Deepfakes are synthetic media that uses artificial intelligence to realistically manipulate images and videos by replacing a person's face with another. The term is a combination of "deep learning" and "fake". While deepfake technology was initially developed for entertainment purposes like special effects, it can also be used to impersonate people, create realistic simulations for training, and generate fake content for social media. However, there are disadvantages like using deepfakes for blackmail, spreading misinformation, and lack of authenticity which is why regulation of this technology is important.
Deepfakes - How they work and what it means for the futureJarrod Overson
Deepfakes originally started as cheap costing but believable video effects and have expanded into AI-generated content of every format. This session dove into the state of deepfakes and how the technology highlights an exciting but dangerous future.
Although manipulations of visual and auditory media are as old as the media themselves, the recent entrance of deepfakes has marked a turning point in the creation of fake content. Powered by latest technological advances in AI and machine learning, they offer automated procedures to create fake content that is harder and harder to detect to human observers. The possibilities to deceive are endless, including manipulated pictures, videos and audio, that will have large societal impact. Because of this, organizations need to understand the inner workings of the underlying techniques, as well as their strengths and limitations. This article provides a working definition of deepfakes together with an overview of the underlying technology. We classify different deepfake types: photo (face- and body-swapping), audio (voice-swapping, text to speech), video (face-swapping, face-morphing, full body puppetry) and audio & video (lip-synching), and identify risks and opportunities to help organizations think about the future of deepfakes. Finally, we propose the R.E.A.L. framework to manage deepfake risks: Record original content to assure deniability, Expose deepfakes early, Advocate for legal protection and Leverage trust to counter credulity. Following these principles, we hope that our society can be more prepared to counter the deepfake tricks as we appreciate its treats.
DeepFake Detection: Challenges, Progress and Hands-on Demonstration of Techno...Symeon Papadopoulos
Slides accompanying an online webinar on DeepFake Detection and a hands-on demonstration of the MeVer DeepFake Detection service. The webinar is supported by the US-Paris Tech Challenge award for our work on the InVID-WeVerify plugin.
Deepfakes - How they work and what it means for the futureJarrod Overson
Deepfakes originally started as cheap costing but believable video effects and have expanded into AI-generated content of every format. This session dove into the state of deepfakes and how the technology highlights an exciting but dangerous future.
Although manipulations of visual and auditory media are as old as the media themselves, the recent entrance of deepfakes has marked a turning point in the creation of fake content. Powered by latest technological advances in AI and machine learning, they offer automated procedures to create fake content that is harder and harder to detect to human observers. The possibilities to deceive are endless, including manipulated pictures, videos and audio, that will have large societal impact. Because of this, organizations need to understand the inner workings of the underlying techniques, as well as their strengths and limitations. This article provides a working definition of deepfakes together with an overview of the underlying technology. We classify different deepfake types: photo (face- and body-swapping), audio (voice-swapping, text to speech), video (face-swapping, face-morphing, full body puppetry) and audio & video (lip-synching), and identify risks and opportunities to help organizations think about the future of deepfakes. Finally, we propose the R.E.A.L. framework to manage deepfake risks: Record original content to assure deniability, Expose deepfakes early, Advocate for legal protection and Leverage trust to counter credulity. Following these principles, we hope that our society can be more prepared to counter the deepfake tricks as we appreciate its treats.
DeepFake Detection: Challenges, Progress and Hands-on Demonstration of Techno...Symeon Papadopoulos
Slides accompanying an online webinar on DeepFake Detection and a hands-on demonstration of the MeVer DeepFake Detection service. The webinar is supported by the US-Paris Tech Challenge award for our work on the InVID-WeVerify plugin.
The Rise of Deep Fake Technology: A Comprehensive Guidefindeverything
In this guide, we go through into the emergence of deep fake technology, an innovative artificial intelligence (AI) technique that utilizes complex deep learning algorithms to fabricate manipulated videos or images with a realistic appearance. While this cutting-edge technology has the potential to revolution the entertainment and marketing industries, it also poses a significant threat to national security, individual privacy, and the truth of information. Our comprehensive analysis explores the difficulties of deep fake technology, its diverse applications, the potential benefits and drawbacks, and its profound impact on various industries.
