Recent Trends in Deepfake Detection

2021 ◽  
pp. 1-28
Author(s):  
Kerenalli Sudarshana ◽  
Mylarareddy C.
Keyword(s):  
Human Life ◽  
Digital Content ◽  
The Internet ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Common Category ◽  
Internet Users ◽  
Multiple Dimensions ◽  
Learning Techniques ◽  
Recent Trends

Almost 59% of the world's population is on the internet, and in 2020, globally, there were more than 3.81 billion individual social network users. Eighty-six percent of the internet users were fooled to spread fake news. The advanced artificial intelligence (AI) algorithms can generate fake digital content that appears to be realistic. The generated content can deceive the users into believing it is real. These fabricated contents are termed deepfakes. The common category of deepfakes is video deepfakes. The deep learning techniques, such as auto-encoders and generative adversarial network (GAN), generate near realistic digital content. The content generated poses a serious threat to the multiple dimensions of human life and civil society. This chapter provides a comprehensive discussion on deepfake generation, detection techniques, deepfake generation tools, datasets, applications, and research trends.

scholarly journals Evolution of the Web: from Web 1.0 to 4.0

2021 ◽  
Vol 1 (3) ◽  
pp. 20-28
Author(s):  
Asaad Khaleel Ibrahim
Keyword(s):  
New Technologies ◽  
Interaction Network ◽  
Web Technology ◽  
The Internet ◽  
Human Machine Interaction ◽  
Web 3.0 ◽  
Internet Users ◽  
Multiple Dimensions ◽  
Machine Communication ◽  
New Generation

The internet has become a vital component of the twenty-first century as technology has advanced. The number of new technologies emerging in tandem with the qualities supplied by the Internet is rapidly increasing. The World Wide Web (WWW), which is commonly referred to as the world's largest information environment, is a vital virtual environment in which internet users may trade, read, and publish information using a Web browser. Web 1.0, Web 2.0, and Web 3.0 technologies have all been seen and are still being observed in this review paper. However, there is no clear definition for Web 4.0, which is a 4th generation web technology, in the literature. Web 4.0 has multiple dimensions, as seen by the first examples that have appeared. Big data, augmented reality, machine-to-machine communication (M2M), cloud computing, and artificial intelligence (AI) technologies, as well as smart agents, will be able to integrate in the future years. Web 4.0 is a web technology revolution that includes a new internet of things (IoT) that interacts with a variety of models. The goal of this study is to clarify the notion of Web 4.0, which is viewed as an intelligent and symbiotic (human-machine interaction) network with massive interfaces and linkages, as well as to contribute to the literature by studying its many dimensions and investigating its links with new generation technologies.

scholarly journals Network Attacks Detection Methods Based on Deep Learning Techniques: A Survey

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Yirui Wu ◽  
Dabao Wei ◽  
Jun Feng
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Attack Detection ◽  
Detection Methods ◽  
Generative Adversarial Network ◽  
Network Attacks ◽  
Adversarial Network ◽  
Fifth Generation ◽  
Learning Techniques ◽  
Benchmark Datasets

With the development of the fifth-generation networks and artificial intelligence technologies, new threats and challenges have emerged to wireless communication system, especially in cybersecurity. In this paper, we offer a review on attack detection methods involving strength of deep learning techniques. Specifically, we firstly summarize fundamental problems of network security and attack detection and introduce several successful related applications using deep learning structure. On the basis of categorization on deep learning methods, we pay special attention to attack detection methods built on different kinds of architectures, such as autoencoders, generative adversarial network, recurrent neural network, and convolutional neural network. Afterwards, we present some benchmark datasets with descriptions and compare the performance of representing approaches to show the current working state of attack detection methods with deep learning structures. Finally, we summarize this paper and discuss some ways to improve the performance of attack detection under thoughts of utilizing deep learning structures.

