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E-banking requires a high level of trust because it involves disclosure of vital and confidential information which customers are often reluctant to share because of the risks involved. With the growth of technology, there has been an increase in cyber threats. While transacting online customers fear the security of their personal information to safeguard against financial losses and unwanted disturbance. Thus, customers’ perceived security and credibility have a critical role in influencing their trust in E-banking. Whereas the identified literature has not paid much attention to studying the impact of identified E-service quality dimensions (credibility and security) on E-trust, particularly in the developing nations context. Therefore, to fill the existing gap, the study seeks to measure the impact of credibility and security dimensions of E-service quality on customers’ E-trust in the context of Indian banks. The sample for the study is taken from customers of public and private sector banks of Delhi/NCR. A total of 420 complete and suitable responses were received for final analysis. During data collection, it was ensured that the respondent is over the age of 18, has an active bank account, and has been using banking E-services for at least six months. Data for the study is analyzed using FEA, CFA, and SEM via using SPSS 24 and AMOS 21 software. The findings of the study reveal that both the credibility and security dimensions of E-service quality have a strong impact in influencing customer trust in E-banking. Banks’ focus on enhancing credibility and security measures creates value in customers’ eyes that as a result enhances their faith in the service provider.

The typical model of steganography has led the prisoners' problem, in which two persons attempt to communicate covertly without alerting the warden, that is, only the receiver knows the existence of the message sent by the sender. One available way to achieve this task is to embed the message in an innocuous-looking medium. In this paper, we propose a variation of the Quantization Index Modulation (QIM) for solving the prisoners' problem. We also propose a theorem to show that the error of mean intensity value of an image block caused by JPEG compression is bounded. The proposed method embeds the messages to be conveyed by modifying the mean intensity value, and the resulting stego-image can be stored in the JPEG format with a low quality setting. Besides, a specific pattern caused by using the QIM embedding method is also identified, and this pattern will be removed using the proposed embedding method. Experimental results and the proposed theorem show that the hidden message is error-free against the JPEG distortion under the quality setting as low as 25. Furthermore, the existence of the hidden message is not only visually imperceptible but also statistically undetectable.

Recently, Android applications have been playing a vital part in the everyday life as several services are offered via mobile applications. Due of its market dominance, Android is more at danger from malicious software, and this threat is growing. The exponential growth of malicious Android apps has made it essential to develop cutting-edge methods for identifying them. Despite the prevalence of a number of security-based approaches in the research, feature selection (FS) methods for Android malware detection methods still have to be developed. In this research, researchers provide a method for distinguishing malicious Android apps from legitimate ones by using a intelligent hyperparameter tuned deep learning based malware detection (IHPT-DLMD). Extraction of features and preliminary data processing are the main functions of the IHPT-DLMD method. The proposed IHPT-DLMD technique initially aims to determine the considerable permissions and API calls using the binary coyote optimization algorithm (BCOA)-based FS technique, which aids to remove the unnecessary features. Besides, bidirectional long short-term memory (Bi-LSTM) model is employed for the detection and classification of Android malware. Finally, the glowworm swarm optimization (GSO) algorithm is applied to optimize the hyperparameters of the BiLSTM model to produce effectual outcomes for Android application classification. This IHPT-DLMD method is checked for quality using a benchmark dataset and evaluated in several ways. The test data demonstrated overall higher performance of the IHPT-DLMD methodology in comparison to the most contemporary methods that are currently in use.

Data reliability and confidence in the data are very important issues, especially when the system integrates fraud or false information. The misusing of data collected may create serious problems. With the fast development of computing techniques, much data are collected from various terminals and industrial devices. Edge computing operates by driving data, software and computer resources from the centralized network to its extremes, allowing pieces of knowledge to lie on distributed cloud networks. Its target customers continue to use commercial Internet application software for every internet customer. Edge computing is used to provide delay-free customer experience assistance for features of the Internet of Things (IoT) services on the edge of the user network. The document identifies an IoT computing platform collaborating with the edge competitive data management latency (CDML) tool. This approach separately categorizes edge layer requests and response data over time using demand-density driven optimization. A difference-based optimization optimizes the frame limits for simultaneous request processing and exact allocation of data. The architectural efficiency of edge computing can be assessed by comparing latency, bandwidth usage, and overhead. Furthermore, estimating the availability, credibility and confidentiality of security solutions within each party would take into consideration security concerns in edge computing and propose a safety assessment process for IoT networks with edge computing. This procedure is finally validated using appropriate tests, and the resulting findings are examined to demonstrate the method’s accuracy. Experimental data are used to validate methods to request maintenance and processing, response time, resource utilization and contract period. In comparison to current approaches, the results of the proposed CDML are measured with a percentage of 97.90%.