Deepfakes are a form of synthetic media that use artificial intelligence and machine learning algorithms to create fake images, videos, or audio recordings that appear to be real. They are created by manipulating or combining existing content to produce a realistic result.
The "Big Data Analytics and its Use by Apple" presentation provides an overview of how Apple harnesses big data analytics to gain insights, drive innovation, and enhance business performance. It explores Apple's strategic use of data analytics in areas such as product development, customer experience, and operational efficiency, showcasing the value of data-driven decision-making in one of the world's leading technology companies.
The “deepfake” phenomenon — using machine learning to generate synthetic video, audio and text content — is an ominous example of how quickly new technologies can be diverted from their original purposes. Month by month, it is becoming easier and cheaper to create fakes that are increasingly difficult to distinguish from genuine artefacts.
Deepfakes: An Emerging Internet Threat and their DetectionSymeon Papadopoulos
Webinar talk in the context of the AI4EU Web Cafe. Recording of the talk available on: https://youtu.be/wY1rvseH1C8
Deepfakes have emerged for some time now as one of the largest Internet threats, and even though their primary use so far has been the creation of pornographic content, the risk of them being abused for disinformation purposes is growing by the day. Deepfake creation approaches and tools are continuously improving in terms of result quality and ease of use by non-experts, and accordingly the amount of deepfake content on the Internet is quickly growing. For that reason, approaches for deepfake detection are a valuable tool for media companies, social media platforms and ultimately citizens to help them tell authentic from deepfake generated content. In this presentation, I will be presenting a short overview of the developments in the field of deepfake detection, and present our lessons learned from working on the problem in the context of the Deepfake Detection Challenge and from developing a service for the H2020 WeVerify project.
This is a presentation for Brandeis International Business School's Big Data II course about newer technologies using artificial intelligence, mainly the recently trendy Deepfake.
deepfake
seminar
computer engineering
ppt on deepfake which uses ai and deep learning technology.with adavantages,disadvantages,intro,reference,conclusion
SSII2021 [SS2] Deepfake Generation and Detection – An Overview （ディープフェイクの生成と検出）SSII
SSII2021 [SS2] Deepfake Generation and Detection – An Overview （ディープフェイクの生成と検出）
6/10 (木) 14:30～15:00
講師：Huy H. Nguyen 氏（総合研究大学院大学／国立情報学研究所）
概要： Advances in machine learning and their interference with computer graphics allow us to easily generate high-quality images and videos. State-of-the-art manipulation methods enable the real-time manipulation of videos obtained from social networks. It is also possible to generate videos from a single portrait image. By combining these methods with speech synthesis, attackers can create a realistic video of some person saying something that they never said and distribute it on the internet. This results in loosing social trust, making confusion, and harming people’s reputation. Several countermeasures have been proposed to tackle this problem, from using hand-crafted features to using convolutional neural network. Some countermeasures use images as input and other leverage temporal information in videos. Their output could be binary (bona fide or fake) or muti-class (deepfake detection), or segmentation masks (manipulation localization). Since deepfake methods evolve rapidly, dealing with unseen ones is still a challenging problem. Some solutions have been proposed, however, this problem is not completely solved. In this talk, I will provide an overview on both deepfake generation and deepfake detection/localization. I will mainly focus on image and video domain and also introduce some audiovisual-based methods on both sides. Some open discussions and future directions are also included.
Dissecting the dangers of deepfakes and their impact on reputation Generative...CSIRO National AI Centre
At the recent Generative AI Conference - This talk defined deepfakes and the widespread damage misinformation can cause. In order to build awareness of the ethical implications of deepfakes. At the
National AI Centre, Responsible AI and Responsible AI Network
allows us to action a way to use AI that is aligned to Australia's AI ethics principles.