CULTURAL-PSYCHOLOGICAL ANALYSIS OF THE INFLUENCE OF EMOTIOGENIC PROPERTIES OF DIGITAL CONTENT ON ADOLESCENT USERS

Communicology ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 126-137
Author(s):  
ELENA VIKTOROVA ◽  
◽  
ELENA BADAEVA
Keyword(s):  
Social Interactions ◽  
Quantitative Research ◽  
Psychological Theory ◽  
Digital Content ◽  
The Internet ◽  
Digital Resources ◽  
Quantitative Research Methods ◽  
Psychological Analysis ◽  
Internet Users ◽  
Age Category

The paper is dedicated to the analysis of the emotiogenic properties of digital content as a factor in the occurrence of impressing impact on an individual on the Internet. Impressing is considered as a sociocultural phenomenon - its results are the formation of a person’s sustainable desire for a certain type of activity. This is especially relevant in adolescence: for Internet users of this age category Internet is the second reality, while surfing the Internet is not only a significant part of social interactions, but also the actualization of individual’s abilities. Based on the sociological and psychological theory of perception, the emotiogenic properties of digital resources are represented as primary and secondary. The ability of each of the types of these properties to determine the occurrence of impressing in adolescent users is revealed. The corresponding assessment of the digital resources demanded by users of the considered age category is given on the basis of empirical data obtained by qualitatively-quantitative research methods: focus group, content analysis, interviews.

Designing Computer Network Subnetting with School Objects Using Cisco Packet Tracer 6.1

2020 ◽  
Vol 8 (4) ◽  
pp. 445
Author(s):  
Desak putu Sekar merta Putri ◽  
I Komang Ari Mogi
Keyword(s):  
Computer Network ◽  
Human Life ◽  
The Internet ◽  
Physical Network ◽  
Internet Users ◽  
The World ◽  
Packet Tracer

The internet is one part that can not be released in human life today. Every year internet users both in Indonesia and in the world have increased. This increase in internet users causes the availability of IP to decrease. That is because users who will use the internet must have an IP. The availability of IPv4 is currently decreasing. To overcome these problems, IPv6 was made which was announced to replace the existence of IPv4. But another solution that can be taken is using subnetting. With subnetting, IP can be used optimally according to the needs of the host or can make efficient use of IP. And subnetting also functions to avoid congestion resulting from too many hosts on the physical network. And to connect between subnets, routing will be done.

scholarly journals Digital content as a fast Internet diffusion factor: Focusing on the fixed broadband Internet

2018 ◽  
Vol 36 (1) ◽  
pp. 97-111 ◽  
Author(s):  
Ho Seoung Na ◽  
Junseok Hwang ◽  
Hongbum Kim
Keyword(s):  
Digital Content ◽  
Mature Stage ◽  
The Internet ◽  
Internet Service ◽  
Broadband Internet ◽  
Diffusion Factor ◽  
Internet Users ◽  
Internet Diffusion ◽  
And Diffusion ◽  
Fast Internet

The Internet has significantly changed the lifestyles of individuals and many aspects of society while also having an important effect on economic growth and sustainable development. However, the usage and diffusion of the Internet vary greatly depending on the country, considering their economic and social conditions. This study investigates through an empirical analysis the factors that make Internet diffusion faster, especially focusing on the digital content. The results show that the abundance of digital content has played a crucial role in the rapid diffusion of the Internet. At the diffusion take-off stage, the number of Internet users appears to be the most important factor for fast Internet diffusion. However, as diffusion progresses to a mature stage, the amount of available digital content becomes the crucial factor for fast Internet diffusion. Thus, the countries in which the Internet is less diffused and the economy is less developed also require policies that promote various digital content from the launching of the Internet service to anticipate fast Internet diffusion in the whole diffusion progress.

scholarly journals Value orientations of vkontakte users with different strategies for meanings transferring

2021 ◽  
Vol 18 (4) ◽  
pp. 139-158
Author(s):  
Pavel N. Ermakov ◽  
Ekaterina E. Belousova
Keyword(s):  
Social Networks ◽  
Young People ◽  
Virtual Environment ◽  
Human Life ◽  
Value Orientations ◽  
The Internet ◽  
Work Processes ◽  
Internet Users ◽  
Terminal Values ◽  
Instrumental Values

