze 3D data.

This article describes the development of two mobile applications for learning Digital Electronics. The first application is an interactive app for iOS where you can study the different digital circuits, and which will serve as the basis for the second: a game of questions in augmented reality.

FinBots are chatbots built on automated decision technology, aimed to facilitate accessible banking and to support customers in making financial decisions. Chatbots are increasing in prevalence, sometimes even equipped to mimic human social rules, expectations and norms, decreasing the necessity for human-to-human interaction. As banks and financial advisory platforms move towards creating bots that enhance the current state of consumer trust and adoption rates, we investigated the effects of chatbot vignettes with and without socio-emotional features on intention to use the chatbot for financial support purposes. We conducted a between-subject online experiment with N = 410 participants. Participants in the control group were provided with a vignette describing a secure and reliable chatbot called XRO23, whereas participants in the experimental group were presented with a vignette describing a secure and reliable chatbot that is more human-like and named Emma. We found that Vignette Emma did not increase participants' trust levels nor lowered their privacy concerns even though it increased perception of social presence. However, we found that intention to use the presented chatbot for financial support was positively influenced by perceived humanness and trust in the bot. Participants were also more willing to share financially-sensitive information such as account number, sort code and payments information to XRO23 compared to Emma - revealing a preference for a technical and mechanical FinBot in information sharing. Overall, this research contributes to our understanding of the intention to use chatbots with different features as financial technology, in particular that socio-emotional support may not be favoured when designed independently of financial function.

In recent days the attention of the researchers has been grabbed by the advent of fog computing which is found to be a conservatory of cloud computing. The fog computing is found to be more advantageous and it solves mighty issues of the cloud namely higher delay and also no proper mobility awareness and location related awareness are found in the cloud environment. The IoT devices are connected to the fog nodes which support the cloud services to accumulate and process a component of data. The presence of Fog nodes not only reduces the demands of processing data, but it had improved the quality of service in real time scenarios. Nevertheless the fog node endures from challenges of false data injection, privacy violation in IoT devices and violating integrity of data. This paper is going to address the key issues related to homomorphic encryption algorithms which is used by various researchers for providing data integrity and authenticity of the devices with their merits and demerits.

Nowadays, Fog Computing gets more attention due to its characteristics. Fog computing provides more advantages in related to apply with the latest technology. On the other hand, there is an issue about the data security over processing of data. Fog Computing encounters many security challenges like false data injection, violating privacy in edge devices and integrity of data, etc. An encryption scheme called Homomorphic Encryption (HME) technique is used to protect the data from the various security threats. This homomorphic encryption scheme allows doing manipulation over the encrypted data without decrypting it. This scheme can be implemented in many systems with various crypto-algorithms. This homomorphic encryption technique is mainly used to retain the privacy and to process the stored encrypted data on a remote server. This paper addresses the terminologies of Fog Computing, work flow and properties of the homomorphic encryption algorithm, followed by exploring the application of homomorphic encryption in various public key cryptosystems such as RSA and Pailier. It focuses on various homomorphic encryption schemes implemented by various researchers such as Brakerski-Gentry-Vaikuntanathan model, Improved Homomorphic Cryptosystem, Upgraded ElGamal based Algebric homomorphic encryption scheme, In-Direct rapid homomorphic encryption scheme which provides integrity of data.

In cyber threat information sharing, secure transfer and protecting privacy are very important. In this paper we solve these issues by suggesting a platform based on private permissioned Blockchain, which provides us with access control as well. The platform is called Anon-ISAC and is built on the Enhanced Privacy ID (EPID) zero-knowledge proof scheme. It makes use of permissioned Blockchain as a way to keep identity anonymous. Organizations can share their information on incidents or other artifacts among trusted parties, while they keep their identity hidden. This will save them from unwanted consequences of exposure of sensitive security information.

Data privacy has been an important area of research in recent years. Dataset often consists of sensitive data fields, exposure of which may jeopardize interests of individuals associated with the data. In order to resolve this issue, privacy techniques can be used to hinder the identification of a person through anonymization of the sensitive data in the dataset to protect sensitive information, while the anonymized dataset can be used by the third parties for analysis purposes without obstruction. In this research, we investigated a privacy technique, k-anonymity for different values of on different number columns of the dataset. Next, the information loss due to k-anonymity is computed. The anonymized files go through the classification process by some machine-learning algorithms i.e., Naive Bayes, J48 and neural network in order to check a balance between data anonymity and data utility. Based on the classification accuracy, the optimal values of and are obtained, and thus, the optimal and can be used for k-anonymity algorithm to anonymize optimal number of columns of the dataset.