9 Examples of Artificial Intelligence in Use TodayIQVIS
Artificial Intelligence (AI) is the branch of computer sciences that emphasizes the development of intelligence machines, thinking and working like humans.
Industry analysts argue that artificial intelligence is the future – but if we look around, we are convinced that it’s not the future – it is the present. The given examples will explain the true meaning and context.
Read as a blog post here. http://www.iqvis.com/blog/9-powerful-examples-of-artificial-intelligence-in-use-today/
DEEPFAKE DETECTION TECHNIQUES: A REVIEWvivatechijri
Noteworthy advancements in the field of deep learning have led to the rise of highly realistic AI generated fake videos, these videos are commonly known as Deepfakes. They refer to manipulated videos, that are generated by sophisticated AI, that yield formed videos and tones that seem to be original. Although this technology has numerous beneficial applications, there are also significant concerns about the disadvantages of the same. So there is a need to develop a system that would detect and mitigate the negative impact of these AI generated videos on society. The videos that get transferred through social media are of low quality, so the detection of such videos becomes difficult. Many researchers in the past have done analysis on Deepfake detection which were based on Machine Learning, Support Vector Machine and Deep Learning based techniques such as Convolution Neural Network with or without LSTM .This paper analyses various techniques that are used by several researchers to detect Deepfake videos.
Avvkskeve vsjsoneceyeu scgsuieks na scec snsjscsyisbs svegsijsceiebe svsjskndcdidken scegsjjebececgdcr. E ejdidnrceyjevr evhejevr .uwjegejiej.eveibe e e.ejevhej.
Deepfakes refer to synthetic media created using advanced AI and ML techniques. What are its potential applications and implications for society at large?
What is Deepfake AI? How it works and How Dangerous Are They?janviverma11
It combines "deep learning" and "fake" to describe both the technology and the misleading content it produces. Deepfake can replace one person with another in existing content or generate entirely new content where people seem to do or say things they never did. The most significant risk of deep fakes lies in their potential to spread false information that seems true.
The Rise of Deep Fake Technology: A Comprehensive Guidefindeverything
In this guide, we go through into the emergence of deep fake technology, an innovative artificial intelligence (AI) technique that utilizes complex deep learning algorithms to fabricate manipulated videos or images with a realistic appearance. While this cutting-edge technology has the potential to revolution the entertainment and marketing industries, it also poses a significant threat to national security, individual privacy, and the truth of information. Our comprehensive analysis explores the difficulties of deep fake technology, its diverse applications, the potential benefits and drawbacks, and its profound impact on various industries.
Deepfakes are a form of synthetic media that use artificial intelligence and machine learning algorithms to create fake images, videos, or audio recordings that appear to be real. They are created by manipulating or combining existing content to produce a realistic result.
The "Big Data Analytics and its Use by Apple" presentation provides an overview of how Apple harnesses big data analytics to gain insights, drive innovation, and enhance business performance. It explores Apple's strategic use of data analytics in areas such as product development, customer experience, and operational efficiency, showcasing the value of data-driven decision-making in one of the world's leading technology companies.
The “deepfake” phenomenon — using machine learning to generate synthetic video, audio and text content — is an ominous example of how quickly new technologies can be diverted from their original purposes. Month by month, it is becoming easier and cheaper to create fakes that are increasingly difficult to distinguish from genuine artefacts.
Deepfakes: An Emerging Internet Threat and their DetectionSymeon Papadopoulos
Webinar talk in the context of the AI4EU Web Cafe. Recording of the talk available on: https://youtu.be/wY1rvseH1C8
Deepfakes have emerged for some time now as one of the largest Internet threats, and even though their primary use so far has been the creation of pornographic content, the risk of them being abused for disinformation purposes is growing by the day. Deepfake creation approaches and tools are continuously improving in terms of result quality and ease of use by non-experts, and accordingly the amount of deepfake content on the Internet is quickly growing. For that reason, approaches for deepfake detection are a valuable tool for media companies, social media platforms and ultimately citizens to help them tell authentic from deepfake generated content. In this presentation, I will be presenting a short overview of the developments in the field of deepfake detection, and present our lessons learned from working on the problem in the context of the Deepfake Detection Challenge and from developing a service for the H2020 WeVerify project.
