Pay for Privacy? The Meta-EU Tussle to Balance Privacy and Advertising
Aditi Pangotra and Dr. Brinda Banerjee
Tech Policy and Research,CyberPeace
PUBLISHED ON
Oct 3, 2024
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Introduction
Privacy has become a concern for netizens and social media companies have access to a user’s data and the ability to use the said data as they see fit. Meta’s business model, where they rely heavily on collecting and processing user data to deliver targeted advertising, has been under scrutiny. The conflict between Meta and the EU traces back to the enactment of GDPR in 2018. Meta is facing numerous fines for not following through with the regulation and mainly failing to obtain explicit consent for data processing under Chapter 2, Article 7 of the GDPR. ePrivacy Regulation, which focuses on digital communication and digital data privacy, is the next step in the EU’s arsenal to protect user privacy and will target the cookie policies and tracking tech crucial to Meta's ad-targeting mechanism. Meta’s core revenue stream is sourced from targeted advertising which requires vast amounts of data for the creation of a personalised experience and is scrutinised by the EU.
Pay for Privacy Model and its Implications with Critical Analysis
Meta came up with a solution to deal with the privacy issue - ‘Pay or Consent,’ a model that allows users to opt out of data-driven advertising by paying a subscription fee. The platform would offer users a choice between free, ad-supported services and a paid privacy-enhanced experience which aligns with the GDPR and potentially reduces regulatory pressure on Meta.
Meta presently needs to assess the economic feasibility of this model and come up with answers for how much a user would be willing to pay for the privacy offered and shift Meta’s monetisation from ad-driven profits to subscription revenues. This would have a direct impact on Meta’s advertisers who use Meta as a platform for detailed user data for targeted advertising, and would potentially decrease ad revenue and innovate other monetisation strategies.
For the users, increased privacy and greater control of data aligning with global privacy concerns would be a potential outcome. While users will undoubtedly appreciate the option to avoid tracking, the suggestion does beg the question that the need to pay might become a barrier. This could possibly divide users between cost-conscious and privacy-conscious segments. Setting up a reasonable price point is necessary for widespread adoption of the model.
For the regulators and the industry, a new precedent would be set in the tech industry and could influence other companies’ approaches to data privacy. Regulators might welcome this move and encourage further innovation in privacy-respecting business models.
The affordability and fairness of the ‘pay or consent’ model could create digital inequality if privacy comes at a digital cost or even more so as a luxury. The subscription model would also need clarifications as to what data would be collected and how it would be used for non-advertising purposes. In terms of market competition, competitors might use and capitalise on Meta’s subscription model by offering free services with privacy guarantees which could further pressure Meta to refine its offerings to stay competitive. According to the EU, the model needs to provide a third way for users who have ads but are a result of non-personalisation advertising.
Meta has further expressed a willingness to explore various models to address regulatory concerns and enhance user privacy. Their recent actions in the form of pilot programs for testing the pay-for-privacy model is one example. Meta is actively engaging with EU regulators to find mutually acceptable solutions and to demonstrate its commitment to compliance while advocating for business models that sustain innovation. Meta executives have emphasised the importance of user choice and transparency in their future business strategies.
Future Impact Outlook
The Meta-EU tussle over privacy is a manifestation of broader debates about data protection and business models in the digital age.
The EU's stance on Meta’s ‘pay or consent’ model and any new regulatory measures will shape the future landscape of digital privacy, leading to other jurisdictions taking cues and potentially leading to global shifts in privacy regulations.
Meta may need to iterate on its approach based on consumer preferences and concerns. Competitors and tech giants will closely monitor Meta’s strategies, possibly adopting similar models or innovating new solutions. And the overall approach to privacy could evolve to prioritise user control and transparency.
Conclusion
Consent is the cornerstone in matters of privacy and sidestepping it violates the rights of users. The manner in which tech companies foster a culture of consent is of paramount importance in today's digital landscape. As the exploration by Meta in the ‘pay or consent’ model takes place, it faces both opportunities and challenges in balancing user privacy with business sustainability. This situation serves as a critical test case for the tech industry, highlighting the need for innovative solutions that respect privacy while fostering growth with the specificity of dealing with data protection laws worldwide, starting with India’s Digital Personal Data Protection Act, of 2023.
