#FactCheck-AI-Generated Video Falsely Shows Mishandling of Baggage at Indian Airport

Introduction

According to the Finance Ministry's data, the incidence of domestic Unified Payment Interface (UPI) fraud rose by 85% in FY 2023-24 compared to FY 2022-23. Further, as of September of FY 2024-25, 6.32 lakh fraud cases had been already reported, amounting to Rs 485 crore. The data was shared on 25th November 2024, by the Finance Ministry in response to a question in Lok Sabha’s winter session about the fraud in UPI transactions during the past three fiscal years.

Statistics

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UPI Frauds and Government's Countermeasures 

On the query as to measures taken by the government for safe and secure UPI transactions and prevention of fraud in the transactions, the ministry has highlighted the measures as follows: 

• The Reserve Bank of India (RBI) has launched the Central Payment Fraud Information Registry (CPFIR), a web-based tool for reporting payment-related frauds, operational since March 2020, and it requires requiring all Regulated Entities (RE) to report payment-related frauds to the said CPFIR.

• The Government, RBI, and National Payments Corporation of India (NPCI) have implemented various measures to prevent payment-related frauds, including UPI transaction frauds. These include device binding, two-factor authentication through PIN, daily transaction limits, and limits on use cases.
• Further, NPCI offers a fraud monitoring solution for banks, enabling them to alert and decline transactions using AI/ML models. RBI and banks are also promoting awareness through SMS, radio, and publicity on 'cyber-crime prevention'.
• The Ministry of Home Affairs has launched a National Cybercrime Reporting Portal (NCRP) (www.cybercrime.gov.in) and a National Cybercrime Helpline Number 1930 to help citizens report cyber incidents, including financial fraud. Customers can also report fraud on the official websites of their bank or bank branches.
• The Department of Telecommunications has introduced the Digital Intelligence Platform (DIP) and 'Chakshu' facility on the Sanchar Saathi portal, enabling citizens to report suspected fraud messages via call, SMS, or WhatsApp.

Conclusion  

UPI is India's most popular digital payment method.  As of June 2024, there are around 350 million active users of the UPI in India. The Indian Cyber Crime Coordination Centre (I4C) report indicates that ‘Online Financial Fraud’, a cyber crime category under NCRP, is the most prevalent among others. The rise of financial fraud, particularly UPI fraud is cause for alarm, the scammers use sophisticated strategies to deceive victims. It is high time for netizens to exercise caution and care with their personal and financial information, stay aware of common tactics used by fraudsters, and adhere to best security practices for secure transactions and the safe use of UPI services.

References

• https://sansad.in/getFile/loksabhaquestions/annex/183/AU211_sk53e3.pdf?source=pqals

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Introduction:

Welcome to the second edition of our blog on Digital forensics series. In our previous blog we discussed what digital forensics is,  the process followed by the tools, and the subsequent challenges faced in the field. Further, we looked at how the future of Digital Forensics will hold in the current scenario.  Today, we will explore differences between 3 particular similar sounding terms that vary significantly in functionality when implemented: Copying, Cloning and Imaging.

In Digital Forensics, the preservation and analysis of electronic evidence are important for investigations and legal proceedings. Replication of the data and devices is one of the fundamental tasks in this domain, without compromising the integrity of the original evidence. 

Three primary techniques -- copying, cloning, and imaging -- are used for this purpose. Each technique has its own strengths and is applied according to the needs of the investigation.

In this blog, we will examine the differences between copying, cloning and imaging. We will talk about the importance of each technique, their applications and why imaging  is considered the best for forensic investigations.

Copying

Copying means duplicating data or files from one location to another. When one does copying, it implies that one is using standard copy commands. However, when dealing with evidence, it might be hard to use copy only. It is because the standard copy can alter the metadata and change the hidden or deleted data .

 The characteristics of copying include: 

• Speed: copying is simpler and faster,compared to cloning or imaging.
•  Risk: The risk involved in copying is that the metadata might be altered and all the data might be captured.

Cloning

It is the process where the transfer of the entire contents of a hard drive or a storage device is done  on another storage device. This process is known as cloning . This way, the cloning process captures both the active data and the unallocated space and hidden partitions, thus containing the whole structure of the original device. Cloning is generally used at the sector level of the device. Clones can be used as the working copy of a device .

