MeitY’s Efforts in Combatting Deepfakes

Introduction

Generative AI models are significant consumers of computational resources and energy required for training and running models. While AI is being hailed as a game-changer, however underneath the shiny exterior, cracks are present which significantly raises concerns for its environmental impact. The development, maintenance, and disposal of AI technology all come with a large carbon footprint. The energy consumption of AI models, particularly large-scale models or image generation systems, these models rely on data centers powered by electricity, often from non-renewable sources, which exacerbates environmental concerns and contributes to substantial carbon emissions.

As AI adoption grows, improving energy efficiency becomes essential. Optimising algorithms, reducing model complexity, and using more efficient hardware can lower the energy footprint of AI systems. Additionally, transitioning to renewable energy sources for data centers can help mitigate their environmental impact. There is a growing need for sustainable AI development, where environmental considerations are integral to model design and deployment.

A breakdown of how generative AI contributes to environmental risks and the pressing need for energy efficiency:

• Gen AI during the training phase has high power consumption, when vast amounts of computational power which is often utilising extensive GPU clusters for weeks or at times even months, consumes a substantial amount of electricity. Post this phase, the inference phase where the deployment of these models takes place for real-time inference, can be energy-extensive especially when we take into account the millions of users of Gen AI.
• The main source of energy used for training and deploying AI models often comes from non-renewable sources which then contribute to the carbon footprint. The data centers where the computations for Gen AI take place are a significant source of carbon emissions if they rely on the use of fossil fuels for their energy needs for the training and deployment of the models. According to a study by MIT, training an AI can produce emissions that are equivalent to around 300 round-trip flights between New York and San Francisco. According to a report by Goldman Sachs, Data Companies will use 8% of US power by 2030, compared to 3% in 2022 as their energy demand grows by 160%.
• The production and disposal of hardware (GPUs, servers) necessary for AI contribute to environmental degradation. Mining for raw materials and disposing of electronic waste (e-waste) are additional environmental concerns. E-waste contains hazardous chemicals, including lead, mercury, and cadmium, that can contaminate soil and water supplies and endanger both human health and the environment. 

Efforts by the Industry to reduce the environmental risk posed by Gen AI 

There are a few examples of how companies are making efforts to reduce their carbon footprint, reduce energy consumption and overall be more environmentally friendly in the long run. Some of the efforts are as under:

• Google's TPUs in particular the Google Tensor are designed specifically for machine learning tasks and offer a higher performance-per-watt ratio compared to traditional GPUs, leading to more efficient AI computations during the shorter periods requiring peak consumption. 
• Researchers at Microsoft, for instance, have developed a so-called “1 bit” architecture that can make LLMs 10 times more energy efficient than the current leading system. This system simplifies the models’ calculations by reducing the values to 0 or 1, slashing power consumption but without sacrificing its performance.
• OpenAI has been working on optimizing the efficiency of its models and exploring ways to reduce the environmental impact of AI and using renewable energy as much as possible including the research into more efficient training methods and model architectures.

Policy Recommendations

We advocate for the sustainable product development process and press the need for Energy Efficiency in AI Models to counter the environmental impact that they have. These improvements would not only be better for the environment but also contribute to the greater and sustainable development of Gen AI.  Some suggestions are as follows:

• AI needs to adopt a Climate justice framework which has been informed by a diverse context and perspectives while working in tandem with the UN’s (Sustainable Development Goals) SDGs.
• Working and developing more efficient algorithms that would require less computational power for both training and inference can reduce energy consumption. Designing more energy-efficient hardware, such as specialized AI accelerators and next-generation GPUs, can help mitigate the environmental impact. 
• Transitioning to renewable energy sources (solar, wind, hydro) can significantly reduce the carbon footprint associated with AI. The World Economic Forum (WEF) projects that by 2050, the total amount of e-waste generated will have surpassed 120 million metric tonnes.
• Employing techniques like model compression, which reduces the size of AI models without sacrificing performance, can lead to less energy-intensive computations. Optimized models are faster and require less hardware, thus consuming less energy.
• Implementing scattered learning approaches, where models are trained across decentralized devices rather than centralized data centers, can lead to a better distribution of energy load evenly and reduce the overall environmental impact.
• Enhancing the energy efficiency of data centers through better cooling systems, improved energy management practices, and the use of AI for optimizing data center operations can contribute to reduced energy consumption.

Final Words

The UN Sustainable Development Goals (SDGs) are crucial for the AI industry just as other industries as they guide responsible innovation. Aligning AI development with the SDGs will ensure ethical practices, promoting sustainability, equity, and inclusivity. This alignment fosters global trust in AI technologies, encourages investment, and drives solutions to pressing global challenges, such as poverty, education, and climate change, ultimately creating a positive impact on society and the environment. The current state of AI is that it is essentially utilizing enormous power and producing a product not efficiently utilizing the power it gets. AI and its derivatives are stressing the environment in such a manner which if it continues will affect the clean water resources and other non-renewable power generation sources which contributed to the huge carbon footprint of the AI industry as a whole.  