The viral image in the social media which depicts fake injuries on the face of the MP(Member of Parliament, Lok Sabha) Kangana Ranaut alleged to have been beaten by a CISF officer at the Chandigarh airport. The reverse search of the viral image taken back to 2006, was part of an anti-mosquito commercial and does not feature the MP, Kangana Ranaut. The findings contradict the claim that the photos are evidence of injuries resulting from the incident involving the MP, Kangana Ranaut. It is always important to verify the truthfulness of visual content before sharing it, to prevent misinformation.
Claims:
The images circulating on social media platforms claiming the injuries on the MP, Kangana Ranaut’s face were because of an assault incident by a female CISF officer at Chandigarh airport. This claim hinted that the photos are evidence of the physical quarrel and resulting injuries suffered by the MP, Kangana Ranaut.
When we received the posts, we reverse-searched the image and found another photo that looked similar to the viral one. We could verify through the earring in the viral image with the new image.
The reverse image search revealed that the photo was originally uploaded in 2006 and is unrelated to the MP, Kangana Ranaut. It depicts a model in an advertisement for an anti-mosquito spray campaign.
We can validate this from the earrings in the photo after the comparison between the two photos.
Hence, we can confirm that the viral image of the injury mark of the MP, Kangana Ranaut has been debunked as fake and misleading, instead it has been cropped out from the original photo to misrepresent the context.
Conclusion:
Therefore, the viral photos on social media which claimed to be the results of injuries on the MP, Kangana Ranaut’s face after being assaulted allegedly by a CISF officer at the airport in Chandigarh were fake. Detailed analysis of the pictures provided the fact that the pictures have no connection with Ranaut; the picture was a 2006 anti-mosquito spray advertisement; therefore, the allegations that show these images as that of Ranaut’s injury are fake and misleading.
Claim: photos circulating on social media claiming to show injuries on the MP, Kangana Ranaut's face following an assault incident by a female CISF officer at Chandigarh airport.
Claimed on: X (Formerly known as Twitter), thread, Facebook
The rapid digitization of educational institutions in India has created both opportunities and challenges. While technology has improved access to education and administrative efficiency, it has also exposed institutions to significant cyber threats. This report, published by CyberPeace, examines the types, causes, impacts, and preventive measures related to cyber risks in Indian educational institutions. It highlights global best practices, national strategies, and actionable recommendations to mitigate these threats.
Image: Recent CyberAttack on Eindhoven University
Significance of the Study:
The pandemic-induced shift to online learning, combined with limited cybersecurity budgets, has made educational institutions prime targets for cyberattacks. These threats compromise sensitive student, faculty, and institutional data, leading to operational disruptions, financial losses, and reputational damage. Globally, educational institutions face similar challenges, emphasizing the need for universal and localized responses.
Threat Faced by Education Institutions:
Based on the insights from the CyberPeace’s report titled 'Exploring Cyber Threats and Digital Risks in Indian Educational Institutions', this concise blog provides a comprehensive overview of cybersecurity threats and risks faced by educational institutions, along with essential details to address these challenges.
🎣 Phishing: Phishing is a social engineering tactic where cyber criminals impersonate trusted sources to steal sensitive information, such as login credentials and financial details. It often involves deceptive emails or messages that lead to counterfeit websites, pressuring victims to provide information quickly. Variants include spear phishing, smishing, and vishing.
💰 Ransomware: Ransomware is malware that locks users out of their systems or data until a ransom is paid. It spreads through phishing emails, malvertising, and exploiting vulnerabilities, causing downtime, data leaks, and theft. Ransom demands can range from hundreds to hundreds of thousands of dollars.
🌐 Distributed Denial of Service (DDoS): DDoS attacks overwhelm servers, denying users access to websites and disrupting daily operations, which can hinder students and teachers from accessing learning resources or submitting assignments. These attacks are relatively easy to execute, especially against poorly protected networks, and can be carried out by amateur cybercriminals, including students or staff, seeking to cause disruptions for various reasons
🕵️ Cyber Espionage: Higher education institutions, particularly research-focused universities, are vulnerable to spyware, insider threats, and cyber espionage. Spyware is unauthorized software that collects sensitive information or damages devices. Insider threats arise from negligent or malicious individuals, such as staff or vendors, who misuse their access to steal intellectual property or cause data leaks..
🔒 Data Theft: Data theft is a major threat to educational institutions, which store valuable personal and research information. Cybercriminals may sell this data or use it for extortion, while stealing university research can provide unfair competitive advantages. These attacks can go undetected for long periods, as seen in the University of California, Berkeley breach, where hackers allegedly stole 160,000 medical records over several months.
