Unravelling AI-Generated Misinformation in the 'Delhi Chalo' Farmers' Protest

Introduction

The fast-paced development of technology and the wider use of social media platforms have led to the rapid dissemination of misinformation with characteristics such as diffusion, fast propagation speed, wide influence, and deep impact through these platforms. Social Media Algorithms and their decisions are often perceived as a black box introduction that makes it impossible for users to understand and recognise how the decision-making process works. 

Social media algorithms may unintentionally promote false narratives that garner more interactions, further reinforcing the misinformation cycle and making it harder to control its spread within vast, interconnected networks. Algorithms judge the content based on the metrics, which is user engagement. It is the prerequisite for algorithms to serve you the best. Hence, algorithms or search engines enlist relevant items you are more likely to enjoy. This process, initially, was created to cut the clutter and provide you with the best information. However, sometimes it results in unknowingly widespread misinformation due to the viral nature of information and user interactions. 

Analysing the Algorithmic Architecture of Misinformation

Social media algorithms, designed to maximize user engagement, can inadvertently promote misinformation due to their tendency to trigger strong emotions, creating echo chambers and filter bubbles. These algorithms prioritize content based on user behaviour, leading to the promotion of emotionally charged misinformation. Additionally, the algorithms prioritize content that has the potential to go viral, which can lead to the spread of false or misleading content faster than corrections or factual content.

Additionally, popular content is amplified by platforms, which spreads it faster by presenting it to more users. Limited fact-checking efforts are particularly difficult since, by the time they are reported or corrected, erroneous claims may have gained widespread acceptance due to delayed responses. Social media algorithms find it difficult to distinguish between real people and organized networks of troll farms or bots that propagate false information. This creates a vicious loop where users are constantly exposed to inaccurate or misleading material, which strengthens their convictions and disseminates erroneous information through networks.

Though algorithms, primarily, aim to enhance user engagement by curating content that aligns with the user's previous behaviour and preferences. Sometimes this process leads to "echo chambers," where individuals are exposed mainly to information that reaffirms their beliefs which existed prior, effectively silencing dissenting voices and opposing viewpoints. This curated experience reduces exposure to diverse opinions and amplifies biased and polarising content, making it arduous for users to discern credible information from misinformation. Algorithms feed into a feedback loop that continuously gathers data from users' activities across digital platforms, including websites, social media, and apps. This data is analysed to optimise user experiences, making platforms more attractive. While this process drives innovation and improves user satisfaction from a business standpoint, it also poses a danger in the context of misinformation. The repetitive reinforcement of user preferences leads to the entrenchment of false beliefs, as users are less likely to encounter fact-checks or corrective information.

Moreover, social networks and their sheer size and complexity today exacerbate the issue. With billions of users participating in online spaces, misinformation spreads rapidly, and attempting to contain it—such as by inspecting messages or URLs for false information—can be computationally challenging and inefficient. The extensive amount of content that is shared daily means that misinformation can be propagated far quicker than it can get fact-checked or debunked.

Understanding how algorithms influence user behaviour is important to tackling misinformation. The personalisation of content, feedback loops, the complexity of network structures, and the role of superspreaders all work together to create a challenging environment where misinformation thrives. Hence, highlighting the importance of countering misinformation through robust measures. 

The Role of Regulations in Curbing Algorithmic Misinformation

The EU's Digital Services Act (DSA) applicable in the EU is one of the regulations that aims to increase the responsibilities of tech companies and ensure that their algorithms do not promote harmful content. These regulatory frameworks play an important role they can be used to establish mechanisms for users to appeal against the algorithmic decisions and ensure that these systems do not disproportionately suppress legitimate voices. Independent oversight and periodic audits can ensure that algorithms are not biased or used maliciously. Self-regulation and Platform regulation are the first steps that can be taken to regulate misinformation. By fostering a more transparent and accountable ecosystem, regulations help mitigate the negative effects of algorithmic misinformation, thereby protecting the integrity of information that is shared online. In the Indian context, the Intermediary Guidelines, 2023, Rule 3(1)(b)(v) explicitly prohibits the dissemination of misinformation on digital platforms. The ‘Intermediaries’ are obliged to ensure reasonable efforts to prevent users from hosting, displaying, uploading, modifying, publishing, transmitting, storing, updating, or sharing any information related to the 11 listed user harms or prohibited content. This rule aims to ensure platforms identify and swiftly remove misinformation, and false or misleading content.

