The Misinformation Ecosystem Surrounding PCOS, Bridging Gaps to Counter Digital Myths

Introduction

AI-generated fake videos are proliferating on the Internet indeed becoming more common by the day. There is a use of sophisticated AI algorithms that help manipulate or generate multimedia content such as videos, audio, and images. As a result, it has become increasingly difficult to differentiate between genuine, altered, or fake content, and these AI-manipulated videos look realistic. A recent study has shown that 98% of deepfake-generated videos have adult content featuring young girls, women, and children, with India ranking 6th among the nations that suffer from misuse of deepfake technology. This practice has dangerous consequences and could harm an individual's reputation, and criminals could use this technology to create a false narrative about a candidate or a political party during elections.

The working of deepfake videos is based on algorithms that refine the fake content, and the generators are built and trained in such a way as to get the desired output. The process is repeated several times, allowing the generator to improve the content until it seems realistic, making it more flawless. Deepfake videos are created by specific approaches some of them are: -

• Lip syncing: This is the most common technique used in deepfake. Here, the voice recordings of the video, make it appear as to what was originally said by the person appearing in the video.
• Audio deepfake:  For Audio-generated deepfake, a generative adversarial network (GAN) is used to colon a person’s voice, based on the vocal patterns and refine it till the desired output is generated.

• Deepfake has become so serious that the technology could be used by bad actors or by cyber-terrorist squads to set their Geo-political agendas.  Looking at the present situation in the past few the number of cases has just doubled, targeting children, women and popular faces. 

• Greater Risk: in the last few years the cases of deep fake have risen. by the end of the year 2022, the number of cases has risen to 96% against women and children according to a survey.
• Every 60 seconds, a deepfake pornographic video is created, now quicker and more affordable than ever, it takes less than 25 minutes and costs using just one clean face image.  
• The connection to deepfakes is that people can become targets of "revenge porn" without the publisher having sexually explicit photographs or films of the victim. They may be made using any number of random pictures or images collected from the internet to obtain the same result. This means that almost everyone who has taken a selfie or shared a photograph of oneself online faces the possibility of a deepfake being constructed in their image.

Deepfake-related security concerns

As deepfakes proliferate, more people are realising that they can be used not only to create non-consensual porn but also as part of disinformation and fake news campaigns with the potential to sway elections and rekindle frozen or low-intensity conflicts.

Deepfakes have three security implications: at the international level, strategic deepfakes have the potential to destroy precarious peace; at the national level, deepfakes may be used to unduly influence elections, and the political process, or discredit opposition, which is a national security concern, and at the personal level, the scope for using Women suffer disproportionately from exposure to sexually explicit content as compared to males, and they are more frequently threatened. 

Policy Consideration

Looking at the present situation where the cases of deepfake are on the rise against women and children, the policymakers need to be aware that deepfakes are utilized for a variety of valid objectives, including artistic and satirical works, which policymakers should be aware of. Therefore, simply banning deepfakes is not a way consistent with fundamental liberties. One conceivable legislative option is to require a content warning or disclaimer. Deepfake is an advanced technology and misuse of deepfake technology is a crime.

What are the existing rules to combat deepfakes?

It's worth noting that both the IT Act of 2000 and the IT Rules of 2021 require social media intermediaries to remove deep-fake videos or images as soon as feasible. Failure to follow these guidelines can result in up to three years in jail and a Rs 1 lakh fine. Rule 3(1)(b)(vii) requires social media intermediaries to guarantee that its users do not host content that impersonates another person, and Rule 3(2)(b) requires such content to be withdrawn within 24 hours of receiving a complaint. Furthermore, the government has stipulated that any post must be removed within 36 hours of being published online. Recently government has also issued an advisory to social media intermediaries to identify misinformation and deepfakes.

Conclusion

It is important to foster ethical and responsible consumption of technology. This can only be achieved by creating standards for both the creators and users, educating individuals about content limits, and providing information. Internet-based platforms should also devise techniques to deter the uploading of inappropriate information. We can reduce the negative and misleading impacts of deepfakes by collaborating and ensuring technology can be used in a better manner.  

References

• https://timesofindia.indiatimes.com/life-style/parenting/moments/how-social-media-scandals-like-deepfake-impact-minors-and-students-mental-health/articleshow/105168380.cms?from=mdr
• https://www.aa.com.tr/en/science-technology/deepfake-technology-putting-children-at-risk-say-experts/2980880
• https://wiisglobal.org/deepfakes-as-a-security-issue-why-gender-matters/

Executive Summary:

One of the most complex threats that have appeared in the space of network security is focused on the packet rate attacks that tend to challenge traditional approaches to DDoS threats’ involvement. In this year, the British based biggest Internet cloud provider of Europe, OVHcloud was attacked by a record and unprecedented DDoS attack reaching the rate of 840 million packets per second. Targets over 1 Tbps have been observed more regularly starting from 2023, and becoming nearly a daily occurrence in 2024. The maximum attack on May 25, 2024, got to 2.5 Tbps, this points to a direction to even larger and more complex attacks of up to 5 Tbps. Many of these attacks target critical equipment such as Mikrotik models within the core network environment; detection and subsequent containment of these threats prove a test for cloud security measures.