🛠️ SQL Injection: SQL injection (SQLI) is an attack that uses malicious code to manipulate backend databases, granting unauthorized access to sensitive information like customer details. Successful SQLI attacks can result in data deletion, unauthorized viewing of user lists, or administrative access to the database.
🔍Eavesdropping attack: An eavesdropping breach, or sniffing, is a network attack where cybercriminals steal information from unsecured transmissions between devices. These attacks are hard to detect since they don't cause abnormal data activity. Attackers often use network monitors, like sniffers, to intercept data during transmission.
🤖 AI-Powered Attacks: AI enhances cyber attacks like identity theft, password cracking, and denial-of-service attacks, making them more powerful, efficient, and automated. It can be used to inflict harm, steal information, cause emotional distress, disrupt organizations, and even threaten national security by shutting down services or cutting power to entire regions
Insights from Project eKawach
The CyberPeace Research Wing, in collaboration with SAKEC CyberPeace Center of Excellence (CCoE) and Autobot Infosec Private Limited, conducted a study simulating educational institutions' networks to gather intelligence on cyber threats. As part of the e-Kawach project, a nationwide initiative to strengthen cybersecurity, threat intelligence sensors were deployed to monitor internet traffic and analyze real-time cyber attacks from July 2023 to April 2024, revealing critical insights into the evolving cyber threat landscape.
Cyber Attack Trends
Between July 2023 and April 2024, the e-Kawach network recorded 217,886 cyberattacks from IP addresses worldwide, with a significant portion originating from countries including the United States, China, Germany, South Korea, Brazil, Netherlands, Russia, France, Vietnam, India, Singapore, and Hong Kong. However, attributing these attacks to specific nations or actors is complex, as threat actors often use techniques like exploiting resources from other countries, or employing VPNs and proxies to obscure their true locations, making it difficult to pinpoint the real origin of the attacks.
Brute Force Attack:
The analysis uncovered an extensive use of automated tools in brute force attacks, with 8,337 unique usernames and 54,784 unique passwords identified. Among these, the most frequently targeted username was “root,” which accounted for over 200,000 attempts. Other commonly targeted usernames included: "admin", "test", "user", "oracle", "ubuntu", "guest", "ftpuser", "pi", "support"
Similarly, the study identified several weak passwords commonly targeted by attackers. “123456” was attempted over 3,500 times, followed by “password” with over 2,500 attempts. Other frequently targeted passwords included: "1234", "12345", "12345678", "admin", "123", "root", "test", "raspberry", "admin123", "123456789"
Insights from Threat Landscape Analysis
Research done by the USI - CyberPeace Centre of Excellence (CCoE) and Resecurity has uncovered several breached databases belonging to public, private, and government universities in India, highlighting significant cybersecurity threats in the education sector. The research aims to identify and mitigate cybersecurity risks without harming individuals or assigning blame, based on data available at the time, which may evolve with new information. Institutions were assigned risk ratings that descend from A to F, with most falling under a D rating, indicating numerous security vulnerabilities. Institutions rated D or F are 5.4 times more likely to experience data breaches compared to those rated A or B. Immediate action is recommended to address the identified risks.
Risk Findings :
The risk findings for the institutions are summarized through a pie chart, highlighting factors such as data breaches, dark web activity, botnet activity, and phishing/domain squatting. Data breaches and botnet activity are significantly higher compared to dark web leakages and phishing/domain squatting. The findings show 393,518 instances of data breaches, 339,442 instances of botnet activity, 7,926 instances related to the dark web and phishing & domain activity - 6711.
Key Indicators: Multiple instances of data breaches containing credentials (email/passwords) in plain text.
Botnet activity indicating network hosts compromised by malware.
Credentials from third-party government and non-governmental websites linked to official institutional emails
Details of software applications, drivers installed on compromised hosts.
Sensitive cookie data exfiltrated from various browsers.
IP addresses of compromised systems.
Login credentials for different Android applications.
Below is the sample detail of one of the top educational institutions that provides the insights about the higher rate of data breaches, botnet activity, dark web activities and phishing & domain squatting.
Risk Detection:
It indicates the number of data breaches, network hygiene, dark web activities, botnet activities, cloud security, phishing & domain squatting, media monitoring and miscellaneous risks. In the below example, we are able to see the highest number of data breaches and botnet activities in the sample particular domain.