Cyberpeace Outlook

Understanding how algorithms prioritise content will enable users to critically evaluate the information they encounter and recognise potential biases. Such cognitive defenses can empower individuals to question the sources of the information and report misleading content effectively. In the future of algorithms in information moderation, platforms should evolve toward more transparent, user-driven systems where algorithms are optimised not just for engagement but for accuracy and fairness. Incorporating advanced AI moderation tools, coupled with human oversight can improve the detection and reduction of harmful and misleading content. Collaboration between regulatory bodies, tech companies, and users will help shape the algorithms landscape to promote a healthier, more informed digital environment.

References:

• https://www.advancedsciencenews.com/misformation-spreads-like-a-nuclear-reaction-on-the-internet/
• https://www.niemanlab.org/2024/09/want-to-fight-misinformation-teach-people-how-algorithms-work/ 
• Press Release: Press Information Bureau (pib.gov.in) 

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Overview:

WazirX is the platform for cryptocurrencies, based in India that has been hacked, and it made a loss of more than $230 million in cryptocurrency. This case concerned an unauthorized transaction with a multisignature or multisig, wallet controlled through Liminal’a digital asset management platform. These attacking incidents have thereafter raised more questions on the security of the Cryptocurrency exchanges and efficiency of the existing policies and laws.

Wallet Configuration and Security Measures

This wallet was breached and had a multisig setting meaning that more than one signature was needed to authorize a transaction. Specifically, it had six signatories: five are funded by WazirX and one is funded by Liminal. Every transaction needed the approval of at least three signatories of WazirX, all of whom had addressed security concerns by using Ledger’s hardware wallets; while the Liminal, too, had a signatory, for approval.

To further increase the level of security of the transactions, a whitelisting policy was introduced, only limited addresses were authorized to receive funds. This system was rather vulnerable, and the attackers managed to grasp the discrepancy between the information available through Liminal’s interface and the content of the transaction to seize unauthorized control over the wallet and implement the theft.

Modus Operandi: Attack Mechanics

The cyber attack appears to have been carefully carried out, with preliminary investigations suggesting the following tactics: 

• Payload Manipulation: The attackers apparently substituted the transaction’s payload during signing; hence, they can reroute the collected funds into an unrelated wallet. 

• Chain Hopping: To make it much harder to track their movements, the attackers split large amounts of money across multiple blockchains and broke tens of thousands of dollars into thousands of transactions involving different cryptocurrencies. This technique makes it difficult to trace people and things. 

• Zero Balance Transactions: There were also some instances where it ended up with no Ethereum (ETH) in the balance and such wallets also in use for the purpose of further anonymization of the transactions.

• Analysis of the blockchain data suggested the enemy might have been making the preparations for this attack for several days prior to their attack and involved a high amount of planning. 

Actions taken by WazirX:

Following the attack, WazirX implemented a series of immediate actions:

• User Notifications: The users were immediately notified of the occurrence of the breach and the possible risk it posed to them. 

• Law Enforcement Engagement: The matters were reported to the National Cyber Crime Reporting Portal and specific authorities of which the Financial Intelligence Unit (FIU) and the Computer Emergency Response Team (CERT-In). 

• Service Suspension: WazirX had suspended all its trading operations and user deposits’ and withdrawals’ to minimize further cases and investigate. 

• Global Outreach: The exchange contacted more than 500 cryptocurrency exchanges and requested to blacklist the wallet’s addresses linked to the theft. 

• Bounty Program: A bounty program was announced to encourage people to share information that can enable the authorities to retrieve the stolen money. A maximum of 23 million dollars was placed on the bounty. 

Further  Investigations 

WazirX stated that it has contracted the services of cybersecurity professionals to help in the prosecution process of identifying and compensating for the losses. The exchange is still investigating the forensic data and working with the police for tracking the stolen assets. Nevertheless, the prospects of full recovery may be quite questionable primarily because of complexity of the attack and the methods used by the attackers. 

Precautionary measures: 

 The WazirX cyber attack clearly implies that there is the necessity to improve the security and the regulation of the cryptocurrency industry. As exchanges become increasingly targeted by hackers, there is a pressing need for: 

• Stricter Security Protocols: The commitment to technical innovations, such as integration of MFA, as well as constant monitoring of the users’ wallets’ activities. 