Modus Operandi of a Packet Rate Attack:

A type of cyberattack where an attacker sends with a large volume of packets in a short period of time aimed at a network device is known as packet rate attack, or packet flood attack or network flood attack under volumetric DDoS attack. As opposed to the deliberately narrow bandwidth attacks, these raids target the computation time linked with package processing. 

Key technical characteristics include: 

• Packet Size: Usually compact, and in many cases is less than 100 bytes 
• Protocol: Named UDP, although it can also involve TCP SYN or other protocol flood attacks 
•  Rate: Exceeding 100 million packets per second (Mpps), with recent attacks exceeding 840 Mpps 
• Source IP Diversity: Usually originating from a small number of sources and with a large number of requests per IP, which testifies about the usage of amplification principles 
• Attack on the Network Stack : To understand the impact, let's examine how these attacks affect different layers of the network stack:

1. Layer 3 (Network Layer):

• Each packet requires routing table lookups and hence routers and L3 switches have the problem of high CPU usage. 
• These mechanisms can often be saturated so that network communication will be negatively impacted by the attacker.

2. Layer 4 (Transport Layer):

• Other stateful devices (e.g. firewalls, load balancers) have problems with tables of connections 
• TCP SYN floods can also utilize all connection slots so that no incoming genuine connection can be made.

3. Layer 7 (Application Layer): 

• Web servers and application firewalls may be triggered to deliver a better response in a large number of requests 
• Session management systems can become saturated, and hence, the performance of future iterations will be a little lower than expected in terms of their perceived quality by the end-user. 

Technical Analysis of Attack Vectors

Recent studies have identified several key vectors exploited in high-volume packet rate attacks:

1.MikroTik RouterOS Exploitation:

• Vulnerability: CVE-2023-4967
• Impact: Allows remote attackers to generate massive packet floods
• Technical detail: Exploits a flaw in the FastTrack implementation

2.DNS Amplification:

• Amplification factor: Up to 54x
• Technique: Exploits open DNS resolvers to generate large responses to small queries
• Challenge: Difficult to distinguish from legitimate DNS traffic

3.NTP Reflection:

• Command: monlist
• Amplification factor: Up to 556.9x
• Mitigation: Requires NTP server updates and network-level filtering

Mitigation Strategies: A Technical Perspective

1. Combating packet rate attacks requires a multi-layered approach:

• Hardware-based Mitigation:
• Implementation: FPGA-based packet processing
• Advantage: Can handle millions of packets per second with minimal latency
• Challenge: High cost and specialized programming requirements

2.Anycast Network Distribution:

• Technique: Distributing traffic across multiple global nodes
• Benefit: Dilutes attack traffic, preventing single-point failures
• Consideration: Requires careful BGP routing configuration

3.Stateless Packet Filtering:

• Method: Applying filtering rules without maintaining connection state
• Advantage: Lower computational overhead compared to stateful inspection
• Trade-off: Less granular control over traffic

4.Machine Learning-based Detection:

• Approach: Using ML models to identify attack patterns in real-time
• Key metrics: Packet size distribution, inter-arrival times, protocol anomalies
• Challenge: Requires continuous model training to adapt to new attack patterns

Performance Metrics and Benchmarking

When evaluating DDoS mitigation solutions for packet rate attacks, consider these key performance indicators:

• Flows per second (fps) or packet per second (pps) capability
• Dispersion and the latency that comes with it is inherent to mitigation systems.
• The false positive rate in the case of the attack detection
• Exposure time before beginning of mitigation from the moment of attack

Way Forward

The packet rate attacks are constantly evolving where the credible defenses have not stayed the same. The next step entails extension to edge computing and 5G networks for distributing mitigation closer to the attack origins. Further, AI-based proactive tools of analysis for prediction of such threats will help to strengthen the protection of critical infrastructure against them in advance.

In order to stay one step ahead in this, it is necessary to constantly conduct research, advance new technologies, and work together with other cybersecurity professionals. There is always a need to develop secure defenses that safeguard these networks.

