#FactCheck: Viral video blast of fuel tank in UAE Al Hariyah Port portray as Russia-Ukraine Conflict

Introduction
‍

The rapid rise of AI tools has reshaped how health content spreads on platforms like Instagram Reels and YouTube Shorts. These sub-minute videos promise quick fixes for weight loss, glowing skin, or reduced anxiety, often delivered through polished visuals and confident AI-generated voiceovers. The result feels highly personalised, as if the advice is tailored to each viewer, even though it is usually generic and widely recycled.

Short-form videos tend to compress complex health topics into “one tip” solutions, such as drinking a specific detox drink daily or following a single workout for rapid fat loss. While appealing, this oversimplification removes essential context, including individual health conditions, long-term risks, and scientific nuance. For example, viral diet trends or fitness hacks may work for some but can be ineffective or even harmful for others.

Algorithms play a major role in amplifying such content. Videos that promise dramatic transformations or instant results are more likely to gain engagement, which pushes them to wider audiences. Repeated exposure then builds familiarity, making the advice seem more credible over time. Audiences often trust this content due to its clean presentation, authoritative tone, and frequent repetition. However, the risks include misinformation, unrealistic expectations, and potential harm from unverified practices. To approach such content critically, viewers should cross-check claims with credible medical sources, avoid relying on single tip solutions, and remember that real health advice is rarely one size fits all.
‍

The Illusion of Personalisation
‍

AI-generated health content often mimics personalisation through:

• Synthetic voiceovers that designers created to match different age groups through their voice output, which speak specifically to people who are 20 years old and younger.
• The script development process uses data that tracks currently popular search terms.
• Viewers can interpret information through visual elements, which show changes between two different states.

The process of "personalisation" uses generalised data that does not match individual health profiles to create targeted results. The videos fail to provide a medical assessment because they do not consider:

• Existing medical conditions
• Hereditary differences
• Personal habits and the impact of surrounding conditions

The users will think that general medical advice applies to their personal health needs, which will lead them to use this advice inappropriately.

‍

Short-Form Content and Oversimplification
‍

Short-form videos have time limitations, which result in reduced complex medical information development into basic medical stories. The typical patterns of evaluation include these two patterns of evaluation include:

• “One-tip solutions” (e.g., “Drink this before bed to burn fat”)
• Binary framing (“good vs bad foods”)
• The process of eliminating all disclaimers and side effects information

For example, the three diet methods here the three diet methods here

• Viral detox drinks that make the claim to "flush toxins" from the body
• Extreme calorie-cutting diet hacks
• Fitness shortcuts that guarantee users will see results within days

The content demonstrates a pattern of disregarding essential human body operation rules that include both metabolic patterns and human body operation over extended periods of time.
‍

Algorithmic Amplification and Virality
‍

The recommendation algorithms used by Instagram and YouTube deliver their most important results through three main factors, which include:

• Engagement (likes, shares, watch time)
• Retention rates
• Emotional or aspirational triggers 

Health-related content that claims to deliver:

• Immediate body changes
• Needs minimal work from viewers
• Results in extreme physical changes

Attractive health-related content that displays extreme physical changes through quick transformations. The system produces a continuous cycle during which:

1. Misleading content gains traction
2. Algorithms amplify it further
3. More creators replicate similar formats using AI tools 

The system produces a secondary result that favours content that people share instead of content that has authentic credibility.
‍

Why Do Users Trust AI-Generated Health Content?
‍

Several psychological and technological factors contribute to trust:

1. Professional Aesthetics - AI tools generate high-quality visual content together with authentic voiceover performance and expert-level script documentation, which replicates professional communication methods.
2. Repetition and Familiarity - When people encounter identical recommendations multiple times, their belief in those recommendations increases through the illusory truth effect.
3. Authority Signals

• Medical terminology serves as a standard term
• Medical professionals appear in stock footage through lab coat visuals
• The narrator delivers information through an assertive speaking style

4. Perceived Personal Relevance - Algorithmic targeting makes users feel the content is "meant for them.

Real-World Examples of Viral Trends
‍

The typical types of health misinformation that artificial intelligence systems spread through their enhanced capabilities include:

• Diet Trends: Keto shortcuts, extreme intermittent fasting variants
• Fitness Hacks: Spot reduction exercises (scientifically unsupported)
• Supplement Advice: Unverified claims about vitamins or herbal products
• Mental Health Tips: Oversimplified coping strategies that lack clinical evidence

The statement that drinking warm lemon water will detox your liver continues to be popular despite the fact that the liver has natural self-detoxification abilities.

