#FactCheck - Virat Kohli's Ganesh Chaturthi Video Falsely Linked to Ram Mandir Inauguration

Introduction

The mysteries of the universe have been a subject of curiosity for humans over thousands of years. To solve these unfolding mysteries of the universe, astrophysicists are always busy, and with the growing technology this seems to be achievable. Recently, with the help of Artificial Intelligence (AI), scientists have discovered the depths of the cosmos. AI has revealed the secret equation that properly “weighs” galaxy clusters. This groundbreaking discovery not only sheds light on the formation and behavior of these clusters but also marks a turning point in the investigation and discoveries of new cosmos. Scientists and AI have collaborated to uncover an astounding 430,000 galaxies strewn throughout the cosmos. The large haul includes 30,000 ring galaxies, which are considered the most unusual of all galaxy forms. The discoveries are the first outcomes of the "GALAXY CRUISE" citizen science initiative. They were given by 10,000 volunteers who sifted through data from the Subaru Telescope. After training the AI on 20,000 human-classified galaxies, scientists released it loose on 700,000 galaxies from the Subaru data. 

Brief Analysis

A group of astronomers from the National Astronomical Observatory of Japan (NAOJ) have successfully applied AI to ultra-wide field-of-view images captured by the Subaru Telescope. The researchers achieved a high accuracy rate in finding and classifying spiral galaxies, with the technique being used alongside citizen science for future discoveries.

Astronomers are increasingly using AI to analyse and clean raw astronomical images for scientific research. This involves feeding photos of galaxies into neural network algorithms, which can identify patterns in real data more quickly and less prone to error than manual classification. These networks have numerous interconnected nodes and can recognise patterns, with algorithms now 98% accurate in categorising galaxies.

Another application of AI is to explore the nature of the universe, particularly dark matter and dark energy, which make up over 95% energy of the universe. The quantity and changes in these elements have significant implications for everything from galaxy arrangement.

AI is capable of analysing massive amounts of data, as training data for dark matter and energy comes from complex computer simulations. The neural network is fed these findings to learn about the changing parameters of the universe, allowing cosmologists to target the network towards actual data.

These methods are becoming increasingly important as astronomical observatories generate enormous amounts of data. High-resolution photographs of the sky will be produced from over 60 petabytes of raw data by the Vera C. AI-assisted computers are being utilized for this.

Data annotation techniques for training neural networks include simple tagging and more advanced types like image classification, which classify an image to understand it as a whole. More advanced data annotation methods, such as semantic segmentation, involve grouping an image into clusters and giving each cluster a label.

This way, AI is being used for space exploration and is becoming a crucial tool. It also enables the processing and analysis of vast amounts of data. This advanced technology is fostering the understanding of the universe. However, clear policy guidelines and ethical use of technology should be prioritized while harnessing the true potential of contemporary technology. 

Policy Recommendation

• Real-Time Data Sharing and Collaboration - Effective policies and frameworks should be established to promote real-time data sharing among astronomers, AI developers and research institutes. Open access to astronomical data should be encouraged to facilitate better innovation and bolster the application of AI in space exploration. 
  

• Ethical AI Use - Proper guidelines and a well-structured ethical framework can facilitate judicious AI use in space exploration. The framework can play a critical role in addressing AI issues pertaining to data privacy, AI Algorithm bias and transparent decision-making processes involving AI-based tech. 
• Investing in Research and Development (R&D) in the AI sector - Government and corporate giants should prioritise this opportunity to capitalise on the avenue of AI R&D in the field of space tech and exploration. Such as funding initiatives focusing on developing AI algorithms coded for processing astronomical data, optimising telescope operations and detecting celestial bodies.
• Citizen Science and Public Engagement - Promotion of citizen science initiatives can allow better leverage of AI tools to involve the public in astronomical research. Prominent examples include the SETI @ Home program (Search for Extraterrestrial Intelligence), encouraging better outreach to educate and engage citizens in AI-enabled discovery programs such as the identification of exoplanets, classification of galaxies and discovery of life beyond earth through detecting anomalies in radio waves. 
• Education and Training - Training programs should be implemented to educate astronomers in AI techniques and the intricacies of data science. There is a need to foster collaboration between AI experts, data scientists and astronomers to harness the full potential of AI in space exploration. 
• Bolster Computing Infrastructure - Authorities should ensure proper computing infrastructure should be implemented to facilitate better application of AI in astronomy. This further calls for greater investment in high-performance computing devices and structures to process large amounts of data and AI modelling to analyze astronomical data. 