References

• https://cio.economictimes.indiatimes.com/news/artificial-intelligence/ais-hunger-for-power-can-be-tamed/111302991
• https://earth.org/the-green-dilemma-can-ai-fulfil-its-potential-without-harming-the-environment/ 
• https://www.technologyreview.com/2019/06/06/239031/training-a-single-ai-model-can-emit-as-much-carbon-as-five-cars-in-their-lifetimes/
• https://www.scientificamerican.com/article/ais-climate-impact-goes-beyond-its-emissions/ ‍
• https://insights.grcglobalgroup.com/the-environmental-impact-of-ai/

Introduction

Sexual Offences against children have recently come under scrutiny after the decision of the Madras High Court which has ruled that watching and downloading child sexual porn is an inchoate crime. In response, the Supreme Court, on 23 September 2024, ruled that Section 15 of the POCSO and Section 67B of the IT Act penalise any form of use of child pornography, including storing and watching such pornographic content. Along with this, the Supreme Court has further recommended replacing the term “Child Pornography” which it said acts as a misnomer and does not capture the full extent of the crime, with a more inclusive term “Child Sexual Exploitative and Abuse Material” (CESAM). This term would more accurately reflect the reality that these images and videos are not merely pornographic but are records of incidents, where a child has either been sexually exploited and abused or where any abuse of children has been portrayed through any self-generated visual depiction.

Intermediaries cannot claim exemption from Liability U/S 79 

Previously, intermediaries claimed safe harbour by only complying with the requirements stipulated under the  MOU. As per the decision of the SC, now, an intermediary cannot claim exemption from the liability under Section 79 of the IT Act for any third-party information, data, or communication link made available or hosted by it unless due diligence is conducted by it and compliance is made of these provisions of the POCSO Act. This is as per the provisions of Sections 19 and 20 of the POCSO read with Rule 11 of the POCSO Rules which have a mandatory nature.

The due diligence under section 79 of the IT Act includes the removal of child pornographic content and immediate reporting of such content to the concerned police units in the manner specified under the POCSO Act and the Rules. In this way, the Supreme Court has broadened the Interpretation and scope of the ‘Due Diligence’ obligation under section 79 of the IT Act. It was also stated that is to be duly noted that merely because an intermediary complies with the IT Act, will not absolve it of any liability under the POCSO. This is unless it duly complies with the requirements and procedure set out under it, particularly Section 20 of the POCSO Act and Rule 11 of the POCSO Rules.

Bar on Judicial Use of the term ‘Child Porn’

Supreme Court found that the term child pornography can be trivialised as pornography is often seen as a consensual act between adults. Supreme Court emphasised using the term Child Sexual Exploitative and Abuse Material  (CESAM) as it would emphasise the exploitation of children highlight the criminality of the act and shift the focus to a more robust framework to counter these crimes. The Supreme Court also stated that the Union of India should consider amending the POCSO Act to replace the "child pornography" term with "child sexual exploitative and abuse material" (CSEAM). This would reflect more accurately on the reality of such offences. Supreme Court also directed that the term "child pornography" shall not be used in any judicial order or judgment, and instead, the term "CSEAM" should be endorsed.

Curbing CSEAM Content on Social Media Platforms

Social Media Intermediaries and Expert Organisations play an important role in curbing CESAM content. Per the directions of the Apex Court, a need to impart positive age-appropriate sex education to prevent youth from engaging in harmful sexual behaviours, including the distribution, and viewing of CSEAM is important and all stakeholders must engage in proactive measures to counter these offences which are under the umbrella of CSEAM. This should entail promoting age-appropriated and lawful content on social media platforms and social media platforms to ensure compliance with applicable provisions.  

Conclusion 

In light of the Supreme Court’s landmark ruling, it is imperative to acknowledge the pressing necessity of establishing a safer online environment that shields children from exploitation. The shift towards using "Child Sexual Exploitative and Abuse Material" (CSEAM) emphasizes the severity of the crime and the need for a vigilant response. The social media intermediaries must respect their commitment to report and remove exploitive content and must ensure compliance with POCSO and IT regulations. Furthermore, comprehensive, age-appropriate sex education can also be used as a preventive measure, educating young people about the moral and legal ramifications of sexual offences, encouraging respect and awareness and ensuring safer cyberspace. 

