Alterations in Personal Data Protection Bill

Introduction

The information of hundreds of thousands of Indians who received the COVID vaccine was Leaked in a significant data breach and posted on a Telegram channel. Numerous reports claim that sensitive information, including a person’s phone number, gender, ID card details, and date of birth, leaked over Telegram. It could be obtained by typing a person’s name into a Telegram bot.

What really happened?

The records pertaining to the mobile number registered in the CoWin portal are accessible on the Malayalam news website channel. It is also feasible to determine which vaccination was given and where it was given.

According to The Report, the list of individuals whose data was exposed includes BJP Tamil Nadu president K Annamalai, Congress MP Karti Chidambaram, and former BJP union minister for health Harsh Vardhan. Telangana’s minister of information and communication technology, Kalvakuntla Taraka Rama Rao, is also on the list.

MEITY stated in response to the data leak, “It is old data, we are still confirming it. We have requested a report on the matter.

After the media Report, the bot was disabled, but experts said the incident raised severe issues because the information might be used for identity theft, phishing emails, con games, and extortion calls. The Indian Computer Emergency Response Team (CERT-In), the government’s nodal body, has opened an investigation into the situation

The central government declared the data breach reports regarding the repository of beneficiaries against Covid to be “mischievous in nature” on Monday and claimed the ‘bot’ that purportedly accessed the confidential data was not directly accessing the CoWIN database.

According to the first complaint by CERT-In, the government’s cybersecurity division, the government claimed the bot might be displaying information from “previously stolen data.” Reports.

The health ministry refuted the claim, asserting that no bots could access the information without first verifying with a one-time password.

“It is made clear that all of these rumours are false and malicious. The health ministry’s CoWIN interface is entirely secure and has sufficient data privacy protections. The security of the data on the CoWIN portal is being ensured in every way possible, according to a statement from the health ministry.

Meity said the CoWin program or database was not directly compromised, and the shared information appeared to be taken from a previous intrusion. But the hack again highlights the growing danger of cyber assaults, particularly on official websites.‍

Recent cases of data leak

Dominos India 2021– Dominos India, a division of Jubilant FoodWorks, faced a cyberattack on May 22, 2021, which led to the disclosure of information from 180 million orders. The breach exposed order information, email addresses, phone numbers, and credit card information. Although Jubilant FoodWorks acknowledged a security breach, it refuted any illegal access to financial data.

Air India – A cyberattack that affected Air India in May 2021 exposed the personal information of about 4.5 million customers globally. Personal information recorded between August 26, 2011, and February 3, 2021, including names, dates of birth, contact information, passport information, ticket details, frequent flyer information from Star Alliance and Air India, and credit card information, were exposed in the breach.

Bigbasket – BigBasket, an online supermarket, had a data breach in November 2020, compromising the personal information of approximately 20 million consumers. Email IDs, password hashes, PINs, phone numbers, addresses, dates of birth, localities, and IP addresses were among the information released from an insecure database containing over 15 GB of customer data. BigBasket admitted to the incident and reported it to the Bengaluru Cyber Crime Department.

Unacademy – Unacademy, an online learning platform, experienced a data breach in May 2020, compromising the email addresses of approximately 11 million subscribers. While no sensitive information, such as financial data or passwords, was compromised, user data, including IDs, passwords, date joined, last login date, email IDs, names, and user credentials, was. The breach was detected when user accounts were uncovered for sale on the dark web.

2022 Card Data- Cybersecurity researchers from AI-driven Singapore-based CloudSEK found a threat actor offering a database of 1.2 million cards for free on a Dark Web forum for crimes on October 12, 2022. This came after a second problem involving 7.9 million cardholder records that were reported on the BidenCash website. This comprised information pertaining to State Bank of India (SBI) clients. And other well-known companies were among those targeted in high-profile data breach cases that have surfaced in recent years.

Conclusion

Data breach cases are increasing daily, and attackers are mainly attacking the healthcare sectors and health details as they can easily find personal details. This recent CoWIN case has compromised thousands of people’s data. The All-India Institute of Medical Sciences’ systems were compromised by hackers a few months ago. Over 95% of adults have had their vaccinations, according to the most recent data, even if the precise number of persons impacted by the CoWin privacy breach could not be determined.

Introduction

According to a shocking report, there are multiple scam loan apps on the App Store in India that charge excessive interest rates and force users to pay by blackmailing and harassing them. Apple has prohibited and removed these apps from the App Store, but they may still be installed on your iPhone and running. You must delete any of these apps if you have downloaded them. Learn the names of these apps and how they operated the fraud.

