Reviewerly/exHarmony huggingface dataset:
A study on data acquisition based on the Huawei smartphone backup protocol

Smartphones, which offer various features such as SMS/MMS, scheduling, messaging, and SNS, have become an integral part of modern life. Smartphones manage information intimately related to users in a self-contained manner, allowing them to provide such convenience efficiently. Such data, which can be used as key digital forensic evidence, are prime targets for investigators. However, exacting relevant data from smartphones with complicated structures requires considerable expertise. The analysis of smartphone backups is one approach to solving this problem. Smartphone manufacturers provide users with programs that include a backup protocol for backing up smartphone data. These programs allow investigators to easily extract smartphone data. Efficient smartphone data extraction is possible by integrating backup programs using different backup protocols into one framework. To achieve this integration, it is necessary to analyze each smartphone manufacturer's backup protocol. In this paper, we describe the results of analyzing the Huawei smartphone backup program HiSuite. HiSuite uses its backup protocol to produce backups of smartphones. We uncovered the entire process of the backup protocol through reverse engineering. We also experimentally verified that it is possible to obtain backup data from Huawei smartphones using the tool we developed to replace HiSuite based on our analysis. We believe this paper will help digital forensics investigators develop a better approaches to collecting data from smartphones.
Survey on Voice Assistance for Laptop

Voice control is a significant developing component that ease day to day life of humans. The voice assistance is generally being utilized in cell phones and workstations. Artificial Intelligence based Voice assistance are the working frameworks that can perceive human voice and react by means of coordinated voices. The voice assistance receives the sound from the receiver and further convert that into message, it passes to GTTS (Google text to speech). GTTS it’s main purpose is to converts text to an audio file and , the audio is further been played using play sound package.
Game-Based Proactive Learning with Augmented Reality(AR)

In this digital period in which we currently live, technology plays a vital role. With each passing day, new software or gadgets are being introduced in the tech market that improves our lives in one way or another and makes it much more comfortable. The mode of education was never the same, and it has changed continuously, today we have technology as our new mode of learning. Technology in education has the potential to drive pupils to learn more actively, resulting in a more effective learning process. Introducing enjoyable and interactive learning could capture the attention of young learners, hence improving teaching and learning. It improves one's ability to take in and grasp things. The application of Augmented Reality (AR) in the classroom has the potential to improve on traditional doctrine. This advanced technology enables users to interact with virtual environments and immerses them in realistic experiences. This application aims at teaching words by providing models of objects and tests the progress, resulting in a better learning experience for the user. This system increases the user’s degree of freedom by connecting with mobile devices because of the interface's usability, portability and general convenience.
Cyberbullying and Social Networking Sites

Media pay considerable attention to episodes that involve children and adolescents and the internet. Usually, the excessive time spent on social networking sites is highlighted as the principal source of risk for cyberbullying as well as for the various types of cyber addictions that can develop. Anonymity is reported to be one of the principal factors that favor cyberbullying, whilst sexting and homophobia are indicated as being among the principal circumstances that bring victims to commit suicide. In this chapter, some relevant aspects of the use of social networking sites will be illustrated and some notions regarding how the internet works will be introduced. Other questions, such as the spread of cyber hate and online incivility will be discussed, and a case of the incautious use of Facebook by a higher public education institution will be reported. Many concepts highlighted here will be useful in the following chapters in which strategies for the prevention of cyberbullying will be considered.
Research Journey of Hate Content Detection From Cyberspace

Hate content detection is the most prospective and challenging research area under the natural language processing domain. Hate speech abuse individuals or groups of people based on religion, caste, language, or sex. Enormous growth of digital media and cyberspace has encouraged researchers to work on hatred speech detection. A commonly acceptable automatic hate detection system is required to stop flowing hate-motivated data. Anonymous hate content is affecting the young generation and adults on social networking sites. Through numerous studies and review papers, the chapter identifies the need for artificial intelligence (AI) in hate speech research. The chapter explores the current state-of-the-art and prospects of AI in natural language processing (NLP) and machine learning algorithms. The chapter aims to identify the most successful methods or techniques for hate speech detection to date. Revolution in this research helps social media to provide a healthy environment for everyone.
The Spatial Leaky Competing Accumulator Model

