#FactCheck - AI-Generated Image Falsely Shows Mohammed Siraj Offering Namaz During Net Practice

Introduction

The advent of AI-driven deepfake technology has facilitated the creation of explicit counterfeit videos for sextortion purposes. There has been an alarming increase in the use of Artificial Intelligence to create fake explicit images or videos for sextortion.

What is AI Sextortion and Deepfake Technology

AI sextortion refers to the use of artificial intelligence (AI) technology, particularly deepfake algorithms, to create counterfeit explicit videos or images for the purpose of harassing, extorting, or blackmailing individuals. Deepfake technology utilises AI algorithms to manipulate or replace faces and bodies in videos, making them appear realistic and often indistinguishable from genuine footage. This enables malicious actors to create explicit content that falsely portrays individuals engaging in sexual activities, even if they never participated in such actions.

Background on the Alarming Increase in AI Sextortion Cases

Recently there has been a significant increase in AI sextortion cases. Advancements in AI and deepfake technology have made it easier for perpetrators to create highly convincing fake explicit videos or images. The algorithms behind these technologies have become more sophisticated, allowing for more seamless and realistic manipulations. And the accessibility of AI tools and resources has increased, with open-source software and cloud-based services readily available to anyone. This accessibility has lowered the barrier to entry, enabling individuals with malicious intent to exploit these technologies for sextortion purposes.

The proliferation of sharing content on social media

The proliferation of social media platforms and the widespread sharing of personal content online have provided perpetrators with a vast pool of potential victims’ images and videos. By utilising these readily available resources, perpetrators can create deepfake explicit content that closely resembles the victims, increasing the likelihood of success in their extortion schemes.

Furthermore, the anonymity and wide reach of the internet and social media platforms allow perpetrators to distribute manipulated content quickly and easily. They can target individuals specifically or upload the content to public forums and pornographic websites, amplifying the impact and humiliation experienced by victims.

What are law agencies doing?

The alarming increase in AI sextortion cases has prompted concern among law enforcement agencies, advocacy groups, and technology companies. This is high time to make strong Efforts to raise awareness about the risks of AI sextortion, develop detection and prevention tools, and strengthen legal frameworks to address these emerging threats to individuals’ privacy, safety, and well-being.

There is a need for Technological Solutions, which develops and deploys advanced AI-based detection tools to identify and flag AI-generated deepfake content on platforms and services. And collaboration with technology companies to integrate such solutions.

Collaboration with Social Media Platforms is also needed. Social media platforms and technology companies can reframe and enforce community guidelines and policies against disseminating AI-generated explicit content. And can ensure foster cooperation in developing robust content moderation systems and reporting mechanisms.

There is a need to strengthen the legal frameworks to address AI sextortion, including laws that specifically criminalise the creation, distribution, and possession of AI-generated explicit content. Ensure adequate penalties for offenders and provisions for cross-border cooperation.

Proactive measures to combat AI-driven sextortion

Prevention and Awareness: Proactive measures raise awareness about AI sextortion, helping individuals recognise risks and take precautions.

Early Detection and Reporting: Proactive measures employ advanced detection tools to identify AI-generated deepfake content early, enabling prompt intervention and support for victims.

Legal Frameworks and Regulations: Proactive measures strengthen legal frameworks to criminalise AI sextortion, facilitate cross-border cooperation, and impose offender penalties.

Technological Solutions: Proactive measures focus on developing tools and algorithms to detect and remove AI-generated explicit content, making it harder for perpetrators to carry out their schemes.

International Cooperation: Proactive measures foster collaboration among law enforcement agencies, governments, and technology companies to combat AI sextortion globally.

Support for Victims: Proactive measures provide comprehensive support services, including counselling and legal assistance, to help victims recover from emotional and psychological trauma.

Implementing these proactive measures will help create a safer digital environment for all.

Misuse of Technology

Misusing technology, particularly AI-driven deepfake technology, in the context of sextortion raises serious concerns.

Exploitation of Personal Data: Perpetrators exploit personal data and images available online, such as social media posts or captured video chats, to create AI- manipulation violates privacy rights and exploits the vulnerability of individuals who trust that their personal information will be used responsibly.

Facilitation of Extortion: AI sextortion often involves perpetrators demanding monetary payments, sexually themed images or videos, or other favours under the threat of releasing manipulated content to the public or to the victims’ friends and family. The realistic nature of deepfake technology increases the effectiveness of these extortion attempts, placing victims under significant emotional and financial pressure.