Risk Changes:
Risk by Categories:
Risk is categorized with factors such as high, medium and low, the risk is at high level for data breaches and botnet activities.
Challenges Faced by Educational Institutions
Educational institutions face cyberattack risks, the challenges leading to cyberattack incidents in educational institutions are as follows:
🔒 Lack of a Security Framework: A key challenge in cybersecurity for educational institutions is the lack of a dedicated framework for higher education. Existing frameworks like ISO 27001, NIST, COBIT, and ITIL are designed for commercial organizations and are often difficult and costly to implement. Consequently, many educational institutions in India do not have a clearly defined cybersecurity framework.
🔑 Diverse User Accounts: Educational institutions manage numerous accounts for staff, students, alumni, and third-party contractors, with high user turnover. The continuous influx of new users makes maintaining account security a challenge, requiring effective systems and comprehensive security training for all users.
📚 Limited Awareness: Cybersecurity awareness among students, parents, teachers, and staff in educational institutions is limited due to the recent and rapid integration of technology. The surge in tech use, accelerated by the pandemic, has outpaced stakeholders' ability to address cybersecurity issues, leaving them unprepared to manage or train others on these challenges.
📱 Increased Use of Personal/Shared Devices: The growing reliance on unvetted personal/Shared devices for academic and administrative activities amplifies security risks.
💬 Lack of Incident Reporting: Educational institutions often neglect reporting cyber incidents, increasing vulnerability to future attacks. It is essential to report all cases, from minor to severe, to strengthen cybersecurity and institutional resilience.
Impact of Cybersecurity Attacks on Educational Institutions
Cybersecurity attacks on educational institutions lead to learning disruptions, financial losses, and data breaches. They also harm the institution's reputation and pose security risks to students. The following are the impacts of cybersecurity attacks on educational institutions:
📚Impact on the Learning Process: A report by the US Government Accountability Office (GAO) found that cyberattacks on school districts resulted in learning losses ranging from three days to three weeks, with recovery times taking between two to nine months.
💸Financial Loss: US schools reported financial losses ranging from $50,000 to $1 million due to expenses like hardware replacement and cybersecurity upgrades, with recovery taking an average of 2 to 9 months.
🔒Data Security Breaches: Cyberattacks exposed sensitive data, including grades, social security numbers, and bullying reports. Accidental breaches were often caused by staff, accounting for 21 out of 25 cases, while intentional breaches by students, comprising 27 out of 52 cases, frequently involved tampering with grades.
⚠️Data Security Breach: Cyberattacks on schools result in breaches of personal information, including grades and social security numbers, causing emotional, physical, and financial harm. These breaches can be intentional or accidental, with a US study showing staff responsible for most accidental breaches (21 out of 25) and students primarily behind intentional breaches (27 out of 52) to change grades.
🏫Impact on Institutional Reputation: Cyberattacks damaged the reputation of educational institutions, eroding trust among students, staff, and families. Negative media coverage and scrutiny impacted staff retention, student admissions, and overall credibility.
🛡️ Impact on Student Safety: Cyberattacks compromised student safety and privacy. For example, breaches like live-streaming school CCTV footage caused severe distress, negatively impacting students' sense of security and mental well-being.
CyberPeace Advisory:
CyberPeace emphasizes the importance of vigilance and proactive measures to address cybersecurity risks:
Develop effective incident response plans: Establish a clear and structured plan to quickly identify, respond to, and recover from cyber threats. Ensure that staff are well-trained and know their roles during an attack to minimize disruption and prevent further damage.
Implement access controls with role-based permissions: Restrict access to sensitive information based on individual roles within the institution. This ensures that only authorized personnel can access certain data, reducing the risk of unauthorized access or data breaches.
Regularly update software and conduct cybersecurity training: Keep all software and systems up-to-date with the latest security patches to close vulnerabilities. Provide ongoing cybersecurity awareness training for students and staff to equip them with the knowledge to prevent attacks, such as phishing.
Ensure regular and secure backups of critical data: Perform regular backups of essential data and store them securely in case of cyber incidents like ransomware. This ensures that, if data is compromised, it can be restored quickly, minimizing downtime.
Adopt multi-factor authentication (MFA): Enforce Multi-Factor Authentication(MFA) for accessing sensitive systems or information to strengthen security. MFA adds an extra layer of protection by requiring users to verify their identity through more than one method, such as a password and a one-time code.