References

• https://www.scconline.com/blog/post/2024/09/23/storing-watching-child-pornography-crime-supreme-court-pocso-it-act/#:~:text=Supreme%20Court%3A%20The%20bench%20of,watching%20of%20such%20pornographic%20content
• https://timesofindia.indiatimes.com/india/supreme-court-viewing-child-porn-is-offence-under-pocso-it-acts/articleshow/113613572.cms
• https://bwlegalworld.com/article/dont-use-term-child-pornography-says-sc-urges-parliament-to-amend-pocso-act-534053  
• https://indianexpress.com/article/india/child-pornography-law-pocso-it-supreme-court-9583376/

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Disclaimer:

This report is based on extensive research conducted by CyberPeace Research using publicly available information, and advanced analytical techniques. The findings, interpretations, and conclusions presented are based on the data available at the time of study and aim to provide insights into global ransomware trends.

The statistics mentioned in this report are specific to the scope of this research and may vary based on the scope and resources of other third-party studies. Additionally, all data referenced is based on claims made by threat actors and does not imply confirmation of the breach by CyberPeace. CyberPeace includes this detail solely to provide factual transparency and does not condone any unlawful activities. This information is shared only for research purposes and to spread awareness. CyberPeace encourages individuals and organizations to adopt proactive cybersecurity measures to protect against potential threats.

CyberPeace Research does not claim to have identified or attributed specific cyber incidents to any individual, organization, or nation-state beyond the scope of publicly observable activities and available information. All analyses and references are intended for informational and awareness purposes only, without any intention to defame, accuse, or harm any entity.

While every effort has been made to ensure accuracy, CyberPeace Research is not liable for any errors, omissions, subsequent interpretations and any unlawful activities of the findings by third parties. The report is intended to inform and support cybersecurity efforts globally and should be used as a guide to foster proactive measures against cyber threats.

Executive Summary: 

The 2024 ransomware landscape reveals alarming global trends, with 166 Threat Actor Groups leveraging 658 servers/underground resources and mirrors to execute 5,233 claims across 153 countries. Monthly fluctuations in activity indicate strategic, cyclical targeting, with peak periods aligned with vulnerabilities in specific sectors and regions. The United States was the most targeted nation, followed by Canada, the UK, Germany, and other developed countries, with the northwestern hemisphere experiencing the highest concentration of attacks. Business Services and Healthcare bore the brunt of these operations due to their high-value data, alongside targeted industries such as Pharmaceuticals, Mechanical, Metal, Electronics, and Government-related professional firms. Retail, Financial, Technology, and Energy sectors were also significantly impacted.

This research was conducted by CyberPeace Research using a systematic modus operandi, which included advanced OSINT (Open-Source Intelligence) techniques, continuous monitoring of Ransomware Group activities, and data collection from 658 servers and mirrors globally. The team utilized data scraping, pattern analysis, and incident mapping to track trends and identify hotspots of ransomware activity. By integrating real-time data and geographic claims, the research provided a comprehensive view of sectoral and regional impacts, forming the basis for actionable insights.

The findings emphasize the urgent need for proactive Cybersecurity strategies, robust defenses, and global collaboration to counteract the evolving and persistent threats posed by ransomware.

Overview:

This report provides insights into ransomware activities monitored throughout 2024. Data was collected by observing 166 Threat Actor Groups using ransomware technologies across 658 servers/underground resources and mirrors, resulting in 5,233 claims worldwide. The analysis offers a detailed examination of global trends, targeted sectors, and geographical impact.

Top 10 Threat Actor Groups:

The ransomware group ‘ransomhub’ has emerged as the leading threat actor, responsible for 527 incidents worldwide. Following closely are ‘lockbit3’ with 522 incidents and ‘play’ with 351. Other Groups are ‘akira’, ‘hunters’, ‘medusa’, ‘blackbasta’, ‘qilin’, ‘bianlian’, ‘incransom’. These groups usually employ advanced tactics to target critical sectors, highlighting the urgent need for robust cybersecurity measures to mitigate their impact and protect organizations from such threats.

Monthly Ransomware Incidents:

In January 2024, the value began at 284, marking the lowest point on the chart. The trend rose steadily in the subsequent months, reaching its first peak at 557 in May 2024. However, after this peak, the value dropped sharply to 339 in June. A gradual recovery follows, with the value increasing to 446 by August. September sees another decline to 389, but a sharp rise occurs afterward, culminating in the year’s highest point of 645 in November. The year concludes with a slight decline, ending at 498 in December 2024 (till 28th of December).