Amplification of Harm: Perpetrators use deepfake technology to create explicit videos or images that appear realistic, thereby increasing the potential for humiliation, harassment, and psychological trauma suffered by victims. The wide distribution of such content on social media platforms and pornographic websites can perpetuate victimisation and cause lasting damage to their reputation and well-being.

Targeting teenagers– Targeting teenagers and extortion demands in AI sextortion cases is a particularly alarming aspect of this issue. Teenagers are particularly vulnerable to AI sextortion due to their increased use of social media platforms for sharing personal information and images. Perpetrators exploit to manipulate and coerce them.

Erosion of Trust: Misusing AI-driven deepfake technology erodes trust in digital media and online interactions. As deepfake content becomes more convincing, it becomes increasingly challenging to distinguish between real and manipulated videos or images.

Proliferation of Pornographic Content: The misuse of AI technology in sextortion contributes to the proliferation of non-consensual pornography (also known as “revenge porn”) and the availability of explicit content featuring unsuspecting individuals. This perpetuates a culture of objectification, exploitation, and non-consensual sharing of intimate material.

Conclusion

Addressing the concern of AI sextortion requires a multi-faceted approach, including technological advancements in detection and prevention, legal frameworks to hold offenders accountable, awareness about the risks, and collaboration between technology companies, law enforcement agencies, and advocacy groups to combat this emerging threat and protect the well-being of individuals online.

BharOS’s successful testing grabbed massive online attention after Ashwini Vaishnaw, Minister of Communications and Electronics & IT, and Union Education Minister Dharmendra Pradhan unveiled the new mobile operating system. On Data Privacy Day, January 28, it’s appropriate to discuss the safety factors.

The OS is developed by JandKops, which has been incubated by IIT Madras Pravartak Technologies Foundation. It is claimed that BharOS will ensure the prevention of the “execution of any malware” and “execution of any malicious application”.

Even though it is called a Made in India OS, there are many people who disagree with this. It is because the OS is based on an AOSP (Android Open Source Project). It includes similar methodologies, functionalities, and basics used in Google Android.

Global safety factor

Security and data safety has been worldwide issue. A few years ago, Alphabet CEO Sundar Pichai also testified in front of US Congress while facing questions related to privacy, data collection, and location tracking.

While experts say that Android’s app ecosystem is a privacy and security disaster, a study that examined 82,501 apps pre-installed on 1,742 Android smartphones sold by 214 vendors concluded that users are woefully unaware of the significant security and privacy risks posed by pre-installed applications.

Even Apple, which takes cybersafety issues as a top priority, sometimes finds itself in a vulnerable situation. For example, last year Apple users were advised to update their devices to protect against a pair of security flaws that could allow attackers to take complete control.

It was said that one of the software flaws affected the kernel, the deepest layer of the OS shared by all Apple devices, while the other had an impact on WebKit, the technology that powers the Safari web browser.

Security researchers, including NordVPN, said that Apple’s closed development OS makes it more difficult for hackers to develop exploits, while Android raises the threat level since anyone can see its source code to develop exploits.

BharOS is not like iOS but it is kind of similar to Android and based on AOSP. So the question is, how safe would this OS be?

‘Security blanket’

Sandip Kumar Panda, Co-founder and CEO of InstaSafe, told News18: “BharOS acts as a security blanket for devices. The framework is designed in a manner that it prevents the execution of any malicious app and verifies each app on the devices before making it live on the BharOS platform.”

There are no apps without any vulnerabilities, he said. “As the app development progresses, vulnerabilities get introduced either in the form of insecure coding practices or third-party software vulnerabilities integrated with the platform. Since several Android vulnerabilities were discovered over the years, all those bugs would have been fixed now and updates would already have been for AOSP, which will be much more mature now,” he added.

Vineet Kumar, Founder and President of CyberPeace Foundation, believes that “the use of AOSP as the foundation for BharOS is a positive step” as it is a robust platform.

But according to him, it is important to note that no OS can be completely immune to all forms of cyber threats. “The key to staying safe online is to stay vigilant, use security software, keep your software updated, and be mindful of the apps you install and the websites you visit,” he said,

Furthermore, the expert stated that it is possible to make an OS more secure by implementing a variety of security features and technologies such as sandboxing, whitelisting, and application control, as well as rigorous testing and code review processes.