This is a presentation for Brandeis International Business School's Big Data II course about newer technologies using artificial intelligence, mainly the recently trendy Deepfake.
deepfake
seminar
computer engineering
ppt on deepfake which uses ai and deep learning technology.with adavantages,disadvantages,intro,reference,conclusion
SSII2021 [SS2] Deepfake Generation and Detection – An Overview （ディープフェイクの生成と検出）SSII
SSII2021 [SS2] Deepfake Generation and Detection – An Overview （ディープフェイクの生成と検出）
6/10 (木) 14:30～15:00
講師：Huy H. Nguyen 氏（総合研究大学院大学／国立情報学研究所）
概要： Advances in machine learning and their interference with computer graphics allow us to easily generate high-quality images and videos. State-of-the-art manipulation methods enable the real-time manipulation of videos obtained from social networks. It is also possible to generate videos from a single portrait image. By combining these methods with speech synthesis, attackers can create a realistic video of some person saying something that they never said and distribute it on the internet. This results in loosing social trust, making confusion, and harming people’s reputation. Several countermeasures have been proposed to tackle this problem, from using hand-crafted features to using convolutional neural network. Some countermeasures use images as input and other leverage temporal information in videos. Their output could be binary (bona fide or fake) or muti-class (deepfake detection), or segmentation masks (manipulation localization). Since deepfake methods evolve rapidly, dealing with unseen ones is still a challenging problem. Some solutions have been proposed, however, this problem is not completely solved. In this talk, I will provide an overview on both deepfake generation and deepfake detection/localization. I will mainly focus on image and video domain and also introduce some audiovisual-based methods on both sides. Some open discussions and future directions are also included.
Dissecting the dangers of deepfakes and their impact on reputation Generative...CSIRO National AI Centre
At the recent Generative AI Conference - This talk defined deepfakes and the widespread damage misinformation can cause. In order to build awareness of the ethical implications of deepfakes. At the
National AI Centre, Responsible AI and Responsible AI Network
allows us to action a way to use AI that is aligned to Australia's AI ethics principles.
9 Examples of Artificial Intelligence in Use TodayIQVIS
Artificial Intelligence (AI) is the branch of computer sciences that emphasizes the development of intelligence machines, thinking and working like humans.
Industry analysts argue that artificial intelligence is the future – but if we look around, we are convinced that it’s not the future – it is the present. The given examples will explain the true meaning and context.
Read as a blog post here. http://www.iqvis.com/blog/9-powerful-examples-of-artificial-intelligence-in-use-today/
DEEPFAKE DETECTION TECHNIQUES: A REVIEWvivatechijri
Noteworthy advancements in the field of deep learning have led to the rise of highly realistic AI generated fake videos, these videos are commonly known as Deepfakes. They refer to manipulated videos, that are generated by sophisticated AI, that yield formed videos and tones that seem to be original. Although this technology has numerous beneficial applications, there are also significant concerns about the disadvantages of the same. So there is a need to develop a system that would detect and mitigate the negative impact of these AI generated videos on society. The videos that get transferred through social media are of low quality, so the detection of such videos becomes difficult. Many researchers in the past have done analysis on Deepfake detection which were based on Machine Learning, Support Vector Machine and Deep Learning based techniques such as Convolution Neural Network with or without LSTM .This paper analyses various techniques that are used by several researchers to detect Deepfake videos.
Avvkskeve vsjsoneceyeu scgsuieks na scec snsjscsyisbs svegsijsceiebe svsjskndcdidken scegsjjebececgdcr. E ejdidnrceyjevr evhejevr .uwjegejiej.eveibe e e.ejevhej.
Deepfakes refer to synthetic media created using advanced AI and ML techniques. What are its potential applications and implications for society at large?