The proposed system enhances the request and response comparison ratio 97.5%, analyzing request performance ratio 98.1%, response with time analysis ratio of 98.3%, data allocation approach analysis ratio 97.7%.

In order to explore multi-directional quantum communication in a three-dimensional (3D) system, five-, seven- and $(2n+1)$-qutrit entangled states are constructed by 3D-Hadamard gates and 3D-controlled-NOT gates in this paper. Then a new scheme of controlled bidirectional quantum teleportation (QT) via five-qutrit entangled channel is proposed, where two observers can exchange their unknown single-qutrit states at the same time under the control of the supervisor. Along this mental, we propose a novel theoretical scheme to fulfil four-party controlled cyclic QT by using a seven-qutrit entangled state as the quantum channel, in which Alice can teleport an arbitrary unknown single-qutrit state to Bob, Bob can transmit an arbitrary single-qutrit state to Charlie, at the same time, Charlie can also teleport an arbitrary unknown single-qutrit state to Alice with the permission of the supervisor. In these schemes, only specific two-qutrit 3D-Bell state measurements, single-qutrit 3D-Z-basis measurements and suitable 3D-Weyl operators are needed, which can be implemented in physics easily. Moreover, the proposed four-party controlled cyclic scheme can be generalized into the case containing $n$ ($n>3$) observers by using a $(2n+1)$-qutrit entangled channel. Analysis shows that the success probability of our schemes can reach 1. Through detailed discussion, we find that the security of our schemes and the control power of the supervisors can be guaranteed, and the intrinsic efficiency of the proposed schemes is relatively high.

While B2C via cloud computing has grown rapidly, information security and trustworthy computation are still major issues in today’s industrial realm. As a result, the routine workflow process varies dynamically over the course of data transactions, resulting in uncertainty. Consumers’ private information becomes easily vulnerable due to such data uncertainty. Intruders/fake marketers may permeate deeply into their current profiles due to the Internet, which leads to the creation of fictitious online markets that, in turn, drive more demand. This evolving business interaction leverages new interlopes to target customers’ data more precisely. However, it is still lacking in terms of complete techniques for dealing with such issues. These days, uncertain B2C workflows are greatly aided by Blockchain technology, especially to most of its security-enhancing characteristics. Despite numerous existing studies that have recommended employing Blockchain to handle B2C records, it is necessary to employ the technology in such business sectors to offer secured record management, workflow and keep data with high confidentiality and integrity intact. In this study, we suggest a Distributed Decentralized Security Scheme (DDSS) that manages and secures uncertain datasets through Blockchain technology in the B2C sector. To improve the safety of data workflows, the proposed approach enables the user to verify the authenticity of the records they require. A smart contract or special chain-code is used to dictate the parameters of the suggested system, ensuring security. The findings and discussions explain that the suggested scheme is far more effective than the previous strategies and has a greater level of confidentiality and integrity strength.

In the modern world, several areas of our lives can be improved, in the form of diverse additional dimensions, in terms of quality, by machine learning. When building machine learning models, open data are often used. Although this trend is on the rise, the monetary losses since the attacks on machine learning models are also rising. Preparation is, thus, believed to be indispensable in terms of embarking upon machine learning. In this field of endeavor, machine learning models may be compromised in various ways, including poisoning attacks. Assaults of this nature involve the incorporation of injurious data into the training data rendering the models to be substantively less accurate. The circumstances of every individual case will determine the degree to which the impairment due to such intrusions can lead to extensive disruption. A modus operandi is proffered in this research as a safeguard for machine learning models in the face of the poisoning menace, envisaging a milieu in which machine learning models make use of data that emanate from numerous sources. The information in question will be presented as training data, and the diversity of sources will constitute a barrier to poisoning attacks in such circumstances. Every source is evaluated separately, with the weight of each data component assessed in terms of its ability to affect the precision of the machine learning model. An appraisal is also conducted on the basis of the theoretical effect of the use of corrupt data as from each source. The extent to which the subgroup of data in question can undermine overall accuracy depends on the estimated data removal rate associated with each of the sources described above. The exclusion of such isolated data based on this figure ensures that the standard data will not be tainted. To evaluate the efficacy of our suggested preventive measure, we evaluated it in comparison with the well-known standard techniques to assess the degree to which the model was providing accurate conclusions in the wake of the change. It was demonstrated during this test that when the innovative mode of appraisal was applied, in circumstances in which 17% of the training data are corrupt, the degree of precision offered by the model is 89%, in contrast to the figure of 83% acquired through the traditional technique. The corrective technique suggested by us thus boosted the resilience of the model against harmful intrusion.

