US Presidential AI Order and ICMR Data Breach

Introduction

Quantum technology involves the study of matter and energy at the sub-atomic level. This technology uses superposition and entanglement to provide new capabilities in computing, cryptography and communication and solves problems at speeds not possible with classical computers. Unlike classical bits, qubits can exist in a superposition of states, representing 0, 1, or any combination of these states simultaneously. The Union Cabinet approved the National Quantum Mission on 19 April 2023, with a budget allocation of Rs 6000 Crore. The mission will seed, nourish, and scale up scientific and industrial R&D in the domain of quantum technology so that India emerges as one of the leaders in developing quantum technologies and their applications. 

The Union Minister for Science and Technology and Minister of Earth Sciences, Dr. Jitendra Singh announced the selection of 8 start-ups for support under India’s National Quantum Mission and the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS). The selected start-ups represent diverse quantum tech domains and were chosen via a rigorous evaluation process. These startups are poised to be critical enablers in translating quantum research into practical applications. This start-up selection aligns with India’s broader vision for technological self-reliance and innovation by 2047. 

Policy Landscape and Vision

The National Quantum Mission’s main goal is to develop intermediate-scale quantum computers with 50-1000 physical qubits in 8 years, across diverse platforms such as superconducting and photonic technology. The mission deliverables include the development of satellite-based secure quantum communications between ground stations over a range of 2000 km within India, long-distance secure quantum communications with other countries, inter-city quantum key distribution over 2000 km, and multi-node quantum networks with quantum memories.

The National Mission on Interdisciplinary Cyber-Physical Systems aims to promote translational research in Cyber-Physical Systems and associated technologies and prototypes and demonstrates applications for national priorities. The other expectations are enhancing the top-of-the-line research base, human resource development and skill sets in these emerging areas. These missions align with India’s broader ideals such as the Digital India and Make in India campaigns to strengthen India’s technological ecosystem. 

Selected Startups and Their Innovations

The startups selected reflect alignment with India’s National Quantum Mission, oriented towards fostering cutting-edge research and innovation and have industrial applications aiming at placing India as the global leader in quantum technology. The selections are:

• QNu Labs (Bengaluru): is advancing quantum communication by developing end-to-end quantum-safe heterogeneous networks.
• QPiAI India Pvt. Ltd. (Bengaluru): is building a superconducting quantum computer.
• Dimira Technologies Pvt. Ltd. (IIT Mumbai):  is creating indigenous cryogenic cables, essential for quantum computing.
• Prenishq Pvt. Ltd. (IIT Delhi): developing precision diode-laser systems.
• QuPrayog Pvt. Ltd. (Pune): is working on creating optical atomic clocks and related technologies.
• Quanastra Pvt. Ltd. (Delhi): is developing advanced cryogenics and superconducting detectors.
• Pristine Diamonds Pvt. Ltd. (Ahmedabad): is creating diamond materials for quantum sensing.
• Quan2D Technologies Pvt. Ltd. (Bengaluru): is making advancements in superconducting Nanowire Single-photon Detectors.

References

• https://pib.gov.in/PressReleasePage.aspx?PRID=2077635 
• https://www.csis.org/analysis/quantum-technology-applications-and-implications ‍
• https://dst.gov.in/national-quantum-mission-nqm

Executive Summary:

Given that AI technologies are evolving at a fast pace in 2024, an AI-oriented phishing attack on a large Indian financial institution illustrated the threats. The documentation of the attack specifics involves the identification of attack techniques, ramifications to the institution, intervention conducted, and resultant effects. The case study also turns to the challenges connected with the development of better protection and sensibilisation of automatized threats. 

Introduction

Due to the advancement in AI technology, its uses in cybercrimes across the world have emerged significant in financial institutions. In this report a serious incident that happened in early 2024 is analysed, according to which a leading Indian bank was hit by a highly complex, highly intelligent AI-supported phishing operation. Attack made use of AI’s innate characteristic of data analysis and data persuasion which led into a severe compromise of the bank’s internal structures.