Why Apple banned these apps?

• Apple has taken action to remove certain apps from the Indian App Store. These apps were engaging in unethical behaviour, such as impersonating financial institutions, demanding high fees, and threatening borrowers. Here are the titles of these apps, as well as what Apple has said about their suspension.
• Following user concerns, Apple removed six loan apps from the Indian App Store. Loan apps include White Kash, Pocket Kash, Golden Kash, Ok Rupee, and others.
• According to multiple user reviews, certain apps seek unjustified access to users’ contact lists and media. These apps also charge exorbitant fees that are not necessitated. Furthermore, companies have been found to engage in unethical tactics such as charging high-interest rates and “processing fees” equal to half the loan amount.
• Some lending app users have reported being harassed and threatened for failing to return their loans on time. In some circumstances, the apps threatened the user’s contacts if payment was not completed by the deadline. According to one user, the app company threatened to produce and send false photographs of her to her contacts.
• These loan apps were removed from the App Store, according to Apple, because they broke the norms and standards of the Apple Developer Program License Agreement. These apps were discovered to be falsely claiming financial institution connections.

Issue of Fake loan apps on the App Store

• The App Store and our App Review Guidelines are designed to ensure we provide our users with the safest experience possible,” Apple explained. “We do not tolerate fraudulent activity on the App Store and have strict rules against apps and developers who attempt to game the system.
• In 2022, Apple blocked nearly $2 billion in fraudulent App Store sales. Furthermore, it rejected nearly 1.7 million software submissions that did not match Apple’s quality and safety criteria and cancelled 428,000 developer accounts due to suspected fraudulent activities.
• The scammers also used heinous tactics to force the loanees to pay. According to reports, the scammers behind the apps gained access to the user’s contact list as well as their images. They would morph the images and then scare the individual by sharing their fake nude photos with their whole contact list.

Dangerous financial fraud apps have surfaced on the App Store

• TechCrunch acquired a user review from one of these apps. “I borrowed an amount in a helpless situation, and a day before the repayment due date, I got some messages with my picture and my contacts in my phone saying that repay your loan or they will inform our contacts that you are not paying the loan,” it said.
• Sandhya Ramesh, a journalist from The Print, recently tweeted a screenshot of a direct message she got. A victim’s friend told a similar story in the message.
• TechCrunch contacted Apple, who confirmed that the apps had been removed from the App Store for breaking the Apple Developer Program License Agreement and guidelines.

Conclusion

Recently, some users have claimed that some quick-loan applications, such as White Kash, Pocket Kash, and Golden Kash, have appeared on the Top Finance applications chart in recent days. These apps necessitate unauthorised and intrusive access to users’ contact lists and media. According to hundreds of user evaluations, these apps charged exorbitantly high and useless fees. They used unscrupulous techniques such as demanding “processing fees” equal to half the loan amount and charging high-interest rates. Users were also harassed and threatened with restitution. If payments were not made by the due date, the lending applications threatened to notify users’ contacts. According to one user, the app provider even threatened to generate phoney nude images of her and send them to her contacts.

Introduction

The Senate bill introduced on 19 March 2024 in the United States would require online platforms to obtain consumer consent before using their data for Artificial Intelligence (AI) model training. If a company fails to obtain this consent, it would be considered a deceptive or unfair practice and result in enforcement action from the Federal Trade Commission (FTC) under the AI consumer opt-in, notification standards, and ethical norms for training (AI Consent) bill. The legislation aims to strengthen consumer protection and give Americans the power to determine how their data is used by online platforms. 

The proposed bill also seeks to create standards for disclosures, including requiring platforms to provide instructions to consumers on how they can affirm or rescind their consent. The option to grant or revoke consent should be made available at any time through an accessible and easily navigable mechanism, and the selection to withhold or reverse consent must be at least as prominent as the option to accept while taking the same number of steps or fewer as the option to accept.

The AI Consent bill directs the FTC to implement regulations to improve transparency by requiring companies to disclose when the data of individuals will be used to train AI and receive consumer opt-in to this use. 
The bill also commissions an FTC report on the technical feasibility of de-identifying data, given the rapid advancements in AI technologies, evaluating potential measures companies could take to effectively de-identify user data.

The definition of ‘Artificial Intelligence System’ under the proposed bill

ARTIFICIALINTELLIGENCE SYSTEM- The term artificial intelligence system“ means a machine-based system that—

1. Is capable of influencing the environment by producing an output, including predictions, recommendations or decisions, for a given set of objectives; and
2. 2. Uses machine or human-based data and inputs to

(i) Perceive real or virtual environments;

(ii) Abstract these perceptions into models through analysis in an automated manner (such as by using machine learning) or manually; and

(iii) Use model inference to formulate options for outcomes.