Conclusion

AI has seen an expansive growth in the field of space exploration. As seen, its multifaceted use cases include discovering new galaxies and classifying celestial objects by analyzing the changing parameters of outer space. Nevertheless, to fully harness its potential, robust policy and regulatory initiatives are required to bolster real-time data sharing not just within the scientific community but also between nations. Policy considerations such as investment in research, promoting citizen scientific initiatives and ensuring education and funding for astronomers. A critical aspect is improving key computing infrastructure, which is crucial for processing the vast amount of data generated by astronomical observatories. 

References

• https://mindy-support.com/news-post/astronomers-are-using-ai-to-make-discoveries/
• https://www.space.com/citizen-scientists-artificial-intelligence-galaxy-discovery
• https://www.sciencedaily.com/releases/2024/03/240325114118.htm
• https://phys.org/news/2023-03-artificial-intelligence-secret-equation-galaxy.html
• https://www.space.com/astronomy-research-ai-future

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Introduction

Deepfake have become a source of worry in an age of advanced technology, particularly when they include the manipulation of public personalities for deceitful reasons. A deepfake video of cricket star Sachin Tendulkar advertising a gaming app recently went popular on social media, causing the sports figure to deliver a warning against the widespread misuse of technology.

Scenario of Deepfake

Sachin Tendulkar appeared in the deepfake video supporting a game app called Skyward Aviator Quest. The app's startling quality has caused some viewers to assume that the cricket legend is truly supporting it. Tendulkar, on the other hand, has resorted to social media to emphasise that these videos are phony, highlighting the troubling trend of technology being abused for deceitful ends.

Tendulkar's Reaction

Sachin Tendulkar expressed his worry about the exploitation of technology and advised people to report such videos, advertising, and applications that spread disinformation. This event emphasises the importance of raising knowledge and vigilance about the legitimacy of material circulated on social media platforms.

The Warning Signs

The deepfake video raises questions not just for its lifelike representation of Tendulkar, but also for the material it advocates. Endorsing gaming software that purports to help individuals make money is a significant red flag, especially when such endorsements come from well-known figures. This underscores the possibility of deepfakes being utilised for financial benefit, as well as the significance of examining information that appears to be too good to be true.

How to Protect Yourself Against Deepfakes

As deepfake technology advances, it is critical to be aware of potential signals of manipulation. Here are some pointers to help you spot deepfake videos:

• Look for artificial facial movements and expressions, as well as lip sync difficulties.
• Body motions and Posture: Take note of any uncomfortable body motions or discrepancies in the individual's posture.
• Lip Sync and Audio Quality: Look for mismatches between the audio and lip motions.
• background and Content: Consider the video's background, especially if it has a popular figure supporting something in an unexpected way.
• Verify the legitimacy of the video by verifying the official channels or accounts of the prominent person.

Conclusion 

The popularity of deepfake videos endangers the legitimacy of social media material. Sachin Tendulkar's response to the deepfake in which he appears serves as a warning to consumers to remain careful and report questionable material. As technology advances, it is critical that individuals and authorities collaborate to counteract the exploitation of AI-generated material and safeguard the integrity of online information.

Reference 

• https://www.news18.com/tech/sachin-tendulkar-disturbed-by-his-new-deepfake-video-wants-swift-action-8740846.html 
• https://www.livemint.com/news/india/sachin-tendulkar-becomes-latest-victim-of-deepfake-video-disturbing-to-see-11705308366864.html 

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Executive Summary:

Traditional Business Email Compromise(BEC) attacks have become smarter, using advanced technologies to enhance their capability. Another such technology which is on the rise is WormGPT, which is a generative AI tool that is being leveraged by the cybercriminals for the purpose of BEC. This research aims at discussing WormGPT and its features as well as the risks associated with the application of the WormGPT in criminal activities. The purpose is to give a general overview of how WormGPT is involved in BEC attacks and give some advice on how to prevent it.

 Introduction

BEC(Business Email Compromise) in simple terms can be defined as a kind of cybercrime whereby the attackers target the business in an effort to defraud through the use of emails. Earlier on, BEC attacks were executed through simple email scams and phishing. However, in recent days due to the advancement of AI tools like WormGPT such malicious activities have become sophisticated and difficult to identify. This paper seeks to discuss WormGPT, a generative artificial intelligence, and how it is used in the BEC attacks to make the attacks more effective.