Reference:

https://blog.ovhcloud.com/the-rise-of-packet-rate-attacks-when-core-routers-turn-evil/

https://cybersecuritynews.com/record-breaking-ddos-attack-840-mpps/

https://www.cloudflare.com/learning/ddos/famous-ddos-attacks/

‍

Data has become a critical asset for the advancement of a nation’s economic, social, and technological development. India’s emergence as a global digital economy hub makes it necessary to create a robust framework that addresses the challenges and opportunities of digital transformation. The Indian government introduced the Draft National Data Governance Framework Policy in 2022, aiming to create a comprehensive data handling and governance framework. This policy draft addresses key challenges in data management, privacy, and digital economy growth.  As per the recent media reports, the Draft National Data Governance Policy so prepared is under the finalisation stage, the government specified in its implementation document for the Budget 2023-24 announcement. The policy also aims to address the country's AI adoption and the issue of lack of datasets by providing widespread access to anonymized data.

Background and Need for the Policy

India has a robust digital economy with its adoption of the Digital India Initiative, Aadhaar digital identification, UPI for seamless payments and many more. In India, 751.5 million people connect to the internet, and is home to 462.0 million social media users in January 2024, equivalent to 32.2% of its total population (Data Reportal 2024). This has brought challenges including data privacy concerns, cybersecurity threats, digital exclusion, and a need for better regulation frameworks. To overcome them, the Draft National Data Governance Policy has been designed to provide institutional frameworks for data rules, standards, guidelines, and protocols for the sharing of non-personal data sets in a manner that ensures privacy, security, and trust so that they remain secure, transparent, and accountable.

Objectives omphasizesf the Framework 

The objective of the Framework Policy is to accelerate Digital Governance in India. The framework will standardize data management and security standards across the Government. It will promote transparency, accountability, and ownership in Non-Personal data and dataset access and build a platform to receive and process data requests. It will also set quality standards and promote the expansion of the datasets program and overall non-personal ecosystem. Further, it aims to build India’s digital government goals and capacity, knowledge, and competency in Government departments and entities. All this would be done while ensuring greater citizen awareness, participation, and engagement. 

Key Provisions of the Draft Policy 

The Draft Framework Policy aims to establish a cohesive digital governance ecosystem in India that balances the need for data utilization with protecting citizens' privacy rights. It sets up an institutional framework of the "India Data Management Office (IDMO) set up under the Digital India Corporation (DIC) which will be responsible for developing rules, standards, and guidelines under this Policy. 

The key provisions of the framework policy include: 

• Promoting interoperability among government digital platforms, ensuring data privacy through data anonymization and security, and enhancing citizen access to government services through digital means. 
• The policy e the creation of unified digital IDs, a standardisation in digital processes, and data-sharing guidelines across ministries to improve efficiency. 
• It also focuses on building digital infrastructure, such as cloud services and data centres in order to support e-governance initiatives. 
• Furthermore, it encourages public-private partnerships and sets guidelines for accountability and transparency in digital governance.

Implications and Concerns of the Framework 

• The policy potentially impacts data sharing in India as it mentions data anonymization. The scale of data that would need to be anonymised in India is at a very large scale and it could become a potential challenge to engage in. 
• Data localization and cross-border transfers have raised concerns among global tech companies and trade partners. They argue that such requirements could increase operational costs and hinder cross-border data flows. Striking a balance between protecting national interests and facilitating business operations remains a critical challenge.
• Another challenge associated with the policy is over-data centralization under the IDMO and the potential risks of government overreach in data access.

Key Takeaways and Recommendations

The GDPR in the European Union and the Digital Personal Data Protection Act passed in 2023 in India and many others are the data privacy laws in force in different countries. The policy needs to be aligned with the DPDP Act, 2023 and be updated as per the recent developments. It further needs to maintain transparency over the sharing of data and a user’s control. The policy needs engagement with industry experts, privacy advocates, and civil society to ensure a balance of innovation with privacy and security.

Conclusion

The Draft National Data Governance Framework Policy of 2022 represents a significant stage in shaping India's digital future. It ensures the evolution of data governance evolves alongside technological advancements. The framework policy seeks to foster a robust digital ecosystem that benefits citizens, businesses, and the government alike by focusing on the essentials of data privacy, transparency, and security. However, achieving this vision requires addressing concerns like data centralisation, cross-border data flows, and maintaining alignment with global privacy standards. Continued engagement with stakeholders and necessary updates to the draft policy will be crucial to its success in balancing innovation with user rights and data integrity. The final version of the policy is expected to be released soon.

References

• https://meity.gov.in/writereaddata/files/National-Data-Governance-Framework-Policy.pdf
• https://datareportal.com/?utm_source=DataReportal&utm_medium=Country_Article_Hyperlink&utm_campaign=Digital_2024&utm_term=India&utm_content=Home_Page_Link
• https://www.imf.org/en/Publications/fandd/issues/2023/03/data-by-people-for-people-tiwari-packer-matthan
• https://inc42.com/buzz/draft-national-data-governance-policy-under-finalisation-centre/  
• https://legal.economictimes.indiatimes.com/news/industry/government-unveiled-national-data-governance-policy-in-budget-2023/97680515

‍