The Leaky Competing Accumulator model (LCA) of Usher and McClelland is able to simulate the time course of perceptual decision making between an arbitrary number of stimuli. Reaction times, such as saccadic latencies, produce a typical distribution that is skewed toward longer latencies and accumulator models have shown excellent fit to these distributions. We propose a new implementation called the Spatial Leaky Competing Accumulator (SLCA), which can be used to predict the timing of subsequent fixation durations during a visual task. SLCA uses a pre-existing saliency map as input and represents accumulation neurons as a two-dimensional grid to generate predictions in visual space. The SLCA builds on several biologically motivated parameters: leakage, recurrent self-excitation, randomness and non-linearity, and we also test two implementations of lateral inhibition. A global lateral inhibition, as implemented in the original model of Usher and McClelland, is applied to all competing neurons, while a local implementation allows only inhibition of immediate neighbors. We trained and compared versions of the SLCA with both global and local lateral inhibition with use of a genetic algorithm, and compared their performance in simulating human fixation latency distribution in a foraging task. Although both implementations were able to produce a positively skewed latency distribution, only the local SLCA was able to match the human data distribution from the foraging task. Our model is discussed for its potential in models of salience and priority, and its benefits as compared to other models like the Leaky integrate and fire network.
The Case of Small Prime Numbers Versus the Joye–Libert Cryptosystem

In this paper, we study the effect of using small prime numbers within the Joye–Libert public key encryption scheme. We introduce two novel versions and prove their security. We further show how to choose the system’s parameters such that the security results hold. Moreover, we provide a practical comparison between the cryptographic algorithms we introduced and the original Joye–Libert cryptosystem.
Poppy Gustafsson: redefining cybersecurity through AI

Study level/applicability This case is meant for MBA students as a part of their leadership/information technology and system curriculum. It is suitable for classes in both offline and online mode. Subject area Human resources management/information technology and systems. Case overview The case discusses how Poppy Gustafsson (Gustafsson) (she), Cofounder and Chief Executive Officer of Darktrace plc, one of the world’s largest cyber-AI companies, is reinventing enterprise security by using artificial intelligence (AI) to detect and respond to cyberthreats to businesses and protect the public. Darktrace’s technology leverages the principles of the human immune system to autonomously defend organizations from cyberattacks, insider threats and AI warfare. In addition to leading a cutting-edge cybersecurity company, Gustafsson evangelizes gender diversity at Darktrace where 40% of employees and four C-level executives are women, a number nearly unheard of in the tech sector.The case chronicles the journey of Gustafsson and how she led the company to growth and success. Under her leadership, Darktrace has grown into a market leader in the AI cybersecurity space serving 5,600 customers in 100 countries, as of June 2021. Gustafsson not only redefined the cybersecurity space but also inspired women to pursue a career in the field of cybersecurity. She also collaborated with a social enterprise called WISE to encourage more girls to consider STEM careers.However, along the way, she faced several challenges including growing competition, procuring funds from investors, cybersecurity talent shortage and training personnel. Going forward, some of the challenges before Gustafsson would be to meet the changing cyber protection demands of customers; hire, train and retain highly skilled cybersecurity personnel; beat the competition in a saturated cybersecurity services space; sustain revenue growth; and post profits as Darktrace had incurred losses every year since its inception. Expected learning outcomes This case is designed to enable students to: understand the issues and challenges women face in the field of cybersecurity; understand the qualities required for a woman leader to lead a technology firm; study the leadership and management style of Gustafsson; understand the importance of transformational leadership in management; understand the role of Gustafsson in Darktrace’s growth and success; analyze the traits that Gustafsson possesses as a tech leader in an emerging cybersecurity space; understand the importance of gender diversity in cybersecurity; and analyze the challenges faced by Gustafsson going forward and explore ways in which she can overcome them. Subject code CSS: 11 Strategy.
Setting Anti-Cyberbullying Legal Policies

It is a broadly shared opinion that establishing the illegitimacy of cyberbullying is a primary action in combating it. In this regard, schools should openly declare that cyberbullying is not an acceptable or admissible behavior, and firm rules regarding this phenomenon should be implemented by them. In this chapter, the problem of setting anti-cyberbullying legal policies will be addressed. Two cases are illustrated and discussed, the famous case of Lori Drew related to the suicide of Megan Meier that occurred in 2006, and the Italian case of Tiziana Cantone whose suicide occurred 10 years later. In fact, the latter was not a cyberbullying case, but it is remarkable since it generated a huge emotional reaction among Italian people that ultimately led to the implementation of the Italian law against cyberbullying in 2017 and, in 2019, brought about the law against the unsolicited sharing of compromising erotic pictures or video, known as revenge porn. Both cases illustrate the issues that may arise in drawing effective anti-cyberbullying laws. The absence of a univocal definition of cyberbullying and the pressure of public opinion negatively affects the establishment of appropriate legal policies. Indeed, the formulation of a law implies unequivocally identifying an infraction and having clear rules to punish it. The current legal situation of cyberbullying in different countries is highlighted, focusing on the USA and Europe, and the general questions regarding the criminalization and punishment of cyberbullying are also analyzed. Finally, the use and positive influence of anti-cyberbullying regulations at schools are reviewed and discussed.
EDUCATION PROBLEMS IN CHALLENGES ON ELABORATION OF FUNDAMENTAL EDUCATION PHILOSOPHY CONCEPTS

