#FactCheck- Viral Photo Claiming PM Modi Met ‘Cockroach Janata Party’ Founder Abhijeet Dipke Is AI-Generated

Introduction

The whole world is shifting towards a cashless economy, with innovative payment transaction systems such as UPI payments, card payments, etc. These payment systems require processing, storage, and movement of millions of cardholders data which is crucial for any successful transaction.

And therefore to maintain the credibility of this payment ecosystem, security or secure movement and processing of cardholders data becomes paramount. Entities involved in a payment ecosystem are responsible for the security of cardholders data. Security is also important because if breaches happen in cardholders data it would amount to financial loss. Fraudsters are attempting smart ways to leverage any kind of security loopholes in the payment system.

So these entities which are involved in the payment ecosystem need to maintain some security standards set by one council of network providers in the payment industry popularly known as the Payment Card Industry Security Standard Council.

Overview of what is PCI and PCI DSS Compliance

Earlier every network providers in the payment industry have their own set of security standards but later they all together i.e., Visa, Mastercard, American Express, Discover, and JCB constituted an independent body to come up with comprehensive security standards like PCI DSS, PA DSS, PCI-PTS, etc.  And these network providers ensure the enforcement of the security standards by putting conditions on services being provided to the merchant or acquirer bank.

In other words, PCI DSS particularly is the global standard that provides a baseline of technical and operational requirements designed to protect account data. PCI DSS is a security standard specially designed for merchants and service providers in the payment ecosystem to protect the cardholders data against any fraud or theft.

It applies to all the entities including third-party vendors which are involved in processing storing and transmitting cardholders data. In organization, even all CDE (Card Holder Data Environment) including system components or network component that stores and process cardholders data, has to comply with all the requirements of PCI compliance.  Recently PCI has released a new version of PCI DSS v4.0 a few months ago with certain changes from the previous version after three years of the review cycle.

12 Requirements of PCI DSS

This is the most important part of PCI DSS as following these requirements can make any organization to some extent PCI compliant. So what are these requirements:

• Installing firewalls or maintaining security controls in the networks
• Use strong password in order to secure the CDE( Card holders data environment)
• Protection of cardholder data
• Encrypting the cardholder data during transmission over an open and public network.
• Timely detection and protection of the cardholders data environment from any malicious activity or software.
• Regular updating the software thereby maintaining a secure system.
• Rule of business need to know should apply to access the cardholders data
• Identification and authentication of the user are important to access the system components.
• Physical access to cardholders data should be restricted.
• Monitoring or screening of system components to know the malicious activity internally in real-time.
• Regular auditing of security control and finding any vulnerabilities available in the systems.
• Make policies and programs accordingly in order to support information security.

How organization can become PCI compliant

• Scope: First step is to determine all the system components or networks storing and processing cardholders data i.e., Cardholders Data Environment.
• Assess: Then test whether these systems or networks are complying with all the requirements of PCI DSS COMPLIANCE.
• Report: Documenting all the assessment through self assessment questionnaire by answering following questions like whether the requirements are met or not? Whether the requirements are met with customized approach.
• Attest: Then the next step is to complete the attestation process available on the website of PCI SSC.
• Submit: Then organization can submit all the documents including reports and other supporting documents if it is requested by other entities such as payment brands, merchant or acquirer.
• Remediate: Then the organisation should take remedial action for the requirements which are not in place on the system components or networks.

Conclusion

One of the most important issues facing those involved in the digital payment ecosystem is cybersecurity. The likelihood of being exposed to cybersecurity hazards including online fraud, information theft, and virus assaults is rising as more and more users prefer using digital payments.

And thus complying and adopting with these security standards is the need of the hour. And moreover RBI has also mandated all the regulated entities ( NBFCs Banks etc) under one recent notification to comply with these standards.

Introduction

According to Statista, the global artificial intelligence software market is forecast to grow by around 126 billion US dollars by 2025. This will include a 270% increase in enterprise adoption over the past four years. The top three verticals in the Al market are BFSI (Banking, Financial Services, and Insurance), Healthcare & Life Sciences, and Retail & e-commerce. These sectors benefit from vast data generation and the critical need for advanced analytics. Al is used for fraud detection, customer service, and risk management in BFSI; diagnostics and personalised treatment plans in healthcare; and retail marketing and inventory management.