Characteristics of cloning: 

•  bit-for-bit replication: cloning keeps the exact content and the whole structure of the original device. 
• Use cases: cloning is used when it is needed to keep the original device intact for further examination or a legal affair. 
•  Time consuming: Cloning is usually longer in comparison to simple copying since it involves the whole detailed replication. Though it depends on various factors like the size of the storage device, the speed of the devices involved, and the method of cloning.

Imaging:

It is the process of creating a forensic image of a storage device. A forensic image is a replica copy of every bit of data that was on the source device, this including the allocated, unallocated, and the available slack space .

 The image is then used for analysis and investigation, and the original evidence is left untouched. Images can’t be used as the working copies of a device.  Unlike cloning, which produces working copies, forensic images are typically used for analysis and investigation purposes and are not intended for regular use as working copies.

Characteristics of Imaging:

•  Integrity: Imaging ensures the integrity and authenticity of the evidence produced
•  Flexibility: Forensic image replicas can be mounted as a virtual drive to create image-specific mode for analysis of data without affecting the original evidence . 
• Metadata: Imaging captures metadata associated with the data, thus promoting forensic analysis.

Key Differences

• Purpose: Copying is for everyday use but not good for forensic investigations requiring data integrity. Cloning and imaging are made for forensic preservation.
• Depth of Replication: Cloning and imaging captures the entire storage device including hidden, unallocated, and deleted data  whereas copying may miss crucial forensic data.
• Data Integrity: Imaging and cloning keep the integrity of the original evidence thus making them suitable for legal and forensic use. Which is a critical aspect of forensic investigations.
• Forensic Soundness: Imaging is considered the best in digital forensics due to its comprehensive and non-invasive nature.
• Cloning is generally from one hard disk to another, where as imaging creates a compressed file that contains a snapshot of the entire hard drive or a specific partitions

Conclusion

Therefore, copying, cloning, and imaging all deal with duplication of data or storage devices with significant variations, especially in digital forensic. However, for forensic investigations, imaging is the most selected approach due to the correct preservation of the evidence state for any analysis or legal use . Therefore, it is essential for forensic investigators to understand these rigorous differences to avail of real and uncontaminated digital evidence for their investigation and legal argument.

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Introduction

In today’s digital world, where everything is related to data, the more data you own, the more control and compliance you have over the market, which is why companies are looking for ways to use data to improve their business. But at the same time, they have to make sure they are protecting people’s privacy. It is very tricky to strike a balance between both of them. Imagine you are trying to bake a cake where you need to use all the ingredients to make it taste great, but you also have to make sure no one can tell what’s in it. That’s kind of what companies are dealing with when it comes to data. Here, ‘Pseudonymisation’ emerges as a critical technical and legal mechanism that offers a middle ground between data anonymisation and unrestricted data processing. 

Legal Framework and Regulatory Landscape 

Pseudonymisation, as defined by the General Data Protection Regulation (GDPR) in Article 4(5), refers to “the processing of personal data in such a manner that the personal data can no longer be attributed to a specific data subject without the use of additional information, provided that such additional information is kept separately and is subject to technical and organisational measures to ensure that the personal data are not attributed to an identified or identifiable natural person”. This technique represents a paradigm shift in data protection strategy, enabling organisations to preserve data utility while significantly reducing privacy risks. The growing importance of this balance is evident in the proliferation of data protection laws worldwide, from GDPR in Europe to India’s Digital Personal Data Protection Act (DPDP) of 2023. 

Its legal treatment varies across jurisdictions, but a convergent approach is emerging that recognises its value as a data protection safeguard while maintaining that the pseudonymised data remains personal data. Article 25(1) of GDPR recognises it as “an appropriate technical and organisational measure” and emphasises its role in reducing risks to data subjects. It protects personal data by reducing the risk of identifying individuals during data processing. The European Data Protection Board’s (EDPB) 2025 Guidelines on Pseudonymisation provide detailed guidance emphasising the importance of defining the “pseudonymisation domain”. It defines who is prevented from attributing data to specific individuals and ensures that the technical and organised measures are in place to block unauthorised linkage of pseudonymised data to the original data subjects. In India, while the DPDP Act does not explicitly define pseudonymisation, legal scholars argue that such data would still fall under the definition of personal data, as it remains potentially identifiable. The Act defines personal data defined in section 2(t) broadly as “any data about an individual who is identifiable by or in relation to such data,” suggesting that the pseudonymised information, being reversible, would continue to require compliance with data protection obligations. 

