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The purpose of this paper is to investigate two-dimensional outer totalistic cellular automata (2D-OTCA) rules other than the Game of Life rule for image scrambling. This paper presents a digital image scrambling (DIS) technique based on 2D-OTCA for improving the scrambling degree. The comparison of scrambling performance and computational effort of proposed technique with existing CA-based image scrambling techniques is also presented.

In this paper, a DIS technique based on 2D-OTCA with von Neumann neighborhood (N_vN) is proposed. Effect of three important cellular automata (CA) parameters on gray difference degree (GDD) is analyzed: first the OTCA rules, afterwards two different boundary conditions and finally the number of CA generations (k) are tested. The authors selected a random sample of gray-scale images from the Berkeley Segmentation Data set and Benchmark, BSDS300 (www2.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/) for the experiments. Initially, the CA is setup with a random initial configuration and the GDD is computed by testing all OTCA rules, one by one, for CA generations ranging from 1 to 10. A subset of these tested rules produces high GDD values and shows positive correlation with the k values. Subsequently, this sample of rules is used with different boundary conditions and applied to the sample image data set to analyze the effect of these boundary conditions on GDD. Finally, in order to compare the scrambling performance of the proposed technique with the existing CA-based image scrambling techniques, the authors use same initial CA configuration, number of CA generations, k=10, periodic boundary conditions and the same test images.

The experimental results are evaluated and analyzed using GDD parameter and then compared with existing techniques. The technique results in better GDD values with 2D-OTCA rule 171 when compared with existing techniques. The CPU running time of the proposed algorithm is also considerably small as compared to existing techniques.

In this paper, the authors focused on using von Neumann neighborhood (N_vN) to evolve the CA for image scrambling. The use of N_vN reduced the computational effort on one hand, and reduced the CA rule space to 1,024 as compared to about 2.62 lakh rule space available with Moore neighborhood (N_M) on the other. The results of this paper are based on original analysis of the proposed work.

The purpose of this paper is to present an imperceptible and robust watermarking algorithm with high embedding capacity for digital images based on discrete wavelet transform (DWT) domain.

First, the watermark image is scrambled using chaotic sequence and mapped to avoid the block effect after embedding watermark into the host image. Then, the scrambled watermark is inserted in LH₂ and HL₂ sub‐bands of the DWT of the host image to provide a good tradeoff between the transparency and the robustness of watermarks.

This paper presents experimental results and compares the results to other methods. It can be seen from the comparison that this method can obtain a better performance in many cases.

One of the main differences of this technique, compared to other wavelet watermarking techniques, is in the selection of the wavelet coefficients of the host image. When performing second level of the DWT, most methods in the current literature select the approximation sub‐band (LL₂) to insert the watermark. The technique presented in this paper decomposes the image using DWT twice, and then obtains the significant coefficients (LH₂ and HL₂ sub‐bands) of the host image to insert the watermark.

Several chaotic system-based encryption techniques have been presented in recent years to protect digital images using cryptography. The challenges of key distribution and administration make symmetric encryption difficult. The purpose of this paper is to address these concerns, the novel hybrid partial differential elliptical Rubik’s cube algorithm is developed in this study as an asymmetric image encryption approach. This novel algorithm generates a random weighted matrix, and uses the masking method on image pixels with Rubik’s cube principle. Security analysis has been conducted, it enhances and increases the reliability of the proposed algorithm against a variety of attacks including statistical and differential attacks.

In this light, a differential elliptical model is designed with two phases for image encryption and decryption. A modified image is achieved by rotating and mixing intensities of rows and columns with a masking matrix derived from the key generation technique using a unique approach based on the elliptic curve and Rubik’s cube principle.

To evaluate the security level, the proposed algorithm is tested with statistical and differential attacks on a different set of test images with peak signal-to-noise ratio, unified average changed intensity and number of pixel change rate performance metrics. These results proved that the proposed image encryption method is completely reliable and enhances image security during transmission.

The elliptic curve–based encryption is hard to break by hackers and adding a Rubik’s cube principle makes it even more complex and nearly impossible to decode. The proposed method provides reduced key size.

Food fraud as intentional deception for economic gain relies on a low-tech food value chain, that applies a ‘paper-and-pencil approach’, unable to provide reliable and trusted data about food products, accompanied processes/activities and actors involved. Such approach has created the information asymmetry that leads to erosion of stakeholders and consumers trust, which in turn discourages cooperation within the food chain by damaging its ability to decrease uncertainty and capability to provide authentic, nutritional, accessible and affordable food for all. Lack of holistic approach, focus on stand-alone measures, lack of proactive measures and undermined role of customers have been major factors behind weaknesses of current anti-fraud measures system. Thus, the process of strong and fast digitalisation enabled by the new emerging technology called Industry 4.0 is a way to provide a shift from food fraud detection to efficient prevention. Therefore, the objective of this chapter is to shed light on current challenges and opportunities associated with Industry 4.0 technology enablers' guardian role in food fraud prevention with the hope to inform future researchers, experts and decision-makers about opportunities opened up by transforming to new cyber-physical-social ecosystem, or better to say ‘self-thinking’ food value chain whose foundations are already under development. The systematic literature network analysis is applied to fulfil the stated objective. Digitalisation and Industry 4.0 can be used to develop a system that is cost effective and ensures data integrity and prevents tampering and single point failure through offering fault tolerance, immutability, trust, transparency and full traceability of the stored transaction records to all agri-food value chain partners. In addition, such approach lays a foundation for adopting new business models, strengthening food chain resilience, sustainability and innovation capacity.