Background

The chosen financial institution, one of the largest banks in India, had a good background regarding the extremity of its cybersecurity policies. However, these global cyberattacks opened up new threats that AI-based methods posed that earlier forms of security could not entirely counter efficiently. The attackers concentrated on the top managers of the bank because it is evident that controlling such persons gives the option of entering the inner systems as well as financial information. 

Attack Execution

The attackers utilised AI in sending the messages that were an exact look alike of internal messages sent between employees. From Facebook and Twitter content, blog entries, and lastly, LinkedIn connection history and email tenor of the bank’s executives, the AI used to create these emails was highly specific. Some of these emails possessed official formatting, specific internal language, and the CEO’s writing; this made them very realistic. 

 It also used that link in phishing emails that led the users to a pseudo internal portal in an attempt to obtain the login credentials. Due to sophistication, the targeted individuals thought the received emails were genuine, and entered their log in details easily to the bank’s network, thus allowing the attackers access. 

Impact

It caused quite an impact to the bank in every aspect. Numerous executives of the company lost their passwords to the fake emails and compromised several financial databases with information from customer accounts and transactions. The break-in permitted the criminals to cease a number of the financial’s internet services hence disrupting its functions and those of its customers for a number of days. 

 They also suffered a devastating blow to their customer trust because the breach revealed the bank’s weakness against contemporary cyber threats. Apart from managing the immediate operations which dealt with mitigating the breach, the financial institution was also toppling a long-term reputational hit. 

Technical Analysis and Findings

1. The AI techniques that are used in generation of the phishing emails are as follows: 

•  The attack used powerful NLP technology, which was most probably developed using the large-scaled transformer, such as GPT (Generative Pre-trained Transformer). Since these models are learned from large data samples they used the examples of the conversation pieces from social networks, emails and PC language to create quite credible emails. 

 Key Technical Features: 

•  Contextual Understanding: The AI was able to take into account the nature of prior interactions and thus write follow up emails that were perfectly in line with prior discourse. 
•  Style Mimicry: The AI replicated the writing of the CEO given the emails of the CEO and then extrapolated from the data given such elements as the tone, the language, and the format of the signature line. 
•  Adaptive Learning: The AI actively adapted from the mistakes, and feedback to tweak the generated emails for other tries and this made it difficult to detect. 

2. Sophisticated Spear-Phishing Techniques

Unlike ordinary phishing scams, this attack was phishing using spear-phishing where the attackers would directly target specific people using emails. The AI used social engineering techniques that significantly increased the chances of certain individuals replying to certain emails based on algorithms which machine learning furnished. 

 Key Technical Features: 

•  Targeted Data Harvesting: Cyborgs found out the employees of the organisation and targeted messages via the public profiles and messengers were scraped. 
•  Behavioural Analysis: The latest behaviour pattern concerning the users of the social networking sites and other online platforms were used by the AI to forecast the courses of action expected to be taken by the end users such as clicking on the links or opening of the attachments. 
•  Real-Time Adjustments: These are times when it was determined that the response to the phishing email was necessary and the use of AI adjusted the consequent emails’ timing and content. 

3. Advanced Evasion Techniques

The attackers were able to pull off this attack by leveraging AI in their evasion from the normal filters placed in emails. These techniques therefore entailed a modification of the contents of the emails in a manner that would not be easily detected by the spam filters while at the same time preserving the content of the message. 

Key Technical Features: 

•  Dynamic Content Alteration: The AI merely changed the different aspects of the email message slightly to develop several versions of the phishing email that would compromise different algorithms. 
•  Polymorphic Attacks: In this case, polymorphic code was used in the phishing attack which implies that the actual payloads of the links changed frequently, which means that it was difficult for the AV tools to block them as they were perceived as threats. 
•  Phantom Domains: Another tactic employed was that of using AI in generating and disseminating phantom domains, that are actual web sites that appear to be legitimate but are in fact short lived specially created for this phishing attack, adding to the difficulty of detection. 