The article is devoted to the analysis of existing conceptual approaches and alternative attitudes to resolving the education problems. The work considers contradictions of worldview ideas and philosophical-ontological and axiological viewpoints of creators of education philosophy concepts, as well as the contradictions of worldview ideas in understanding the essence of philosophical and pedagogical anthropology. The work presents the analysis of the basic concepts of pedagogy and philosophy of education in the post-Soviet space. The goal of the article is to analyze and clarify philosophical conceptual approaches to the creation of new pedagogical methods of teaching and upbringing, focused both on the younger generation and on adults. Difficulties in creating such methods are caused by the existing disagreements in the formation of fundamental concepts of education philosophy, as well as the lack of common conceptual attitudes, as a result of which, in every case, teachers have to form their own personal approaches to education and training challenges. The work proposes a revised model of the "philosophical and pedagogical pyramid". The author proposes to pay special attention to andragogy and ethnic resource of pedagogy, oriented on the upbringing of youth and adults, taking into account the ethnicity of an individual, when creating concepts of education philosophy. In author’s opinion, in order to create new educational technologies, it is advisable to identify and restore the lost pedagogical methods of education from the origins of people’s genetic and ethnic memory. The conclusion gives a number of findings revealing the problems of education philosophy and essence of upbringing methods, as well as the author's conceptual assessment of the approaches to creating pedagogical technologies of upbringing and training.
The Potential of Gaming to Ameliorate Human Factors in Information Security Compliance

In this chapter, the author discusses the need for appropriate training to improve information security compliance and some of the human factors that lead to non-compliance. Following is a section on theories that attempt to model and predict compliance. The author discusses the use of serious games, games-based learning, and gamification as educational tools, and their strengths in providing some of the major training needs, including emotional engagement, intrinsic motivation, repetition, discussion, reflection, and self-efficacy. This is followed by a list of some prominent games and gamification tools in the field of information security. Finally, the author concludes with guidelines and considerations for information security professionals who may be considering the use of serious games and gamification to enhance their information security awareness training.
Communication mechanism of Internet of Things based on blockchain

Aiming at solving the security problems of data confidentiality and integrity in the traditional centralized Internet of things communication, data leakage and tampering caused by malicious users abusing communication functions in the Internet of things system, a data communication mechanism of Internet of things based on blockchain is proposed. Combined with the characteristics of blockchain, such as decentralization, immutability and auditability, the data exchange mechanism of Internet of things communication tunnel is proposed. Preventing malicious communication through communication tunnel management and control of data exchange between devices, and ensures data integrity in combination with digital signature technology. The security analysis shows that the mechanism has good security characteristics and meets the security requirements of Internet of things communication. Experiments on Ethereum show that compared with existing studies, this mechanism has less time overhead, indicating the feasibility and availability of this mechanism.
Using the NIST Framework and COBIT 2019 in Offering Cybersecurity Consulting and Assurance Services

Information processing in a cyber environment offers tremendous benefits but is also accompanied by inevitable dangers including compromised confidentiality and malware such as ransomware that can shut down major segments of a country's operations. A variety of forms of guidance and regulation have been developed to deal with these cybersecurity issues. The professions of public accounting and internal audit have long worked with organizations to protect the integrity of their information systems. Both of these professions are working diligently to guide organization management in the area of cybersecurity. An important aspect of such services is an appropriate framework to use as a basis for advisement and assurance. One such framework is the Framework for Improving Critical Infrastructure Cybersecurity issued by the National Institute of Standards and Technology.
Online task assignment for federated learning in smart city