In this paper, we consider the issue of digital camera identification based on images. This topic matches the area of digital forensics. The problem is well known in the literature and many algorithms based on camera’s fingerprint have been proposed. In this paper, we discuss the digital camera identification based on convolutional neural networks (CNN). CNNs are state-of-the-art method in computer vision and are widely utilized in many applications. Our goal is to find out whether it is possible to speed up the process of learning the networks by the images. We conduct a set of representative experiments which show that replacing the ReLU with SELU activation function and adjusting the network’s hyperparamethers (e.g. learning rate) may have a significant impact on reduction time of learning. We also consider using the dropout layer. The experiments are held on representative image dataset, consisting of many images coming from modern cameras and show effectiveness of our propositions.

Crime and the insecurities relating to it within urban neighborhoods are currently amongst the major concerns of urban citizens, and such issues have resulted in significant harm to their social life, to the point that urban neighborhoods are even sometimes considered to be a subcategory of urban abnormality. Such a result has arisen largely due to a lack of security in cities. The qualitative and quantitative aspects associated with the sense of security are crucial to the positive existence of urban neighborhoods, both from physical and social perspectives. A particularly important issue to consider is the safety of women and girls and the elderly in urban areas, especially at night. The goal of this study is to evaluate the role that the physical characteristics of an area playing in improving the security perceptions of urban citizens within that area. The approach of the study, given its descriptive-analytic nature, might be applied to all kinds of applied research. The study’s data collection is of two forms: library documents and survey-based questionnaires. In this research, a questionnaire was developed and distributed among residents of Zones Five and Ten of Shiraz, Iran. After collecting the required data, SPSS is used for the study’s analysis. The study adopts a simple random sampling method, with the statistical population of the study areas being 281,341. In turn, the sample size used via application of the Cochran formula is 384. The results of the T-test and the F-test are used to analyze the differences between the independent and dependent variables. The findings of the research reveal that the average security perception in Zone Ten is 41.51, an amount higher than that in Zone Five, which is 37.41. The observed difference between the averages of the Zones Five and Ten confirms the hypotheses of the research. The analysis shows that such factors of physical characteristics, including parks, buildings, schools, street lighting and roads network patterns, influence the quantity of potential criminals and thus the security perceptions. In general, there is a significant difference among the physical characteristics of the study areas in terms of their security perceptions.

Chinese officials tend to claim that Chinese economic and security activities in Africa are based on the principles of equality and mutual benefits (win-win), thus they are generally beneficial to the nation-building and development of African countries. Drawing on the case study of Ghana, this article argues that China’s commitment to enhancing the capacity of national security agencies, fighting against piracy, strengthening maritime security, and promoting intelligence sharing in West Africa have been, in general, constructive. However, anti-Chinese sentiments mainly triggered by the involvement of Chinese migrants in illegal gold mining activities in Ghana and other West African countries have been destructive, with serious security ramifications for not only Ghana, but also the entire region that has a history of violent conflicts closely related to extraction of natural resources.

Three major factors have made closer China-UK cooperation on African peace and security not only desirable but also feasible: expanding convergence of outlook and overlap of interests, the pan-African vision of peace and development as outlined in Agenda 2063, and the launch of a global comprehensive strategic partnership between Beijing and London. At the same time, the increasing securitization of Britain’s aid policy, Africans’ growing concern about unwarranted external intervention in continental affairs, and disparate development priorities may present significant challenges for closer trilateral coordination. The prospects of China-UK cooperation on African peace and security depend on whether Beijing and London can narrow differences, achieve policy alignment, and build a multilayered security cooperation mechanism. This article proposes three priorities where closer three-way coordination can contribute to African peace and security: a regularized China-UK-Africa peace dialogue, a development-centered approach to conflict prevention and response, and increased cooperation on nontraditional security risks.