Further, the DPDP  Act, 2023 also includes principles of data minimisation and purpose limitation. Section 8(4) says that a “Data Fiduciary shall implement appropriate technical and organisational measures to ensure effective observance of the provisions of this Act and the Rules made under it.” The concept of Pseudonymization fits here because it is a recognised technical safeguard, which means companies can use pseudonymization as one of the methods or part of their compliance toolkit under Section 8(4) of the DPDP Act. However, its use should be assessed on a case to case basis, since ‘encryption’ is also considered one of the strongest methods for protecting personal data. The suitability of pseudonymization depends on the nature of the processing activity, the type of data involved, and the level of risk that needs to be mitigated. In practice, organisations may use pseudonymization in combination with other safeguards to strengthen overall compliance and security.

The European Court of Justice’s recent jurisprudence has introduced nuanced considerations about when pseudonymised data might not constitute personal data for certain entities. In cases where only the original controller possesses the means to re-identify individuals, third parties processing such data may not be subject to the full scope of data protection obligations, provided they cannot reasonably identify the data subjects. The “means reasonably likely” assessment represents a significant development in understanding the boundaries of data protection law. 

Corporate Implementation Strategies 

Companies find that pseudonymisation is not just about following rules, but it also brings real benefits. By using this technique, businesses can keep their data more secure and reduce the damage in the event of a breach. Customers feel more confident knowing that their information is protected, which builds trust. Additionally, companies can utilise this data for their research or other important purposes without compromising user privacy. 

Key Benefits of Pseudonymisation:

1. Enhanced Privacy Protection: It hides personal details like names or IDs with fake ones (with artificial values or codes), making it harder for accidental privacy breaches.
2. Preserved Data Utility: Unlike completely anonymous data, pseudonymised data keeps its usefulness by maintaining important patterns and relationships within datasets.
3. Facilitate Data Sharing: It’s easier to share pseudonymised data with partners or researchers because it protects privacy while still being useful.

However, using pseudonymisation is not as easy as companies have to deal with tricky technical issues like choosing the right methods, such as encryption or tokenisation and managing security keys safely. They have to implement strong policies to stop anyone from figuring out who the data belongs to. This can get expensive and complicated, especially when dealing with a large amount of data, and it often requires expert help and regular upkeep. 

Balancing Privacy Rights and Data Utility

The primary challenge in pseudonymisation is striking the right balance between protecting individuals' privacy and maintaining the utility of the data. To get this right, companies need to consider several factors, such as why they are using the data, the potential hacker's level of skill, and the type of data being used.

Conclusion 

Pseudonymisation offers a practical middle ground between full anonymisation and restricted data use, enabling organisations to harness the value of data while protecting individual privacy. Legally, it is recognised as a safeguard but still treated as personal data, requiring compliance under frameworks like GDPR and India’s DPDP Act. For companies, it is not only regulatory adherence but also ensuring that it builds trust and enhances data security. However, its effectiveness depends on robust technical methods, governance, and vigilance. Striking the right balance between privacy and data utility is crucial for sustainable, ethical, and innovation-driven data practices.

References:

1. https://gdpr-info.eu/art-4-gdpr/
2. https://www.meity.gov.in/static/uploads/2024/06/2bf1f0e9f04e6fb4f8fef35e82c42aa5.pdf
3. https://gdpr-info.eu/art-25-gdpr/
4. https://www.edpb.europa.eu/system/files/2025-01/edpb_guidelines_202501_pseudonymisation_en.pdf
5. https://curia.europa.eu/juris/document/document.jsf?text=&docid=303863&pageIndex=0&doclang=EN&mode=req&dir=&occ=first&part=1&cid=16466915
6. https://curia.europa.eu/juris/document/document.jsf?text=&docid=303863&pageIndex=0&doclang=EN&mode=req&dir=&occ=first&part=1&cid=16466915

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