The Chairperson of the Competition Commission of India’s Chief, Smt. Ravneet Kaur raised a concern that Artificial Intelligence has the potential to aid cartelisation by automating collusive behaviour through predictive algorithms. She explained that the mere use of algorithms cannot be anti-competitive but in case the algorithms are manipulated, then that is a valid concern about competition in markets.

This blog focuses on how policymakers can balance fostering innovation and ensuring fair competition in an AI-driven economy. 

What is the Risk Created by AI-driven Collusion?

AI uses predictive algorithms, and therefore, they could lead to aiding cartelisation by automating collusive behaviour. AI-driven collusion could be through:

• The use of predictive analytics to coordinate pricing strategies among competitors.
• The lack of human oversight in algorithm-induced decision-making leads to tacit collusion (competitors coordinate their actions without explicitly communicating or agreeing to do so).

AI has been raising antitrust concerns and the most recent example is the partnership between Microsoft and OpenAI, which has raised concerns among other national competition authorities regarding potential competition law issues. While it is expected that the partnership will potentially accelerate innovation, it also raises concerns about potential anticompetitive effects such as market foreclosure or the creation of barriers to entry for competitors and, therefore, has been under consideration in the German and UK courts. The problem here is in detecting and proving whether collusion is taking place. 

The Role of Policy and Regulation

The uncertainties induced by AI regarding its effects on competition create the need for algorithmic transparency and accountability in mitigating the risks of AI-driven collusion. It leads to the need to build and create regulatory frameworks that mandate the disclosure of algorithmic methodologies and establish a set of clear guidelines for the development of AI and its deployment. These frameworks or guidelines should encourage an environment of collaboration between competition watchdogs and AI experts. 

The global best practices and emerging trends in AI regulation already include respect for human rights, sustainability, transparency and strong risk management. The EU AI Act could serve as a model for other jurisdictions, as it outlines measures to ensure accountability and mitigate risks. The key goal is to tailor AI regulations to address perceived risks while incorporating core values such as privacy, non-discrimination, transparency, and security.

Promoting Innovation Without Stifling Competition

Policymakers need to ensure that they balance regulatory measures with innovation scope and that the two priorities do not hinder each other. 

1. Create adaptive and forward-thinking regulatory approaches to keep pace with technological advancements that take place at the pace of development and allow for quick adjustments in response to new AI capabilities and market behaviours.n
2. Competition watchdogs need to recruit domain experts to assess competition amid rapid changes in the technology landscape. Create a multi-stakeholder approach that involves regulators, industry leaders, technologists and academia who can create inclusive and ethical AI policies. 
3. Businesses can be provided incentives such as recognition through certifications, grants or benefits in acknowledgement of adopting ethical AI practices. 
4. Launch studies such as the CCI’s market study to study the impact of AI on competition. This can lead to the creation of a driving force for sustainable growth with technological advancements. 

Conclusion: AI and the Future of Competition

We must promote a multi-stakeholder approach that enhances regulatory oversight, and incentivising ethical AI practices. This is needed to strike a delicate balance that safeguards competition and drives sustainable growth. As AI continues to redefine industries, embracing collaborative, inclusive, and forward-thinking policies will be critical to building an equitable and innovative digital future. 

The lawmakers and policymakers engaged in the drafting of the frameworks need to ensure that they are adaptive to change and foster innovation. It is necessary to note that fair competition and innovation are not mutually exclusive goals, they are complementary to each other. Therefore, a regulatory framework that promotes transparency, accountability, and fairness in AI deployment must be established.

References

• https://www.thehindu.com/sci-tech/technology/ai-has-potential-to-aid-cartelisation-fair-competition-integral-for-sustainable-growth-cci-chief/article69041922.ece 
• https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-market-74851580.html 
• https://www.ey.com/en_in/insights/ai/how-to-navigate-global-trends-in-artificial-intelligence-regulation#:~:text=Six%20regulatory%20trends%20in%20Artificial%20Intelligence&text=These%20include%20respect%20for%20human,based%20approach%20to%20AI%20regulation. ‍
• https://www.business-standard.com/industry/news/ai-has-potential-to-aid-fair-competition-for-sustainable-growth-cci-chief-124122900221_1.html