The Northeast Asian security landscape is fast evolving amid intensifying China-U.S. strategic competition and a still raging coronavirus pandemic. Frequent summit meetings among regional leaders, including the historic meetings between Donald Trump and Kim Jong-un, have not translated into broader security dialogues and joint efforts to build a robust and durable regional security architecture. Divergent security perceptions, America’s dominant security role, and a mosaic pattern of regional security arrangements and mechanisms are the major factors shaping Northeast Asian security dynamics. Beijing remains committed to the declared path of peaceful development amid growing suspicion and concern over its strategic intention and capabilities; with strategic patience and perseverance, it is determined to play a larger role in forging consensus, building institutions, advancing cooperation, and coordinating relations in regional security matters.

In this article, the political–security relations between the United States and Pakistan in the Post-Cold War era are analyzed. The allied relationship between the two countries during the Cold War was abruptly disrupted following the conclusion of the Cold War in 1991 and the United States imposed a series of sanctions against Pakistan following the nuclear issue in 1990. However, the September 11 attacks of 2001 and the global anti-terrorism war launched by the G. W. Bush government resumed the relationship. Again, Pakistan became one of the principal allies of the United States and bilateral political–security relations were promoted unprecedentedly thanks to their collaboration against terrorism. The war against terrorism, however, has also produced many contradictions, which brought the relationship between the two countries into disputes and crises. This article discusses the U.S.–Pakistan relations in the Post-Cold War Era with special attention to the political–security aspects. Attempts will be made to clarify the nature, impacts and tendencies of the relationship. The U.S.–Pakistan relationship is a typical example of the international relationship between a superpower and a middle power, and it is also typical of the U.S.’s changing alliance relations.

Adverse climate change is more than an environmental concern. The are several consequential outcomes of climate change such as loss of oil wealth, depletion of scarce resources, decline in sources of livelihood, property loss, water shortages, and land scarcity. Secondary effects could include increased mortality, deteriorating health, hunger, poverty, inequality, and financial hardship. Studies over the years have shown that climate change could also precipitate conflicts and lead to displacements. For many women in conflict situations, it is difficult to access medical care, especially reproductive healthcare. Amid efforts to contain insecurity and its devastating effect, the government often loses sight of the vulnerabilities of women and girls, whose reproductive health challenges have been exacerbated by the effects of climate change. Men and women may encounter health challenges in climate change-induced conflict situations however, women may be affected more differently than men. Specific healthcare services, treatments, and commodities for women’s general and reproductive/sexual health are often ignored despite the need for healthcare, menstrual hygiene products, health education, and general health supplies in times of conflict. In addition to the associated conflict-related risk, women may face a heightened risk of rape and other sexual-related violence. The risk to women and girls may further increase if resources are diverted from sexual and reproductive health care to respond to the insecurity and crises or where the supply chain is affected by climate change-induced conflicts. This study examines the challenges that women face in climate change-induced conflict and post-conflict situations, particularly as it affects their reproductive health rights. It further argues that the realization that women’s reproductive and sexual health in a climate change-induced conflict setting is a human right that warrants concerted attention. Ultimately, it advocates for gender-sensitive responses to the reproductive and sexual health of women and girls as a matter of fundamental human right.

‘Asia’ is a big place. At the outset, therefore, it is important to emphasise that most of the discussion in what follows is preoccupied with East Asia, or the region we associate with China, Japan, the Korean peninsula, Taiwan and the countries that make-up the Association of Southeast Asian Nations (ASEAN). Even this relatively narrow conception of Asia contains a remarkably diverse group of states with every conceivable form of government, level of economic development and security challenge it is possible to imagine. As we shall see, though, other formulations of regional identity are possible and have potentially quite different implications for thinking about broadly conceived security issues. Not only are the protagonists different as regional definitions shrink or expand, but so, too, are the issue areas that preoccupy policymakers in different parts of the world. For example — and all its current problems notwithstanding — Western Europe remains far less concerned about conventional military security than East Asia does, where unresolved territorial claims have given a surprising and rather deflating immediacy to the sorts of security problems many thought were being erased by the pacifying influence of ‘globalisation’ (Gartzke 2007; Weissman 2012)…

This chapter provides overview of E-business, describes definition, types, and elements of E-business, explains challenges & issues of E-business, and points out emerging trends and future directions & opportunities of E-business.