Kumar said: “It would be important for an independent, reputable security firm to evaluate BharOS and test its security features before it can be stated with certainty that it is more secure than other OSs.”

It is difficult to say whether the BharOS will be free of cybersecurity issues without more information about the specific features and security measures that have been implemented, he noted while adding that this OS has to go through a rigorous testing and certification process.

“It will be important to see how it measures up against established security standards and how well it can withstand real-world attacks,” the expert stated.

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Reference Link : https://www.news18.com/amp/news/tech/data-privacy-day-how-safe-is-bharos-what-do-cybersecurity-experts-say-you-are-about-to-find-out-6932521.html

Introduction

The first activity one engages in while using social media is scrolling through their feed and liking or reacting to posts. Social media users' online activity is passive, involving merely reading and observing, while active use occurs when a user consciously decides to share information or comment after actively analysing it. We often "like" photos, posts, and tweets reflexively, hardly stopping to think about why we do it and what information it contains. This act of "liking" or "reacting" is a passive activity that can spark an active discourse. Frequently, we encounter misinformation on social media in various forms, which could be identified as false at first glance if we exercise caution and avoid validating it with our likes.

Passive engagement, such as liking or reacting to a post, triggers social media algorithms to amplify its reach, exposing it to a broader audience. This amplification increases the likelihood of misinformation spreading quickly as more people interact with it. As the content circulates, it gains credibility through repeated exposure, reinforcing false narratives and expanding its impact.

Social media platforms are designed to facilitate communication and conversations for various purposes. However, this design also enables the sharing, exchange, distribution, and reception of content, including misinformation. This can lead to the widespread spread of false information, influencing public opinion and behaviour. Misinformation has been identified as a contributing factor in various contentious events, ranging from elections and referenda to political or religious persecution, as well as the global response to the COVID-19 pandemic.

The Mechanics of Passive Sharing

Sharing a post without checking the facts mentioned or sharing it without providing any context can create situations where misinformation can be knowingly or unknowingly spread. The problem with sharing and forwarding information on social media without fact-checking is that it usually starts in small, trusted networks before going on to be widely seen across the internet. This web which begins is infinite and cutting it from the roots is necessary. The rapid spread of information on social media is driven by algorithms that prioritise engagement and often they amplify misleading or false content and contribute to the spread of misinformation.  The algorithm optimises the feed and ensures that the posts that are most likely to engage with appear at the top of the timeline, thus encouraging a cycle of liking and posting that keeps users active and scrolling.

The internet reaches billions of individuals and enables them to tailor persuasive messages to the specific profiles of individual users. The internet because of its reach is an ideal medium for the fast spread of falsehoods at the expense of accurate information. 

Recommendations for Combating Passive Sharing

The need to combat passive sharing that we indulge in is important and some ways in which we can do so are as follows:

• We need to critically evaluate the sources before sharing any content. This will ensure that the information source is not corrupted and used as a means to cause disruptions. The medium should not be used to spread misinformation due to the source's ulterior motives. Tools such as crowdsourcing and AI methods have been used in the past to evaluate the sources and have been successful to an extent.
• Engaging with fact-checking tools and verifying the information is also crucial. The information that has been shared on the post needs to be verified through authenticated sources before indulging in the practice of sharing. 
• Being mindful of the potential impact of online activity, including likes and shares is important. The kind of reach that social media users have today is due to several reasons ranging from the content they create, the rate at which they engage with other users etc.  Liking and sharing content might not seem much for an individual user but the impact it has collectively is huge.

Conclusion 

Passive sharing of misinformation, like liking or sharing without verification, amplifies false information, erodes trust in legitimate sources, and deepens social and political divides. It can lead to real-world harm and ethical dilemmas. To combat this, critical evaluation, fact-checking, and mindful online engagement are essential to mitigating this passive spread of misinformation. The small act of “like” or “share” has a much more far-reaching effect than we anticipate and we should be mindful of all our activities on the digital platform. 

References

• https://www.tandfonline.com/doi/full/10.1080/00049530.2022.2113340#summary-abstract 
• https://timesofindia.indiatimes.com/city/thane/badlapur-protest-police-warn-against-spreading-fake-news/articleshow/112750638.cms

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