Top 10 Targeted Countries:

1. The United States consistently topped the list as the primary target probably due to its advanced economic and technological infrastructure.
2. Other heavily targeted nations include Canada, UK, Germany, Italy, France, Brazil, Spain, and India.
3. A total of 153 countries reported ransomware attacks, reflecting the global scale of these cyber threats

Top Affected Sectors:

1. Business Services and Healthcare faced the brunt of ransomware threat due to the sensitive nature of their operations.
2. Specific industries under threats:
   1. Pharmaceutical, Mechanical, Metal, and Electronics industries.
   2. Professional firms within the Government sector.
3. Other sectors:
   1. Retail, Financial, Technology, and Energy sectors were also significant targets.

Geographical Impact:

The continuous and precise OSINT(Open Source Intelligence) work on the platform, performed as a follow-up action to data scraping, allows a complete view of the geography of cyber attacks based on their claims. The northwestern region of the world appears to be the most severely affected by Threat Actor groups. The figure below clearly illustrates the effects of this geographic representation on the map.

Ransomware Threat Trends in India:

In 2024, the research identified 98 ransomware incidents impacting various sectors in India, marking a 55% increase compared to the 63 incidents reported in 2023. This surge highlights a concerning trend, as ransomware groups continue to target India's critical sectors due to its growing digital infrastructure and economic prominence.

Top Threat Actors Group Targeted India:

Among the following threat actors ‘killsec’ is the most frequent threat. ‘lockbit3’  follows as the second most prominent threat, with significant but lower activity than killsec. Other groups, such as ‘ransomhub’, ‘darkvault’, and ‘clop’, show moderate activity levels. Entities like ‘bianlian’, ‘apt73/bashe’, and ‘raworld’ have low frequencies, indicating limited activity. Groups such as ‘aps’ and ‘akira’ have the lowest representation, indicating minimal activity. The chart highlights a clear disparity in activity levels among these threats, emphasizing the need for targeted cybersecurity strategies.

Top Impacted Sectors in India:

The pie chart illustrates the distribution of incidents across various sectors, highlighting that the industrial sector is the most frequently targeted, accounting for 75% of the total incidents. This is followed by the healthcare sector, which represents 12% of the incidents, making it the second most affected. The finance sector accounts for 10% of the incidents, reflecting a moderate level of targeting. In contrast, the government sector experiences the least impact, with only 3% of the incidents, indicating minimal targeting compared to the other sectors. This distribution underscores the critical need for enhanced cybersecurity measures, particularly in the industrial sector, while also addressing vulnerabilities in healthcare, finance, and government domains.

Month Wise Incident Trends in India:

The chart indicates a fluctuating trend with notable peaks in May and October, suggesting potential periods of heightened activity or incidents during these months. The data starts at 5 in January and drops to its lowest point, 2, in February. It then gradually increases to 6 in March and April, followed by a sharp rise to 14 in May. After peaking in May, the metric significantly declines to 4 in June but starts to rise again, reaching 7 in July and 8 in August. September sees a slight dip to 5 before the metric spikes dramatically to its highest value, 24, in October. Following this peak, the count decreases to 10 in November and then drops further to 7 in December.

CyberPeace Advisory:

1. Implement Data Backup and Recovery Plans: Backups are your safety net. Regularly saving copies of your important data ensures you can bounce back quickly if ransomware strikes. Make sure these backups are stored securely—either offline or in a trusted cloud service—to avoid losing valuable information or facing extended downtime.  
2. Enhance Employee Awareness and Training: People often unintentionally open the door to ransomware. By training your team to spot phishing emails, social engineering tricks, and other scams, you empower them to be your first line of defense against attacks.  
3. Adopt Multi-Factor Authentication (MFA): Think of MFA as locking your door and adding a deadbolt. Even if attackers get hold of your password, they’ll still need that second layer of verification to break in. It’s an easy and powerful way to block unauthorized access.  
4. Utilize Advanced Threat Detection Tools: Smart tools can make a world of difference. AI-powered systems and behavior-based monitoring can catch ransomware activity early, giving you a chance to stop it in its tracks before it causes real damage.  
5. Conduct Regular Vulnerability Assessments: You can’t fix what you don’t know is broken. Regularly checking for vulnerabilities in your systems helps you identify weak spots. By addressing these issues proactively, you can stay one step ahead of attackers.

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Conclusion:

The 2024 ransomware landscape reveals the critical need for proactive cybersecurity strategies. High-value sectors and technologically advanced regions remain the primary targets, emphasizing the importance of robust defenses. As we move into 2025, it is crucial to anticipate the evolution of ransomware tactics and adopt forward-looking measures to address emerging threats. 

Global collaboration, continuous innovation in cybersecurity technologies, and adaptive strategies will be imperative to counteract the persistent and evolving threats posed by ransomware activities. Organizations and governments must prioritize preparedness and resilience, ensuring that lessons learned in 2024 are applied to strengthen defenses and minimize vulnerabilities in the year ahead.

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