The advent of Internet of Things and widespread mobile devices in urban cities have motivated a new paradigm emergence that is smart city. Data acquired from ubiquitous devices can be used to train the Artificial Intelligence(AI) models that support the smart services and benefit society in all aspects. Federated learning (FL) as a distributed learning technology enables multiple edge nodes collaboratively train a global model with remaining their raw data in local, which protects data privacy. Previous efforts mostly focus on offline FL task assignment where datasets are offline, i.e., continuously training the model with the same datasets. Actually, there is always new data produced during training process and these new data should be added to training datasets as an update for improving the performance of the model and online datasets scenario is more realistic. Based on Lyapunov optimization theory, we constructe a dynamic queue model to formalize the online dataset of each edge node. To effectively assign the model to the edge nodes, an online task assignment algorithm that is Federated Online Control Algorithm (FedOCA) is proposed. Through empirical analysis, we found that our proposed algorithm can achieve higher accuracy compared to Fedavg on the FashionMNIST dataset. We also verify the effect of batch size on accuracy, and find that the larger batch has worse effect.
Relevant Word Determination from Dynamic Text Network

Text network has been of research interest in the computational domain. A text network contains textual documents with dynamic content. The textual documents linguistically depend upon the grammar and use of words. We have proposed determining relevant words in dynamic content using dynamic complex network approaches. We considered dynamic news updates for exploring our analysis of text networks. This work proposes a complex network-based approach for determining the change of important words with dynamic content. We have suggested determining relevant words from dynamic content using degree centrality, closeness centrality and clustering coefficient. We have proposed Affiliation Factor for bond strength determination among the important words. We have considered an instance of live updates in the news for our approach. The news updates on a particular live incident are uploaded dynamically in a thread. We have introduced the Instance Factor for perceiving the relevance of the important words throughout the document, apart from considering the co-occurrence frequency. The approach is free of semantic analysis and, consequently, exempt depending on any corpus. The analytical results show that the varying important words can be efficiently determined from the dynamic content of the text network compared to the other approaches.
The Simulation and Design of Zero-Energy Homes—A Comparison between Photo-Voltaic, Solar-Thermal, and Photo-Voltaic-Thermal Systems

The domestic sector is the leading energy consumer in Pakistan. Due to an increase in population, urbanization, and economic development, energy demand is increasing day by day. To meet this energy demand, net-zero energy buildings provide the optimal solution. In zero energy buildings, energy demand is met by renewable energy sources, such as solar energy. This study describes techniques of home design using simulation, and energy conservation is achieved by using proper construction techniques and insulation materials in building construction. In this study, the actual climate data of different climate zones in Pakistan is being used to design zero-energy homes. The results show that there is a remarkable difference between the energy demand of standard homes and homes proposed by the simulator used. The total energy performance index of a house decreased from 94.6% to 67.6%. The comparative simulation analysis of different solar energy system solutions such as solar thermal, photo-voltaic, and hybrid photo-voltaic-thermal modules for different climate zones in Pakistan, is presented in this paper. This study also describes the best combination of solar energy systems to reach a close-to-zero energy balance and the results depend on the building design and design of building energy systems. A cost analysis based on the rate of return on investment is also presented to motivate the usage of this method.
Cybercitizens at Schools

In recent decades, cyberethics, cybersecurity, and cybersafety have been the center of interest at schools. This chapter uses a case study approach to describe the issue of cyberethics, cybersafety, and cybersecurity (3Cs) as well as how problems of these three Cs are intermingled to become general cyberethics issues for the society. The chapter also promotes good cybercitizens at schools because it is of great importance for the school districts to take some measures to improve students' knowledge and awareness of cyberethics, cybersafety, and cybersecurity, to enhance the safety and security of school infrastructure, to avoid cyberbullying, to ensure students are good cybercitizens, and to help train teachers to be cyber professionals.
Cybercrime Research

Technological advancements have transformed the way people go about their daily lives. However, this development is not without unintended consequences, as cyber-criminals have also devised ways to gain leverage. The authors conducted a literature review on 106 articles across 40 journals to bring to fore cybercrime studies that have been conducted according to the research themes, methodological approaches, level of analysis, geographical focus, and publication outlets. Themes identified in the review were categorized under an existing typology of cybercrime: cyber-trespass, cyber-deception/theft, cyber-pornography and obscenity, and cyber-violence. This review suggested two main directions for future research in terms of socio-technical and theoretical approaches with five research questions. The originality of this review stems from the fact that it is arguably one of the first reviews that have reviewed cybercrime from a holistic perspective.
A Decoding Algorithm for Convolutional Codes

It is shown how the decoding algorithms of Pellikaan and Rosenthal can be coupled to produce a decoding algorithm for convolutional codes. Bounds for the computational cost per decoded codeword are also computed. As a case study, our results are applied to a family of convolutional codes constructed by Rosenthal–Schumacher–York and, in this situation, the previous bounds turn out to be polynomial on the degree of the code.