‍

Risks and Public Health Implications
‍

The widespread consumption of such content creates multiple dangers, which include:

1. Physical Health Risks

• Nutritional deficiencies from extreme diets
• Injury from improper exercise techniques
• Delayed medical consultation

2. Psychological Impact

• Unrealistic body image expectations
• Anxiety due to conflicting advice

3. Misinformation Ecosystem

• The public loses confidence in evidence-based medicine
• Unverified or pseudoscientific practices spread throughout society

Regulatory and Ethical Concerns

The increase of AI-generated health materials connects to more extensive problems, which include:

• Who is responsible for the content
• Who is responsible for the platform
• How AI systems show their inner workings to users

Most platforms today do not have strict systems that can:

• Verify medical claims
• Display which health advice comes from artificial intelligence
• Punish users who spread false information multiple times

The absence of regulations allows misleading information to spread without consequences.
‍

A CyberPeace Perspective: Building Digital Health Resilience
‍

The problem needs complete involvement from several parties to create effective solutions that protect both online security and data integrity. 
‍

For Users

• Users should confirm claims by using trustworthy medical resources, which include the WHO and peer-reviewed studies.
• People should avoid using "quick solutions" until they receive guidance from certified experts.
• Users should exercise caution when they encounter content that does not include necessary warning signs.

For Platforms

• Platforms should implement systems that enable users to identify AI-generated content.
• Platforms should decrease the visibility of health information that contains false statements.
• Platforms should support authentic health content producers who have been validated.

For Policymakers

• Policymakers should create standards that govern AI-produced medical content.
• Policymakers need to enhance initiatives that teach people about the health information available online.

For Content Creators

• Content creators must show how they implement AI technologies.
• They should stay away from making claims that either go beyond what is needed or state things as absolute truth.

Conclusion
‍

AI-generated health tips on short-form video platforms create complex research conditions that involve three scientific fields: technology, psychology and public health. The tools provide equal access to information, yet create higher risks for people to believe false information when they use the tools without responsible usage. 

The challenge requires organisations to maintain user safety through accurate information management while providing users with transparent digital health services. The growing dependence of users on algorithm-based content requires educational institutions to develop students' critical thinking abilities and digital skills to minimise negative effects from AI-driven communication methods.
‍

References
‍

• https://pmc.ncbi.nlm.nih.gov/articles/PMC12924558/
• https://academic.oup.com/heapro/article/40/2/daaf023/8100645
• https://pmc.ncbi.nlm.nih.gov/articles/PMC12673052/
• https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1713794/full
• https://www.who.int/teams/digital-health-and-innovation/digital-channels/combatting-misinformation-online
• https://link.springer.com/article/10.1186/s12982-025-00777-2
• https://www.washingtonpost.com/health/2026/04/21/chatbot-medical-advice-accurate/

‍

Introduction 

The geographical world has physical boundaries, but the digital one has a different architecture and institutions are underprepared when it comes to addressing cybersecurity breaches. Cybercrime, which may lead to economic losses, privacy violations, national security threats and have psycho-social consequences,  is forecast to continuously increase between 2024 and 2029, reaching an estimated cost of at least 6.4 trillion U.S. dollars (Statista). As cyber threats become persistent and ubiquitous, they are becoming a critical governance challenge. Lawmakers around the world need to collaborate on addressing this emerging issue.