Importance of the proposed AI Consent Bill USA

1. Consumer Data Protection: The AI Consent bill primarily upholds the privacy rights of an individual. Consent is necessitated from the consumer before data is used for AI Training; the bill aims to empower individuals with unhinged autonomy over the use of personal information. The scope of the bill aligns with the greater objective of data protection laws globally, stressing the criticality of privacy rights and autonomy.

2. Prohibition Measures: The proposed bill intends to prohibit covered entities from exploiting the data of consumers for training purposes without their consent. This prohibition extends to the sale of data, transfer to third parties and usage. Such measures aim to prevent data misuse and exploitation of personal information. The bill aims to ensure companies are leveraged by consumer information for the development of AI without a transparent process of consent.

3. Transparent Consent Procedures: The bill calls for clear and conspicuous disclosures to be provided by the companies for the intended use of consumer data for AI training. The entities must provide a comprehensive explanation of data processing and its implications for consumers. The transparency fostered by the proposed bill allows consumers to make sound decisions about their data and its management, hence nurturing a sense of accountability and trust in data-driven practices.

4. Regulatory Compliance: The bill's guidelines call for strict requirements for procuring the consent of an individual. The entities must follow a prescribed mechanism for content solicitation, making the process streamlined and accessible for consumers. Moreover, the acquisition of content must be independent, i.e. without terms of service and other contractual obligations. These provisions underscore the importance of active and informed consent in data processing activities, reinforcing the principles of data protection and privacy.

5. Enforcement and Oversight: To enforce compliance with the provisions of the bill, robust mechanisms for oversight and enforcement are established. Violations of the prescribed regulations are treated as unfair or deceptive acts under its provisions. Empowering regulatory bodies like the FTC to ensure adherence to data privacy standards. By holding covered entities accountable for compliance, the bill fosters a culture of accountability and responsibility in data handling practices, thereby enhancing consumer trust and confidence in the digital ecosystem.

Importance of Data Anonymization

Data Anonymization is the process of concealing or removing personal or private information from the data set to safeguard the privacy of the individual associated with it. Anonymised data is a sort of information sanitisation in which data anonymisation techniques encrypt or delete personally identifying information from datasets to protect data privacy of the subject. This reduces the danger of unintentional exposure during information transfer across borders and allows for easier assessment and analytics after anonymisation. When personal information is compromised, the organisation suffers not just a security breach but also a breach of confidence from the client or consumer. Such assaults can result in a wide range of privacy infractions, including breach of contract, discrimination, and identity theft.

The AI consent bill asks the FTC to study data de-identification methods. Data anonymisation is critical to improving privacy protection since it reduces the danger of re-identification and unauthorised access to personal information. Regulatory bodies can increase privacy safeguards and reduce privacy risks connected with data processing operations by investigating and perhaps implementing anonymisation procedures.

The AI consent bill emphasises de-identification methods, as well as the DPDP Act 2023 in India, while not specifically talking about data de-identification, but it emphasises the data minimisation principles, which highlights the potential future focus on data anonymisation processes or techniques in India.

Conclusion

The proposed AI Consent bill in the US represents a significant step towards enhancing consumer privacy rights and data protection in the context of AI development. Through its stringent prohibitions, transparent consent procedures, regulatory compliance measures, and robust enforcement mechanisms, the bill strives to strike a balance between fostering innovation in AI technologies while safeguarding the privacy and autonomy of individuals.

References:

• https://fedscoop.com/consumer-data-consent-training-ai-models-senate-bill/#:~:text=%E2%80%9CThe%20AI%20CONSENT%20Act%20gives,Welch%20said%20in%20a%20statement
• https://www.dataguidance.com/news/usa-bill-ai-consent-act-introduced-house#:~:text=USA%3A%20Bill%20for%20the%20AI%20Consent%20Act%20introduced%20to%20House%20of%20Representatives,-ConsentPrivacy%20Law&text=On%20March%2019%2C%202024%2C%20US,the%20U.S.%20House%20of%20Representatives
• https://datenrecht.ch/en/usa-ai-consent-act-vorgeschlagen/
• https://www.lujan.senate.gov/newsroom/press-releases/lujan-welch-introduce-billto-require-online-platforms-receive-consumers-consent-before-using-their-personal-data-to-train-ai-models/

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