Maps can be challenging to reference librarians, especially to those without the specialized skills needed for working with the material. Such is the same with maps found on the Internet. Finding, using, saving, or printing maps requires different strategies than those taken with other online documents. This article discusses the value of electronic maps, will help to form accurate expectations as to what one should expect to find, and cover some useful Internet sites for finding freely available general maps. Last, some strategies in working with large graphic files will assist reference librarians in putting electronic maps into the hands of their patrons.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

Wu et al.'s scheme has a security problem that is related to anonymity: attackers can determine by interception the identity of a legal user. This paper aims to propose a new secure authentication which combines a chaos system with an Arnold cat map. The scheme improves upon that of the Wu et al.'s scheme. The scheme proposed herein provides for full anonymity and improves the security of authentication messages for wireless communications.

A novel scheme that integrates a chaos sequence is used with an Arnold cat map for authentication messages. Authentication messages are shuffled using an Arnold cat map to improve the security of authentication in wireless communications. An analytic approach based on a chaos sequence with an Arnold cat map is developed to secure authentication. The proposed scheme is presented in this study to overcome the inherent drawbacks of existing designs.

The integrated scheme involves two steps. First, a chaos map is used to generate a set of chaos sequences that is added to the authentication messages. Second, the authentication messages are shuffled using an Arnold cat map. The main feature of the proposed design is such that the chaos systems are sensitive to the initial values of conditions. Sensitivity will lead to long-term behavior unpredictability to reflect the non-linear dynamic systems. Furthermore, to increase the complexity of the authentication message, the authors also use an Arnold cat map.

The proposed scheme provides functions that include full anonymity properties, protection of the real identity of the user, one-time password properties, timestamp benefits and sufficient complexity of the password. The analysis shows that the proposed scheme exhibits the advantages of the chaos system and is more secure than previous schemes. Notably, the proposed scheme is effective for wireless communications.

The manufacturing of intelligent and secure visual data transmission over the wireless sensor network is key requirement nowadays to many applications. The two-way transmission of image under a wireless channel needed image must compatible along channel characteristics such as band width, energy-efficient, time consumption and security because the image adopts big space under the device of storage and need a long time that easily undergoes cipher attacks. Moreover, Quizzical the problem for the additional time under compression results that, the secondary process of the compression followed through the acquisition consumes more time.

Hence, for resolving these issues, compressive sensing (CS) has emerged, which compressed the image at the time of sensing emerges as a speedy manner that reduces the time consumption and saves bandwidth utilization but fails under secured transmission. Several kinds of research paved path to resolve the security problems under CS through providing security such as the secondary process.

Thus, concerning the above issues, this paper proposed the Corvus corone module two-way image transmission that provides energy efficiency along CS model, secured transmission through a matrix of security under CS such as inbuilt method, which was named as compressed secured matrix and faultless reconstruction along that of eminent random matrix counting under CS.

Experimental outputs shows intelligent module gives energy efficient, secured transmission along lower computational timing also decreased bit error rate.

The purpose of this paper is to investigate how subtle religious representations affect prosocial behavior. The authors study the impact of religious representations on prosocial behavior in terms of cooperation in a one‐shot/three‐person public goods game.

The authors used the scrambled sentence task to prime participants with religious words before they were asked to make a one‐shot/three‐person public goods game decision.

Both in the raw data and when controlling for factors such as age, gender and religious beliefs, the authors found that priming of religious representations increased cooperation in the experiment, that is, increased contributions to the public good. The authors found no significant interaction effects between priming and self‐reported measures of religiosity, suggesting that the priming effect was present among both self‐reported religious and nonreligious participants. Self‐reported measures of religiosity were not correlated with cooperation in this study.

The paper adds to the growing body of experimental economics literature that has studied self‐reported measures of religiosity alongside behavior in different economic games. This study contributes to the literature by examining the effect of subtle influences of religion on cooperation. Also, in contrast to previous economic literature, the paper examines the direct impact of religion as an independent variable on cooperation.

The purpose of this paper is to monitor the changes of delivery of city branding advertisements in China and to try to find a tendency of city branding ads in the delivery for the future.

The quantitative research methods used in this paper study the advertisements with city image messages in 13 China Central Television (CCTV) channels that appeared between the year of 2007 to 2010 – a total of 320,653 advertisements. This paper is based on several data sets: advertisement producers, regional distribution of producers, advertisement time slots, types of advertisings, and other such categories. In addition, they have also studied city branding advertisings from international producers in terms of channel selections, program choices, and media outlet choices and so forth.

Through an analysis of quantity and total duration of city image advertisements, it can be concluded that first‐tier cities have been reducing the broadcasting of city image ads domestically yearly, and third‐tier cities are proving to be a significant power in producing city branding advertisements. Significantly, the eastern littoral region has surpassed the central and west region both in the duration and in growth rate of city branding advertisements. Moreover, between 2007 and 2010, a total of nine foreign cities have produced city branding advertisements on CCTV channels. Unlike cities in China, international cities have scattered their ads widely across different periods of one day.

Finally, based on analysis of advantages and disadvantages in city image advertisements strategies applied by those advanced cities at home and abroad, this author hopes this study can offer some scientifically based reference point for other cities.

Based on analysis of advantages and disadvantages in city image advertisements strategies applied by those advanced cities at home and abroad, this study tries to offer some scientifically based reference point for other cities.