What is Deepfake AI? How it works and How Dangerous Are They?janviverma11
It combines "deep learning" and "fake" to describe both the technology and the misleading content it produces. Deepfake can replace one person with another in existing content or generate entirely new content where people seem to do or say things they never did. The most significant risk of deep fakes lies in their potential to spread false information that seems true.
Deepfakes Manipulating Reality with AI.pdfIMRAN SIDDIQ
Blogging has been a passion of mine for quite some time. I find immense joy in creating engaging content that informs, entertains, and inspires my readers. Through my blog, I aim to explore various topics related to AI, curative technologies, and their impact on our lives.
Artificial intelligence has emerged as a transformative force in today's world. It has the potential to revolutionize industries, enhance our daily lives, and solve complex problems. As an AI enthusiast, I'm constantly exploring the latest advancements, applications, and ethical considerations surrounding this field. I believe in the power of AI to drive positive change and create a better future for all.
Additionally, my curiosity extends to curative technologies, which focus on finding innovative solutions to diseases and health-related challenges. I'm fascinated by the advancements in medical research, genomics, and personalized medicine, and I strive to stay up-to-date with the latest breakthroughs. Through my blog, I aim to demystify complex medical concepts and present them in an accessible manner for my readers.
By combining my passion for blogging, AI, and curative technologies, I aim to provide valuable insights, thought-provoking discussions, and practical information to my readers. I hope to contribute to the growing dialogue surrounding these topics and create a community where like-minded individuals can engage, learn, and exchange ideas.
Join me on this exciting journey as we explore the wonders of artificial intelligence, delve into the realm of curative technologies, and uncover the potential they hold for shaping our future. Together, let's embark on a quest to understand and harness the power of these transformative fields.
Thank you for visiting my blog, and I look forward to sharing knowledge and inspiration with you!
A survey of deepfakes in terms of deep learning and multimedia forensicsIJECEIAES
Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfake detection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection of deepfakes, and iii) finally how in the future incorporating both deep learning technology and tools for forensics can increase the efficiency of deepfakes detection.
Deepfake Videos on the Rise: Examining the Alarming ConcernsbluetroyvictorVinay
In the rapidly evolving landscape of digital content, the surge in deepfake videos has emerged as a significant cause for concern. As this technological phenomenon continues to gain momentum, it’s crucial to delve into the alarming concerns surrounding deepfake videos and their potential implications.
Deepfake AI has emerged as an enthralling and troubling topic in this age of rapid technological advancement. Deepfake AI, short for "deep learning fake artificial intelligence," is a powerful tool that manipulates and generates incredibly realistic video, audio, and textual content using artificial intelligence. This technology has far-reaching societal implications, from entertainment to politics and beyond. The purpose of this article is to provide a comprehensive and simplified understanding of deepfake AI, its implications, and potential safeguards.
1: What Is Deepfake AI?
1.1 Definition and Origins of Deepfake AI
Deepfake AI is a combination of "deep learning" and "fake," referring to AI's ability to create highly convincing fake content. Deep neural networks, which are complex mathematical models that learn from large datasets to mimic human-like behaviors, are used.
1.2 How Does Deepfake AI Work?
#image_title
Deepfake AI works in two stages:
Data Collection: It collects massive amounts of data on the target person, including images, videos, and audio recordings.
Model Training: The AI uses this data to train itself to produce realistic content by mimicking the person's mannerisms, expressions, and voice.
1.3 The Science Behind Deepfake AI
AI models, particularly deep neural networks, are used to create deepfakes. These networks learn the nuances of a person's speech patterns, facial expressions, and mannerisms by analyzing massive datasets of images and audio recordings. This knowledge serves as the foundation for creating realistic imitations.
2: Implications of Deepfake AI
2.1 Misinformation and Disinformation
Deepfake AI has the capability of disseminating false information and manipulating public perception. Deepfakes can be used by malicious actors to impersonate individuals and create fake news, jeopardizing trust in media and information sources.
2.2 Privacy Concerns
Deepfakes raise serious privacy concerns because personal data can be used to create fabricated content. Individuals' privacy may be jeopardized when their faces and voices are used without their permission.