• Regulatory Oversight: Formalization of the laws that require proper security for the cryptocurrency exchange platforms to safeguard their users as well as their investments. 

• Community Awareness: To bypass such predicaments, there is a need to study on emergent techniques in spreading awareness, particularly in cases of scams or phishing attempts that are likely to follow such breaches. 

Conclusion:

The cyber attack on WazirX in the field of cryptocurrency market, shows weaknesses and provides valuable lessons for enhancing the security.  This attack highlights critical vulnerabilities in cryptocurrency exchanges, even though employing advanced security measures like multisignature wallets and whitelisting policies. The attack's complexity, involving payload manipulation, chain hopping, and zero balance transactions, underscores the attackers' meticulous planning and the challenges in tracing stolen assets. This case brings a strong message regarding the necessity of solid security measures, and constant attention to security in the rapidly growing world of digital assets. Furthermore, the incident highlights the importance of community awareness and education on emerging threats like scams and phishing attempts, which usually follow such breaches. By fostering a culture of vigilance and knowledge, the cryptocurrency community can better defend against future attacks.

Reference:

https://wazirx.com/blog/important-update-cyber-attack-incident-and-measures-to-protect-your-assets/

https://www.moneycontrol.com/news/opinion/the-230-million-crypto-theft-at-wazirx-is-a-wake-up-call-for-indian-regulators-government-12772563.html

https://www.linkedin.com/pulse/wazirx-cyberattack-in-depth-analysis-jyqxf

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What are Deepfakes? 

A deepfake is essentially a video of a person in which their face or body has been digitally altered so that they appear to be someone else, typically used maliciously or to spread false information. Deepfake technology is a method for manipulating videos, images, and audio utilising powerful computers and deep learning. It is used to generate fake news and commit financial fraud, among other wrongdoings. It overlays a digital composite over an already-existing video, picture, or audio; cybercriminals use Artificial Intelligence technology. The term deepfake was coined first time in 2017 by an anonymous Reddit user, who called himself deepfake. 

Deepfakes works on a combination of AI and ML, which makes the technology hard to detect by Web 2.0 applications, and it is almost impossible for a layman to see if an image or video is fake or has been created using deepfakes. In recent times, we have seen a wave of AI-driven tools which have impacted all industries and professions across the globe. Deepfakes are often created to spread misinformation. There lies a key difference between image morphing and deepfakes. Image morphing is primarily used for evading facial recognition, but deepfakes are created to spread misinformation and propaganda. 

Issues Pertaining to Deepfakes in India 

Deepfakes are a threat to any nation as the impact can be divesting in terms of monetary losses, social and cultural unrest, and actions against the sovereignty of India by anti-national elements. Deepfake detection is difficult but not impossible. The following threats/issues are seen to be originating out of deep fakes: 

• Misinformation: One of the biggest issues of Deepfake is misinformation, the same was seen during the Russia-Ukraine conflict, where in a deepfake of Ukraine’s president, Mr Zelensky, surfaced on the internet and caused mass confusion and propaganda-based misappropriation among the Ukrainians. 
• Instigation against the Union of India: Deepfake poses a massive threat to the integrity of the Union of India, as this is one of the easiest ways for anti-national elements to propagate violence or instigate people against the nation and its interests. As India grows, so do the possibilities of anti-national attacks against the nation. 
• Cyberbullying/ Harassment: Deepfakes can be used by bad actors to harass and bully people online in order to extort money from them. 
• Exposure to Illicit Content: Deepfakes can be easily used to create illicit content, and oftentimes, it is seen that it is being circulated on online gaming platforms where children engage the most. 
• Threat to Digital Privacy: Deepfakes are created by using existing videos. Hence, bad actors often use photos and videos from Social media accounts to create deepfakes, this directly poses a threat to the digital privacy of a netizen.  
• Lack of Grievance Redressal Mechanism: In the contemporary world, the majority of nations lack a concrete policy to address the aspects of deepfake. Hence, it is of paramount importance to establish legal and industry-based grievance redressal mechanisms for the victims. 
• Lack of Digital Literacy: Despite of high internet and technology penetration rates in India, digital literacy lags behind, this is a massive concern for the Indian netizens as it takes them far from understanding the tech, which results in the under-reporting of crimes. Large-scale awareness and sensitisation campaigns need to be undertaken in India to address misinformation and the influence of deepfakes. 