4. Exploitation of Human Vulnerabilities

This kind of attack’s success was not only in AI but also in the vulnerability of people, trust in familiar language and the tendency to obey authorities. 

Key Technical Features: 

•  Social Engineering: As for the second factor, AI determined specific psychological principles that should be used in order to maximise the chance of the targeted recipients opening the phishing emails, namely the principles of urgency and familiarity. 
•  Multi-Layered Deception: The AI was successfully able to have a two tiered approach of the emails being sent as once the targeted individuals opened the first mail, later the second one by pretext of being a follow up by a genuine company/personality. 

Response

On sighting the breach, the bank’s cybersecurity personnel spring into action to try and limit the fallout. They reported the matter to the Indian Computer Emergency Response Team (CERT-In) to find who originated the attack and how to block any other intrusion. The bank also immediately started taking measures to strengthen its security a bit further, for instance, in filtering emails, and increasing the authentication procedures. 

 Knowing the risks, the bank realised that actions should be taken in order to enhance the cybersecurity level and implement a new wide-scale cybersecurity awareness program. This programme consisted of increasing the awareness of employees about possible AI-phishing in the organisation’s info space and the necessity of checking the sender’s identity beforehand.

Outcome

Despite the fact and evidence that this bank was able to regain its functionality after the attack without critical impacts with regards to its operations, the following issues were raised. Some of the losses that the financial institution reported include losses in form of compensation of the affected customers and costs of implementing measures to enhance the financial institution’s cybersecurity. However, the principle of the incident was significantly critical of the bank as customers and shareholders began to doubt the organisation’s capacity to safeguard information in the modern digital era of advanced artificial intelligence cyber threats. 

 This case depicts the importance for the financial firms to align their security plan in a way that fights the new security threats. The attack is also a message to other organisations in that they are not immune from such analysis attacks with AI and should take proper measures against such threats.

Conclusion

The recent AI-phishing attack on an Indian bank in 2024 is one of the indicators of potential modern attackers’ capabilities. Since the AI technology is still progressing, so are the advances of the cyberattacks. Financial institutions and several other organisations can only go as far as adopting adequate AI-aware cybersecurity solutions for their systems and data. 

 Moreover, this case raises awareness of how important it is to train the employees to be properly prepared to avoid the successful cyberattacks. The organisation’s cybersecurity awareness and secure employee behaviours, as well as practices that enable them to understand and report any likely artificial intelligence offences, helps the organisation to minimise risks from any AI attack.

Recommendations

1. Enhanced AI-Based Defences: Financial institutions should employ AI-driven detection and response products that are capable of mitigating AI-operation-based cyber threats in real-time. 
2.  Employee Training Programs: CYBER SECURITY: All employees should undergo frequent cybersecurity awareness training; here they should be trained on how to identify AI-populated phishing. 
3.  Stricter Authentication Protocols: For more specific accounts, ID and other security procedures should be tight in order to get into sensitive ones. 
4.  Collaboration with CERT-In: Continued engagement and coordination with authorities such as the Indian Computer Emergency Response Team (CERT-In) and other equivalents to constantly monitor new threats and valid recommendations. 
5.  Public Communication Strategies: It is also important to establish effective communication plans to address the customers of the organisations and ensure that they remain trusted even when an organisation is facing a cyber threat. 

Through implementing these, financial institutions have an opportunity for being ready with new threats that come with AI and cyber terrorism on essential financial assets in today’s complex IT environments.

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Introduction 

AI has revolutionized the way we look at growing technologies. AI is capable of performing complex tasks in fasten time. However, AI’s potential misuse led to increasing cyber crimes. As there is a rapid expansion of generative AI tools, it has also led to growing cyber scams such as Deepfake, voice cloning, cyberattacks targeting Critical Infrastructure and other organizations, and threats to data protection and privacy. AI is empowered by giving the realistic output of AI-created videos, images, and voices, which cyber attackers misuse to commit cyber crimes. 