What is WormGPT?

Definition and Overview

WormGPT is a generative AI model designed to create human-like text. It is built on advanced machine learning algorithms, specifically leveraging large language models (LLMs). These models are trained on vast amounts of text data to generate coherent and contextually relevant content. WormGPT is notable for its ability to produce highly convincing and personalised email content, making it a potent tool in the hands of cybercriminals.

How WormGPT Works

1. Training Data: Here the WormGPT is trained with the arrays of data sets, like emails, articles, and other writing material. This extensive training enables it to understand and to mimic different writing styles and recognizable textual content.

 2. Generative Capabilities: Upon training, WormGPT can then generate text based on specific prompts, as in the following examples in response to prompts. For example, if a cybercriminal comes up with a prompt concerning the company’s financial information, WormGPT is capable of releasing an appearance of a genuine email asking for more details.

 3. Customization: WormGPT can be retrained any time with an industry or an organisation of interest in mind. This customization enables the attackers to make their emails resemble the business activities of the target thus enhancing the chances for an attack to succeed.

Enhanced Phishing Techniques

Traditional phishing emails are often identifiable by their generic and unconvincing content. WormGPT improves upon this by generating highly personalised and contextually accurate emails. This personalization makes it harder for recipients to identify malicious intent.

Automation of Email Crafting

Previously, creating convincing phishing emails required significant manual effort. WormGPT automates this process, allowing attackers to generate large volumes of realistic emails quickly. This automation increases the scale and frequency of BEC attacks.

Exploitation of Contextual Information

WormGPT can be fed with contextual information about the target, such as recent company news or employee details. This capability enables the generation of emails that appear highly relevant and urgent, further deceiving recipients into taking harmful actions.

Implications for Cybersecurity

Challenges in Detection

The use of WormGPT complicates the detection of BEC attacks. Traditional email security solutions may struggle to identify malicious emails generated by advanced AI, as they can closely mimic legitimate correspondence. This necessitates the development of more sophisticated detection mechanisms.

Need for Enhanced Training

Organisations must invest in training their employees to recognize signs of BEC attacks. Awareness programs should emphasise the importance of verifying email requests for sensitive information, especially when such requests come from unfamiliar or unexpected sources.

Implementation of Robust Security Measures

1. Multi-Factor Authentication (MFA): MFA can add an additional layer of security, making it harder for attackers to gain unauthorised access even if they successfully deceive an employee.
2. Email Filtering Solutions: Advanced email filtering solutions that use AI and machine learning to detect anomalies and suspicious patterns can help identify and block malicious emails.
3. Regular Security Audits: Conducting regular security audits can help identify vulnerabilities and ensure that security measures are up to date.

Case Studies

Case Study 1: Financial Institution

A financial institution fell victim to a BEC attack orchestrated using WormGPT. The attacker used the tool to craft a convincing email that appeared to come from the institution’s CEO, requesting a large wire transfer. The email’s convincing nature led to the transfer of funds before the scam was discovered.

Case Study 2: Manufacturing Company

In another instance, a manufacturing company was targeted by a BEC attack using WormGPT. The attacker generated emails that appeared to come from a key supplier, requesting sensitive business information. The attack exploited the company’s lack of awareness about BEC threats, resulting in a significant data breach.

Recommendations for Mitigation

1. Strengthen Email Security Protocols: Implement advanced email security solutions that incorporate AI-driven threat detection.
2. Promote Cyber Hygiene: Educate employees on recognizing phishing attempts and practising safe email habits.
3. Invest in AI for Defense: Explore the use of AI and machine learning in developing defences against generative AI-driven attacks.
4. Implement Verification Procedures: Establish procedures for verifying the authenticity of sensitive requests, especially those received via email.

Conclusion

WormGPT is a new tool in the arsenal of cybercriminals which improved their options to perform Business Email Compromise attacks more effectively and effectively. Therefore, it is critical to provide the defence community with information regarding the potential of WormGPT and its implications for enhancing the threat landscape and strengthening the protection systems against advanced and constantly evolving threats. 

This means the development of rigorous security protocols, general awareness of security solutions, and incorporating technologies such as artificial intelligence to mitigate the risk factors that arise from generative AI tools to the best extent possible.