Cybersecurity Governance and its Structural Elements

Cybersecurity governance refers to the strategies, policies, laws, and institutional frameworks that guide national and international preparedness and responses to cyber threats to governments, private entities, and individuals. Effective cybersecurity governance ensures that digital risks are managed proactively while balancing security with fundamental rights like privacy and internet freedom. It includes, but is not limited to :

1. Policies and Legal Frameworks: Laws that define the scope of cybercrime, cybersecurity responsibilities, and mechanisms for data protection. Eg: India’s National Cybersecurity Policy (NCSP) of 2013, Information Technology Act, 2000, and Digital Personal Data Protection Act, 2023, EU’s Cybersecurity Act (2019), Cyber Resilience Act (2024), Cyber Solidarity Act (2025), and NIS2 Directive (2022), South Africa’s Cyber Crimes Act (2021), etc.
2. Regulatory Bodies: Government agencies such as data protection authorities, cybersecurity task forces, and other sector-specific bodies. Eg: India’s Computer Emergency Response Team (CERT-In), Indian Cyber Crime Coordination Centre (I4C), Europe’s  European Union Agency for Cybersecurity (ENISA), and others.
3. Public-Private Knowledge Sharing: The sharing of the private sector’s expertise and the government’s resources plays a crucial role in improving enforcement and securing critical infrastructure. This model of collaboration is followed in the EU, Japan, Turkey, and the USA. 
4. Research and Development: Apart from the technical, the cyber domain also includes military, politics, economy, law, culture, society, and other elements. Robust, multi-sectoral research is necessary for formulating international and regional frameworks on cybersecurity. 

Challenges to Cybersecurity Governance 

Governments face several challenges in securing cyberspace and protecting critical assets and individuals despite the growing focus on cybersecurity. This is because so far the focus has been on cybersecurity management, which, considering the scale of attacks in the recent past, is not enough. Stakeholders must start deliberating on the aspect of governance in cyberspace while ensuring that this process is multi-consultative. (Savaş & Karataş 2022). Prominent challenges which need to be addressed are: 

• Dynamic Threat Landscape: The threat landscape in cyberspace is ever-evolving.  Bad actors are constantly coming up with new ways to carry out attacks, using elements of surprise, adaptability, and asymmetry aided by AI and quantum computing. While cybersecurity measures help mitigate risks and minimize damage, they can’t always provide definitive solutions. E.g., the pace of malware development is much faster than that of legal norms, legislation, and security strategies for the protection of information technology (IT). (Efe and Bensghir 2019).
• Regulatory Fragmentation and Compliance Challenges: Different countries, industries, or jurisdictions may enforce varying or conflicting cybersecurity laws and standards, which are still evolving and require rapid upgrades. This makes it harder for businesses to comply with regulations, increases compliance costs, and jeopardizes the security posture of the organization. 
• Trans-National Enforcement Challenges: Cybercriminals operate across jurisdictions, making threat intelligence collection, incident response, evidence-gathering, and prosecution difficult.  Without cross-border agreements between law enforcement agencies and standardized compliance frameworks for organizations, bad actors have an advantage in getting away with attacks. 
• Balancing Security with Digital Rights: Striking a balance between cybersecurity laws and privacy concerns (e.g., surveillance laws vs. data protection) remains a profound challenge,  especially in areas of CSAM prevention and identifying terrorist activities. Without a system of checks and balances, it is difficult to prevent government overreach into domains like journalism, which are necessary for a healthy democracy, and Big Tech’s invasion of user privacy. 

The Road Ahead: Strengthening Cybersecurity Governance 

All domains of human life- economy, culture, politics, and society- occur in digital and cyber environments now. It follows naturally, that governance in the physical world translates into governance in cyberspace. It must be underpinned by features consistent with the principles of openness, transparency, participation, and accountability, while also protecting human rights. In cyberspace, the world is stateless and threats are rapidly evolving with innovations in modern computing. Thus, cybersecurity governance requires a global, multi-sectoral approach utilizing the rules of international law, to chart out problems, and solutions, and carry out detailed risk analyses. (Savaş & Karataş 2022). 