2.3 Political Manipulation
Deepfake AI can be used to target political figures. These tampered with videos and audio recordings can be used to fabricate evidence, sway elections, and tarnish reputations.
2.4 Identity Theft
Deepfakes can be used to steal people's identities, causing significant harm. Criminals may use realistic deepfake content to create fake profiles, steal identities, or commit fraud.
3: Detecting Deepfake AI
3.1 Facial and Vocal Anomalies
Examining facial and vocal cues is frequently used to detect deepfakes. Unusual movements, blinking patterns, and inconsistent lip-syncing are red flags.
3.2 Metadata Analysis
Deepfake AI can sometimes leave digital traces in media metadata. Analyzing metadata for inconsistencies can aid in the detection of manipulated content.
3.3 AI Algorithms Development for Deepfake AI
1 www.mediaethicsinitiative.org How Deep Does the .docxjeremylockett77
1 | www.mediaethicsinitiative.org
How Deep Does the Virtual Rabbit Hole Go?
“Deepfakes” and the Ethics of Faked Video Content
Photo: Geralt / CC0
The Internet has a way of both refining techniques and technologies by pushing them to their
limits—and of bending them toward less-altruistic uses. For instance, artificial intelligence
is increasingly being used to push the boundaries of what appears to be reality in faked
videos. The premise of the phenomenon is straightforward: use artificial intelligence to
seamlessly crop the faces of other people (usually celebrities or public figures) from an
authentic video into other pre-existing videos. While some uses of this technology can be
beneficial or harmless, the potential for real damage is also present. This recent
phenomenon, often called “Deepfakes,” has gained media attention due to early adopters and
programmers using it to place the face of female celebrities onto the bodies of actresses in
unrelated adult film videos. A celebrity therefore appears to be participating in a
pornographic video even though, in reality, they have not done so. The actress Emma Watson
was one of the first targets of this technology, finding her face cropped onto an explicit porn
video without her consent. She is currently embroiled in a lawsuit filed against the producer
of the faked video. While the Emma Watson case is still in progress, the difficulty of getting
videos like these taken down cannot be understated. Law professor Eric Goldman points out
the difficulty of pursuing such cases. He notes that while defamation and slander laws may
apply to Deepfake videos, there is no straightforward or clear legal path for getting videos
like these taken down, especially given their ability to re-appear once uploaded to the
internet. While pornography is protected as a form of expression or art of some producer,
Deepfake technology creates the possibility of creating adult films without the consent of
those “acting” in it. Making matters more complex is the increasing ease with which this
technology is available: forums exist with users offering advice on making faked videos and
a phone app is available for download that can be employed by basically anyone to make a
Deepfake video using little more than a few celebrity images.
Part of the challenge presented by Deepfakes concerns a conflict between aesthetic values
and issues of consent. Celebrities or targets of faked videos did not consent to be portrayed
in this manner, a fact which has led prominent voices in the adult film industry to condemn
http://www.mediaethicsinitiative.org/
https://pixabay.com/en/binary-code-woman-face-view-1327501/
https://pixabay.com/en/service/terms/#usage
2 | www.mediaethicsinitiative.org
Deepfakes. One adult film company executive characterized the problem with Deepfakes in
a Variety article: “it’s f[**]ed up. Everything we do … is built around the word consent.
Deepfakes by defini ...
1 www.mediaethicsinitiative.org How Deep Does the .docxteresehearn
1 | www.mediaethicsinitiative.org
How Deep Does the Virtual Rabbit Hole Go?