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It is notable that the rapid advancement of technologies such as generative AI(Artificial Intelligence), deepfake, machine learning, etc. Such technologies offer convenience in performing several tasks and are capable of assisting individuals and business entities. On the other hand, since these technologies are easily accessible, cyber-criminals leverage AI tools and technologies for malicious activities or for committing various cyber frauds. By such misuse of advanced technologies such as AI, deepfake, and voice clones. Such new cyber threats have emerged. 

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What is Deepfake?

Deepfake is an AI-based technology. Deepfake is capable of creating realistic images or videos which in actuality are created by machine algorithms. Deepfake technology, since easily accessible, is misused by fraudsters to commit various cyber crimes or deceive and scam people through fake images or videos that look realistic. By using the Deepfake technology, cybercriminals manipulate audio and video content which looks very realistic but, in actuality, is fake. Voice cloning is also a part of deepfake. To create a voice clone of anyone's, audio can be deepfaked too, which closely resembles a real one but, in actuality, is a fake voice created through deepfake technology. 

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How Deepfake Can Harm Organizations or Enterprises?

• Reputation: Deepfakes have a negative impact on the reputation of the organization. It’s a reputation which is at stake. Fake representations or interactions between an employee and user, for example,  misrepresenting  CEO online, could damage an enterprise’s credibility, resulting in user and other financial losses. To be protective against such incidents of deepfake, organisations must thoroughly monitor online mentions and keep tabs on what is being said or posted about the brand. Deepfake-created content can also be misused to Impersonate leaders, financial officers and officials of the organisation.
• Misinformation: Deepfake can be used to spread misrepresentation or misinformation about the organisation by utilising the deepfake technology in the wrong way. 
• Deepfake Fraud calls misrepresenting the organisation: There have been incidents where bad actors pretend to be from legitimate organisations and seek personal information. Such as helpline fraudsters, fake representatives from hotel booking departments, fake loan providers, etc., where bad actors use voice clones or deepfake-oriented fake video calls in order to propose themselves as belonging to legitimate organisations and, in actuality, they are deceiving people.

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How can organizations combat AI-driven cybercrimes such as deepfake? 

• Cybersecurity strategy: Organisations need to keep in place a wide range of cybersecurity strategies or use advanced tools to combat the evolving disinformation and misrepresentation caused by deepfake technology.  Cybersecurity tools can be utilised to detect deepfakes. 
• Social media monitoring: Social media monitoring can be done to detect any unusual activity. Organisations can select or use relevant tools and implement technologies to detect deepfakes and demonstrate media provenance. Real-time verification capabilities and procedures can be used. Reverse image searches, like TinEye, Google Image Search, and Bing Visual Search, can be extremely useful if the media is a composition of images.
• Employee Training: Employee education on cybersecurity will also play a significant role in strengthening the overall cybersecurity posture of the organisation.

Conclusion

There have been incidents where AI-driven tools or technology have been misused by cybercriminals or bad actors.  Synthetic videos developed by AI are used by bad actors. Generative AI has gained significant popularity for many capabilities that produce synthetic media. There are concerns about synthetic media, such as its misuse of disinformation operations designed to influence the public and spread false information. In particular, synthetic media threats that organisations most often face include undermining the brand, financial gain, threat to the security or integrity of the organisation itself and Impersonation of the brand’s leaders for financial gain.

Synthetic media attempts to target organisations intending to defraud the organisation for financial gain. Example includes fake personal profiles on social networking sites and deceptive deepfake calls, etc. The organisation needs to have the proper cyber security strategy in place to combat such evolving threats. Monitoring and detection should be performed by the organisations and employee training on empowering on cyber security will also play a crucial role to effectively deal with evolving threats posed by the misuse of AI-driven technologies. 

References:

• https://media.defense.gov/2023/Sep/12/2003298925/-1/-1/0/CSI-DEEPFAKE-THREATS.PDF
• https://www.securitymagazine.com/articles/98419-how-to-mitigate-the-threat-of-deepfakes-to-enterprise-organizations

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