The paper presents the results of a study of strategies for transferring the meanings and the value orientations of young people in social networks. The Internet is so firmly rooted in our everyday life that we can no longer imagine our life without it. It is penetrating into an increasing number of human life spheres, becoming the environment in which communication, educational and work processes, leisure and shopping take place. Its hard not to notice that the youth audience is especially interested in the virtual environment. The Internet and, in particular, social networks are becoming the environment that influences the formation and development of society, the dissemination of ideas, news, trends. On the Internet, one can observe both the amazing consolidation of users who are able to create a news agenda, and the disunity of many contradictory judgments, meanings and forms of their presentation. The purpose of this study is to identify the strategies for the translation of meanings that Internet users resort to when commenting on posts on social networks, and to study the value orientations of young people using various strategies for the translation of meanings. The study includes the authors questionnaire, the method of diagnosing M. Rokichs value orientations, methods of mathematical statistics (H-Kruskal-Wallis criterion, 22-criterion). Terminal and instrumental values characteristic of the 6 strategies of meanings transferring have been determined; the strategies most often used by users with abstract and concrete terminal values are revealed. The research helps to understand how the transferring of meanings takes place in a network and according to which characteristics of the value sphere users with different strategies for the meanings transferring differ.

scholarly journals Pengaruh Tehnologi Digital terhadap Motivasi Belajar Peserta Didik

PALAPA ◽  
2017 ◽  
Vol 5 (2) ◽  
pp. 53-77
Author(s):  
Muhasim Muhasim
Keyword(s):  
Digital Technology ◽  
Human Life ◽  
Rapid Development ◽  
Negative Influence ◽  
Positive Influence ◽  
The Internet ◽  
Rapid Progression ◽  
Human Communication ◽  
Internet Users ◽  
Technology Benefits

Perkembangan tehnologi digital merupakan hasil rekayasa akal, pikiran dan kecerdasan manusia, yang tercermin dalam kemajuan ilmu pengetahuan, selanjutnya memberikan manfaat dalam segala aspek kehidupan manusia. Dalam perkembangan komunikasi manusia telah berhasil membawa kemajuan yang sangat pesat. The development of digital technologies is the result of engineering intellect, mind and human intelligence, which is reflected in the advancement of science, and provides benefits in all aspects of human life. In the development of human communication has managed to bring a very rapid progression, from communication to manually change into analog, digital, where technology has provided ease in communicating quickly, without alimited distance, space and time through the Internet. Based on the data of Internet users in Indonesia 2016 as much as 132.7 million people from a total population of Indonesia as much as 256.2 million people, certainly the year 2017 is much more rapid development. From the results of a survey by the Association of organizers of Internet network , revealed that, on average, through the Internet in Indonesia 67.2 million or 50.7 percent, to access via mobile devices and the computer. In West NusaTenggara as many as 3.3 million or 64 percent. The number of internet users from 80 percent of who mareaged 15-19 years, meaning the teenage is still recorded as learners. Therefore the purpose of this paper is to find out how digital technology benefits against the motivation of learners. The method use disdescriptive qualitative studies. As the analysis of data and information furnished observations, document definitions obtained from books written by experts and scripts through social media or the Internet. Discussion of the results obtained positive influence motivation towards learning digital technology learners. With a fixed geared to anticipate the negative influence posed that can disrupt moral behavior, and thus a threat motivation learning learners. Because energy must begiven Faith, discipline on an ongoing basis, in order to take advantage of positive tehnology digital to enhance learning motivation of learners.

scholarly journals A Review on Secure Data Transmission for Banking Application using Machine Learning

2021 ◽  
Vol 10 (5) ◽  
pp. 182-186
Author(s):  
Gurram Bhaskar ◽  
Motati Dinesh Reddy ◽  
Thatikonda , Mounika
Keyword(s):  
Deep Learning ◽  
Information Transmission ◽  
Learning Strategy ◽  
The Internet ◽  
Energy Productivity ◽  
Generative Adversarial Network ◽  
Lightweight Framework ◽  
Adversarial Network ◽  
Secure Data Transmission ◽  
Financial Application