How to spot deepfakes? 

Deepfakes look like the original video at first look, but as we progress into the digital world, it is pertinent to establish identifying deepfakes in our digital routine and netiquettes in order to stay protected in the future and to address this issue before it is too late. The following aspects can be kept in mind while differentiating between a real video and a deepfake

• Look for facial expressions and irregularities: Whenever differentiating between an original video and deepfake, always look for changes in facial expressions and irregularities, it can be seen that the facial expressions, such as eye movement and a temporary twitch on the face, are all signs of a video being a deepfake. 
• Listen to the audio: The audio in deepfake also has variations as it is imposed on an existing video, so keep a check on the sound effects coming from a video in congruence with the actions or gestures in the video. 
• Pay attention to the background: The most easiest way to spot a deepfake is to pay attention to the background, in all deepfakes, you can spot irregularities in the background as, in most cases, its created using virtual effects so that all deepfakes will have an element of artificialness in the background. 
• Context and Content: Most of the instances of deepfake have been focused towards creating or spreading misinformation hence, the context and content of any video is an integral part of differentiating between an original video and deepfake. 
• Fact-Checking: As a basic cyber safety and digital hygiene protocol, one should always make sure to fact-check each and every piece of information they come across on social media. As a preventive measure, always make sure to fact-check any information or post sharing it with your known ones.  
• AI Tools: When in doubt, check it out, and never refrain from using Deepfake detection tools like- Sentinel, Intel’s real-time deepfake detector - Fake catcher, We Verify, and Microsoft’s Video Authenticator tool to analyze the videos and combating technology with technology. 

Recent Instance 

A deepfake video of actress Rashmika Mandanna recently went viral on social media, creating quite a stir. The video showed a woman entering an elevator who looked remarkably like Mandanna. However, it was later revealed that the woman in the video was not Mandanna, but rather, her face was superimposed using AI tools. Some social media users were deceived into believing that the woman was indeed Mandanna, while others identified it as an AI-generated deepfake. The original video was actually of a British-Indian girl named Zara Patel, who has a substantial following on Instagram. This incident sparked criticism from social media users towards those who created and shared the video merely for views, and there were calls for strict action against the uploaders. The rapid changes in the digital world pose a threat to personal privacy; hence, caution is advised when sharing personal items on social media​​.

Legal Remedies

Although Deepfake is not recognised by law in India, it is indirectly addressed by Sec. 66 E of the IT Act, which makes it illegal to capture, publish, or transmit someone's image in the media without that person's consent, thus violating their privacy. The maximum penalty for this violation is ₹2 lakh in fines or three years in prison. The DPDP Act's applicability in 2023 means that the creation of deepfakes will directly affect an individual's right to digital privacy and will also violate the IT guidelines under the Intermediary Guidelines, as platforms will be required to exercise caution while disseminating and publishing misinformation through deepfakes. The indirect provisions of the Indian Penal Code, which cover the sale and dissemination of derogatory publications, songs and actions, deception in the delivery of property, cheating and dishonestly influencing the delivery of property, and forgery with the intent to defame, are the only legal remedies available for deepfakes. Deep fakes must be recognized legally due to the growing power of misinformation. The Data Protection Board and the soon-to-be-established fact-checking body must recognize crimes related to deepfakes and provide an efficient system for filing complaints.

Conclusion 

Deepfake is an aftermath of the advancements of Web 3.0 and, hence is just the tip of the iceberg in terms of the issues/threats from emerging technologies. It is pertinent to upskill and educate the netizens about the keen aspects of deepfakes to stay safe in the future. At the same time, developing and developed nations need to create policies and laws to efficiently regulate deepfake and to set up redressal mechanisms for victims and industry. As we move ahead, it is pertinent to address the threats originating out of the emerging techs and, at the same time, create a robust resilience for the same. 

References 

• https://www.drishtiias.com/daily-updates/daily-news-analysis/deepfake-technology
• https://timesofindia.indiatimes.com/gadgets-news/explained-what-are-deepfakes-and-how-to-spot-one/articleshow/90916962.cms
• https://www.unite.ai/best-deepfake-detector-tools-and-techniques/