“Deepfakes” and the Ethics of Faked Video Content
Photo: Geralt / CC0
The Internet has a way of both refining techniques and technologies by pushing them to their
limits—and of bending them toward less-altruistic uses. For instance, artificial intelligence
is increasingly being used to push the boundaries of what appears to be reality in faked
videos. The premise of the phenomenon is straightforward: use artificial intelligence to
seamlessly crop the faces of other people (usually celebrities or public figures) from an
authentic video into other pre-existing videos. While some uses of this technology can be
beneficial or harmless, the potential for real damage is also present. This recent
phenomenon, often called “Deepfakes,” has gained media attention due to early adopters and
programmers using it to place the face of female celebrities onto the bodies of actresses in
unrelated adult film videos. A celebrity therefore appears to be participating in a
pornographic video even though, in reality, they have not done so. The actress Emma Watson
was one of the first targets of this technology, finding her face cropped onto an explicit porn
video without her consent. She is currently embroiled in a lawsuit filed against the producer
of the faked video. While the Emma Watson case is still in progress, the difficulty of getting
videos like these taken down cannot be understated. Law professor Eric Goldman points out
the difficulty of pursuing such cases. He notes that while defamation and slander laws may
apply to Deepfake videos, there is no straightforward or clear legal path for getting videos
like these taken down, especially given their ability to re-appear once uploaded to the
internet. While pornography is protected as a form of expression or art of some producer,
Deepfake technology creates the possibility of creating adult films without the consent of
those “acting” in it. Making matters more complex is the increasing ease with which this
technology is available: forums exist with users offering advice on making faked videos and
a phone app is available for download that can be employed by basically anyone to make a
Deepfake video using little more than a few celebrity images.
Part of the challenge presented by Deepfakes concerns a conflict between aesthetic values
and issues of consent. Celebrities or targets of faked videos did not consent to be portrayed
in this manner, a fact which has led prominent voices in the adult film industry to condemn
http://www.mediaethicsinitiative.org/
https://pixabay.com/en/binary-code-woman-face-view-1327501/
https://pixabay.com/en/service/terms/#usage
2 | www.mediaethicsinitiative.org
Deepfakes. One adult film company executive characterized the problem with Deepfakes in
a Variety article: “it’s f[**]ed up. Everything we do … is built around the word consent.
Deepfakes by defini.
The dispersal of data likewise experienced in the continuous Russia-Ukraine war. Deepfake recordings of leaders of the two sides hit virtual entertainment. Also, it's not a genuinely new thing. Figure out what is deepfake
Video & AI: capabilities and limitations of AI in detecting video manipulationsVasileiosMezaris
Invited presentation given by Dr. Vasileios Mezaris during the Greek Media Literacy Week 2019; specifically, presented in the international conference on "Disinformation in Cyberspace: Media literacy meets Artificial Intelligence" that was organized as part of the Media Literacy Week 2019 in Athens, Greece, on November 15, 2019.
Unmasking deepfakes: A systematic review of deepfake detection and generation...Araz Taeihagh
Due to the fast spread of data through digital media, individuals and societies must assess the reliability of information. Deepfakes are not a novel idea but they are now a widespread phenomenon. The impact of deepfakes and disinformation can range from infuriating individuals to affecting and misleading entire societies and even nations. There are several ways to detect and generate deepfakes online. By conducting a systematic literature analysis, in this study we explore automatic key detection and generation methods, frameworks, algorithms, and tools for identifying deepfakes (audio, images, and videos), and how these approaches can be employed within different situations to counter the spread of deepfakes and the generation of disinformation. Moreover, we explore state-of-the-art frameworks related to deepfakes to understand how emerging machine learning and deep learning approaches affect online disinformation. We also highlight practical challenges and trends in implementing policies to counter deepfakes. Finally, we provide policy recommendations based on analyzing how emerging artificial intelligence (AI) techniques can be employed to detect and generate deepfakes online. This study benefits the community and readers by providing a better understanding of recent developments in deepfake detection and generation frameworks. The study also sheds a light on the potential of AI in relation to deepfakes.
This is a PPT of SOCIAL MEDIA THREATS AND THEIR PREVENTION. This is help full for learning. Thanks.
Social media offers an outlet for people to connect, share life experiences, pictures and video. But too much sharing—or a lack of attention to impostors—can lead to a compromise of business and personal accounts.