Security on the Internet of Things (IoT) accentuates safeguarding the Internet-empowered devices that connect to remote networks. IoT Safety endeavors to shield IoT gadgets and frameworks against cybercrime, and it is considered a vital security element linked to the IoT. Conversely, banking applications are dynamically being regulated for their inability to give an adequate level of client assistance and insure themselves against and react to digital assaults. One of the primary components for this is the weakness of Fintech systems and organizations to breaking down. Therefore, wireless organizations covering these IoT items are incredibly unprotected. IoT is a lightweight framework, and it is ideal when utilizing lightweight and energy-effective cryptography for assurance. Deep learning is a proficient technique to examine dangers and react to assaults and security occurrences. So this business locales both security and energy productivity in IoT utilizing two novel strategies helped out through the deep learning. This work adds to the most inventive method of saving energy in IoT gadgets through diminishing the utilization of energy-costly '1' values in the interface of Dynamic RAM. This should be possible by utilizing Base + XOR encoding of information during information transmission. Utilizing Conditional Generative Adversarial Network (CGAN) based deep learning strategy, the Base + XOR encoding technique and C.X.E. are prepared or trained quite well in the banking/financial application. The information age in CGAN is done dependent on rules delivered utilizing the generator model. This work is ended up being burning-through less energy, less information transmission time, and gives greater security when thought about the existing frameworks.

Multimodal News Feed Evaluation System with Deep Reinforcement Learning Approaches

2021 ◽  
Vol 20 (1) ◽  
pp. 1-12
Author(s):  
S. Rakesh Kumar ◽  
S. Muthuramalingam ◽  
Fadi Al-Turjman
Keyword(s):  
Deep Learning ◽  
Reinforcement Learning ◽  
Evaluation System ◽  
Language Models ◽  
Learning Approaches ◽  
Generative Adversarial Network ◽  
Vast Number ◽  
News Analysis ◽  
Adversarial Network ◽  
Learning Techniques

Multilingual and multimodal data analysis is the emerging news feed evaluation system. News feed analysis and evaluations are interrelated processes, which are useful in understanding the news factors. The news feed evaluation system can be implemented for single or multilingual language models. Classification techniques used on multilingual news analysis require deep layered learning techniques rather than conventional approaches. In this proposed work, a hierarchical structure of deep learning algorithms is implemented for making an effective complex news evaluation system. Deep learning techniques such as the Deep Cooperative Multilingual Reinforcement Learning Model, the Multidimensional Genetic Algorithm, and the Multilingual Generative Adversarial Network are developed to evaluate a vast number of news feeds. The proposed tech-niques collaborate in a pipeline order to build a deep news feed evaluation system. The implementation details project that the newly proposed system performs 5% to 12% better than the other news evaluation systems.

scholarly journals A Review on Malware Analysis by using an Approach of Machine Learning Techniques

IJOSTHE ◽  
2019 ◽  
Vol 3 (5) ◽  
pp. 5
Author(s):  
Aayushi Priya ◽  
Kajol Singh ◽  
Rajeev Tiwari
Keyword(s):  
Machine Learning ◽  
Malware Detection ◽  
Economic Benefits ◽  
Machine Learning Techniques ◽  
The Internet ◽  
Security Threats ◽  
Malware Analysis ◽  
Internet Age ◽  
Internet Users ◽  
Learning Techniques

In the Internet age, malware (such as viruses, trojans, ransomware, and bots) has posed serious andevolving security threats to Internet users. To protect legitimate users from these threats, anti-malware softwareproducts from different companies, including Comodo, Kaspersky, Kingsoft, and Symantec, provide the majordefense against malware. Unfortunately, driven by the economic benefits, the number of new malware sampleshas explosively increased: anti-malware vendors are now confronted with millions of potential malware samplesper year. In order to keep on combating the increase in malware samples, there is an urgent need to developintelligent methods for effective and efficient malware detection from the real and large daily sample collection.One of the most common approaches in literature is using machine learning techniques, to automatically learnmodels and patterns behind such complexity, and to develop technologies to keep pace with malware evolution.This survey aims at providing an overview on the way machine learning has been used so far in the context ofmalware analysis in Windows environments. This paper gives an survey on the features related to malware filesor documents and what machine learning techniques they employ (i.e., what algorithm is used to process the inputand produce the output). Different issues and challenges are also discussed.

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