Deploy anti-malware tools: Use advanced anti-malware software to detect, block, and remove malicious programs. This helps protect institutional systems from viruses, ransomware, and other forms of malware that can compromise data security.
Monitor networks using intrusion detection systems (IDS): Implement IDS to monitor network traffic and detect suspicious activity. By identifying threats in real time, institutions can respond quickly to prevent breaches and minimize potential damage.
Conduct penetration testing: Regularly conduct penetration testing to simulate cyberattacks and assess the security of institutional networks. This proactive approach helps identify vulnerabilities before they can be exploited by actual attackers.
Collaborate with cybersecurity firms: Partner with cybersecurity experts to benefit from specialized knowledge and advanced security solutions. Collaboration provides access to the latest technologies, threat intelligence, and best practices to enhance the institution's overall cybersecurity posture.
Share best practices across institutions: Create forums for collaboration among educational institutions to exchange knowledge and strategies for cybersecurity. Sharing successful practices helps build a collective defense against common threats and improves security across the education sector.
Conclusion:
The increasing cyber threats to Indian educational institutions demand immediate attention and action. With vulnerabilities like data breaches, botnet activities, and outdated infrastructure, institutions must prioritize effective cybersecurity measures. By adopting proactive strategies such as regular software updates, multi-factor authentication, and incident response plans, educational institutions can mitigate risks and safeguard sensitive data. Collaborative efforts, awareness, and investment in cybersecurity will be essential to creating a secure digital environment for academia.
The 2023-24 annual report of the Union Home Ministry states that WhatsApp is among the primary platforms being targeted for cyber fraud in India, followed by Telegram and Instagram. Cybercriminals have been conducting frauds like lending and investment scams, digital arrests, romance scams, job scams, online phishing etc., through these platforms, creating trauma for victims and overburdening law enforcement, which is not always the best equipped to recover their money. WhatsApp’s scale, end-to-end encryption, and ease of mass messaging make it both a powerful medium of communication and a vulnerable target for bad actors. It has over 500 million users in India, which makes it a primary subject for scammers running illegal lending apps, phishing schemes, and identity fraud.
Action Taken by Whatsapp
As a response to this worrying trend and in keeping with Rule 4(1)(d) of the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, [updated as of 6.4.2023], WhatsApp has been banning millions of Indian accounts through automated tools, AI-based detection systems, and behaviour analysis, which can detect suspicious activity and misuse. In July 2021, it banned over 2 million accounts. By February 2025, this number had shot up to over 9.7 million, with 1.4 million accounts removed proactively, that is, before any user reported them. While this may mean that the number of attacks has increased, or WhatsApp’s detection systems have improved, or both, what it surely signals is the acknowledgement of a deeper, systemic challenge to India’s digital ecosystem and the growing scale and sophistication of cyber fraud, especially on encrypted platforms.
CyberPeace Insights
Under Rule 4(1)(d) of the IT Rules, 2021, significant social media intermediaries (SSMIs) are required to implement automated tools to detect harmful content. But enforcement has been uneven. WhatsApp’s enforcement action demonstrates what effective compliance with proactive moderation can look like because of the scale and transparency of its actions.
Platforms must treat fraud not just as a content violation but as a systemic abuse of the platform’s infrastructure.
India is not alone in facing this challenge. The EU’s Digital Services Act (DSA), for instance, mandates large platforms to conduct regular risk assessments, maintain algorithmic transparency, and allow independent audits of their safety mechanisms. These steps go beyond just removing bad content by addressing the design of the platform itself. India can draw from this by codifying a baseline standard for fraud detection, requiring platforms to publish detailed transparency reports, and clarifying the legal expectations around proactive monitoring. Importantly, regulators must ensure this is done without compromising encryption or user privacy.
WhatsApp’s efforts are part of a broader, emerging ecosystem of threat detection. The Indian Cyber Crime Coordination Centre (I4C) is now sharing threat intelligence with platforms like Google and Meta to help take down scam domains, malicious apps, and sponsored Facebook ads promoting illegal digital lending. This model of public-private intelligence collaboration should be institutionalized and scaled across sectors.
Conclusion: Turning Enforcement into Policy
WhatsApp’s mass account ban is not just about enforcement but an example of how platforms must evolve. As India becomes increasingly digital, it needs a forward-looking policy framework that supports proactive monitoring, ethical AI use, cross-platform coordination, and user safety. The digital safety of users in India and those around the world must be built into the architecture of the internet.
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