Introduction

Advanced deepfake technology blurs the line between authentic and fake. To ascertain the credibility of the content it has become important to differentiate between genuine and manipulated or curated online content highly shared on social media platforms. AI-generated fake voice clone, videos are proliferating on the Internet and social media. There is the use of sophisticated AI algorithms that help manipulate or generate synthetic multimedia content such as audio, video and images. As a result, it has become increasingly difficult to differentiate between genuine, altered, or fake multimedia content. McAfee Corp., a well-known or popular global leader in online protection, has recently launched an AI-powered deepfake audio detection technology under Project “Mockingbird” intending to safeguard consumers against the surging threat of fabricated or AI-generated audio or voice clones to dupe people for money or unauthorisly obtaining their personal information. McAfee Corp. announced its AI-powered deepfake audio detection technology, known as Project Mockingbird, at the Consumer Electronics Show, 2024.

What is voice cloning?

To create a voice clone of anyone's, audio can be deeplyfaked, too, which closely resembles a real voice but, in actuality, is a fake voice created through deepfake technology. 

Emerging Threats: Cybercriminal Exploitation of Artificial Intelligence in Identity Fraud, Voice Cloning, and Hacking Acceleration

AI is used for all kinds of things from smart tech to robotics and gaming. Cybercriminals are misusing artificial intelligence for rather nefarious reasons including voice cloning to commit cyber fraud activities. Artificial intelligence can be used to manipulate the lips of an individual so it looks like they're saying something different, it could also be used for identity fraud to make it possible to impersonate someone for a remote verification for your bank and it also makes traditional hacking more convenient. Cybercriminals have been misusing advanced technologies such as artificial intelligence, which has led to an increase in the speed and volume of cyber attacks, and that's been the theme in recent times.

Technical Analysis

To combat Audio cloning fraudulent activities, McAfee Labs has developed a robust AI model that precisely detects artificially generated audio used in videos or otherwise.

• Context-Based Recognition: Contextual assessment is used by technological devices to examine audio components in the overall setting of an audio. It improves the model's capacity to recognise discrepancies suggestive of artificial intelligence-generated audio by evaluating its surroundings information.
• Conductual Examination: Psychological detection techniques examine linguistic habits and subtleties, concentrating on departures from typical individual behaviour. Examining speech patterns, tempo, and pronunciation enables the model to identify artificially or synthetically produced material.
• Classification Models: Auditory components are categorised by categorisation algorithms for detection according to established traits of human communication. The technology differentiates between real and artificial intelligence-synthesized voices by comparing them against an extensive library of legitimate human speech features.
• Accuracy Outcomes: McAfee Labs' deepfake voice recognition solution, which boasts an impressive ninety per cent success rate, is based on a combined approach incorporating psychological, context-specific, and categorised identification models. Through examining audio components in the larger video context and examining speech characteristics, such as intonation, rhythm, and pronunciation, the system can identify discrepancies that could be signs of artificial intelligence-produced audio. Categorical models make an additional contribution by classifying audio information according to characteristics of known human speech. This all-encompassing strategy is essential for precisely recognising and reducing the risks connected to AI-generated audio data, offering a strong barrier against the growing danger of deepfake situations.
• Application Instances: The technique protects against various harmful programs, such as celebrity voice-cloning fraud and misleading content about important subjects.

Conclusion

It is important to foster ethical and responsible consumption of technology. Awareness of common uses of artificial intelligence is a first step toward broader public engagement with debates about the appropriate role and boundaries for AI. Project Mockingbird by Macafee employs AI-driven deepfake audio detection to safeguard against cyber criminals who are using fabricated AI-generated audio for scams and manipulating the public image of notable figures, protecting consumers from financial and personal information risks. 

References:

• https://www.cnbctv18.com/technology/mcafee-deepfake-audio-detection-technology-against-rise-in-ai-generated-misinformation-18740471.htm
• https://www.thehindubusinessline.com/info-tech/mcafee-unveils-advanced-deepfake-audio-detection-technology/article67718951.ece
• https://lifestyle.livemint.com/smart-living/innovation/ces-2024-mcafee-ai-technology-audio-project-mockingbird-111704714835601.html
• https://news.abplive.com/fact-check/audio-deepfakes-adding-to-cacophony-of-online-misinformation-abpp-1654724