Attackers often use social media accounts during the reconnaissance phase of a social engineering or phishing attack. Social media can give attackers a platform to impersonate trusted people and brands or the information they need carry out additional attacks, including social engineering and phishing.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
2. INTRODUCTION
► Deepfakes are synthetic media in which a person in an existing
image or video is replaced by someone's else likeness.
► It is a term used to describe a type of artificial intelligence
technology that can be used to create realistic fake videos or
images.
► The term "deepfake" is a combination of "deep learning" and
"fake“.
3. HISTORY
Photo manipulation was developed in the 19th century and soon
applied to motion pictures. Technology steadily improved during the
20th century, and more quickly with the advent of digital video.
Deepfake technology has been developed by researchers at academic
institutions beginning in the 1990s, and later by amateurs in online
communities. More recently the methods have been adopted by
industry.
In recent time, Deepfake technology has been used to impersonate
notable personalities like former U.S. Presidents Barack Obama and
Donald Trump, India's Prime Minister Narendra Modi, etc.
4. HOW IT WORKS?
Deepfakes are created by training a machine learning model on
large amounts of data, such as photos or videos of a person's face
or voice. The model then learns to generate realistic media of the
person, even though the media may be entirely fabricated.
In the given fig we can observe the
accuracy of deepfake technology.
5. AIM & OBJECTIVES
The aim of deepfake technology is to create realistic digital content that
can be used for various purposes, including entertainment, education,
and etc., Objectives include:
• Entertainment-Deepfakes can be used to create realistic special effects
in movies, TV Shows, and video games.
• Education-Deepfakes can be used to create realistic simulations for
training purposes, such as medical procedures or military exercises.
• Social media content-Deepfakes can be used to create humorous or
satirical videos for social media platforms.
6. ADVANTAGES
1.Low-Cost Video Campaigns:
Marketers using deepfakes can save money on the budgets for their
video campaigns using because you don’t need an in-person actor.
Instead of using an in-person actor, a marketer can purchase a license
for an actor’s identity.
2. Professional training:
Deepfake technology can be used to create AI Avatars for used in
training videos . Startups like London-based Synthesia have been
getting more attention from the corporate world during the COVID
pandemic since lockdowns and health concerns have made video
shoots involving real people much more difficult to pull off.
7. 3.Art:
You can bring back a decedent actor or actress. In many movies to make
a digital creation of an dead person it is used.
4.Financial Saving:
Others point out that generative technology could potentially
democratize a number of industries. By allowing the cheap creation of
everything from videos, to advertisement and games, generative
technology could allow individuals and companies to enter these fields
with less investment.
8. DISADVANTAGES
1.Sockpuppets:
Deepfake photographs can be used to create sock puppets , non-existent
persons, who are active both online and in traditional media. A deepfake
photograph appears to have been generated together with a legend for
an apparently non-existent person.
2. Politics/Scamming:
Deepfakes have been used to misrepresent well- known politicians in
videos to Scam people.
9. 3.Blackmail:
Deepfakes can be used to generate blackmail materials that
falsely incriminate a victim. It is possible to repurpose commodity
cryptocurrency mining hardware with a small software program to
generate this blackmail content for any number of subjects in
huge quantities, driving up the supply of fake blackmail content
limitlessly and in highly scalable fashion.
4.Lack of authenticity:
Using deepfakes in marketing campaigns could make it seem like
you are not being authentic. People might not trust your brand if
you are using fake technology to mislead them.
10. Real time examples for usage of Deepfake technology
1.Captain America: Civil War (Robert Downey Jr)
2.Avengers: Endgame (Michael Douglas, John Slattery)
3.James (Punit Rajkumar)
4.Fast & Furious 7 (Paul Walker)
5.US President Campaigns (Mr. Barack Obama)
11. CONCLUSION
In conclusion, deepfakes have the potential to be used for good or bad,
and it is up to us to determine how we use this technology.
We must be aware of its potential benefits and drawbacks, and take
steps to regulate its use to ensure that it is used ethically and
responsibly.
At the same time, we must continue to invest in technology that can
detect deepfakes and prevent them from spreading false information or
causing harm.