References

• https://www.statista.com/forecasts/1280009/cost-cybercrime-worldwide#statisticContainer
• https://link.springer.com/article/10.1365/s43439-021-00045-4#citeas 
• https://digital-strategy.ec.europa.eu/en/policies/cybersecurity-policies#ecl-inpage-cybersecurity-strategy 

‍

Introduction

The whole world is shifting towards a cashless economy, with innovative payment transaction systems such as UPI payments, card payments, etc. These payment systems require processing, storage, and movement of millions of cardholders data which is crucial for any successful transaction.

And therefore to maintain the credibility of this payment ecosystem, security or secure movement and processing of cardholders data becomes paramount. Entities involved in a payment ecosystem are responsible for the security of cardholders data. Security is also important because if breaches happen in cardholders data it would amount to financial loss. Fraudsters are attempting smart ways to leverage any kind of security loopholes in the payment system.

So these entities which are involved in the payment ecosystem need to maintain some security standards set by one council of network providers in the payment industry popularly known as the Payment Card Industry Security Standard Council.

Overview of what is PCI and PCI DSS Compliance

Earlier every network providers in the payment industry have their own set of security standards but later they all together i.e., Visa, Mastercard, American Express, Discover, and JCB constituted an independent body to come up with comprehensive security standards like PCI DSS, PA DSS, PCI-PTS, etc.  And these network providers ensure the enforcement of the security standards by putting conditions on services being provided to the merchant or acquirer bank.

In other words, PCI DSS particularly is the global standard that provides a baseline of technical and operational requirements designed to protect account data. PCI DSS is a security standard specially designed for merchants and service providers in the payment ecosystem to protect the cardholders data against any fraud or theft.

It applies to all the entities including third-party vendors which are involved in processing storing and transmitting cardholders data. In organization, even all CDE (Card Holder Data Environment) including system components or network component that stores and process cardholders data, has to comply with all the requirements of PCI compliance.  Recently PCI has released a new version of PCI DSS v4.0 a few months ago with certain changes from the previous version after three years of the review cycle.

12 Requirements of PCI DSS

This is the most important part of PCI DSS as following these requirements can make any organization to some extent PCI compliant. So what are these requirements:

• Installing firewalls or maintaining security controls in the networks
• Use strong password in order to secure the CDE( Card holders data environment)
• Protection of cardholder data
• Encrypting the cardholder data during transmission over an open and public network.
• Timely detection and protection of the cardholders data environment from any malicious activity or software.
• Regular updating the software thereby maintaining a secure system.
• Rule of business need to know should apply to access the cardholders data
• Identification and authentication of the user are important to access the system components.
• Physical access to cardholders data should be restricted.
• Monitoring or screening of system components to know the malicious activity internally in real-time.
• Regular auditing of security control and finding any vulnerabilities available in the systems.
• Make policies and programs accordingly in order to support information security.

How organization can become PCI compliant

• Scope: First step is to determine all the system components or networks storing and processing cardholders data i.e., Cardholders Data Environment.
• Assess: Then test whether these systems or networks are complying with all the requirements of PCI DSS COMPLIANCE.
• Report: Documenting all the assessment through self assessment questionnaire by answering following questions like whether the requirements are met or not? Whether the requirements are met with customized approach.
• Attest: Then the next step is to complete the attestation process available on the website of PCI SSC.
• Submit: Then organization can submit all the documents including reports and other supporting documents if it is requested by other entities such as payment brands, merchant or acquirer.
• Remediate: Then the organisation should take remedial action for the requirements which are not in place on the system components or networks.

Conclusion

One of the most important issues facing those involved in the digital payment ecosystem is cybersecurity. The likelihood of being exposed to cybersecurity hazards including online fraud, information theft, and virus assaults is rising as more and more users prefer using digital payments.

And thus complying and adopting with these security standards is the need of the hour. And moreover RBI has also mandated all the regulated entities ( NBFCs Banks etc) under one recent notification to comply with these standards.