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Introduction

Quantum mechanics is not a new field. It finds its roots in the works of physicists such as Niels Bohr in the 1920s, and has informed the development of technologies like nuclear power in the past. But with developments in science and engineering, we are at the cusp of harnessing quantum mechanics for a new wave of real-world uses in sensing and metrology, computing, networking, security, and more. While at different stages of development, quantum technologies have the potential to revolutionise global security, economic systems, and digital infrastructure. The science is dazzling, but it is equally urgent to start preparing for its broader impact on society, especially regarding privacy and digital security. This article explores quantum computing, its threat to information integrity, and global interdependencies as they exist today, and discusses policy areas that should be addressed.

What Is Quantum Computing?

Classical computers use binary bits (0 or 1) to represent and process information. This binary system forms the base of modern computing. But quantum computers use qubits (quantum bits) as a basic unit, which can exist in multiple states ( 0, 1, both, or with other qubits) simultaneously due to quantum principles like superposition and entanglement. This creates an infinite range of possibilities in information processing and allows quantum machines to perform complex computations at speeds impossible for traditional computers. While still in their early stages, large-scale quantum computers could eventually:

1. Break modern encryption systems
2. Model complex molecules for drug discovery
3. Optimise global logistics and financial systems
4. Accelerate AI and machine learning

While this could eventually present significant opportunities in fields such as health innovation, material sciences, climate modelling, and cybersecurity, challenges will continue to arise even before the technology is ready for commercial application. Policymakers must start anticipating their impact.

Threats

Policy solutions surrounding quantum technologies will depend on the pace of development of the elements of the quantum ecosystem. However, the most urgent concerns regarding quantum computing applications are the risk to encryption and the impact on market competition.

1. Cybersecurity Threat: Digital infrastructure today (e.g., cloud services, networks, servers, etc.) across sectors such as government, banking and finance, healthcare, energy, etc., depends on encryption for secure data handling and communications. Threat actors can utilise quantum computers to break this encryption. Widely used asymmetric encryption keys, such as RSA or ECC, are particularly susceptible to being broken. Threat actors could "harvest now, decrypt later”- steal encrypted data now and decrypt it later when quantum capabilities mature. Although AES-256, a symmetric encryption standard, is currently considered resistant to quantum decryption, it only protects data after a secure connection is established through a process that today relies on RSA or ECC. This is why governments and companies are racing to adopt Post- Quantum Cryptography (PQC) and quantum key distribution (QKD) to protect security and privacy in digital infrastructure.

2. Market Monopoly: Quantum computing demands significant investments in infrastructure, talent, and research, which only a handful of countries and companies currently possess. As a result, firms that develop early quantum advantage may gain unprecedented competitive leverage through offerings such as quantum-as-a-service, disrupting encryption-dependent industries, or accelerating innovation in pharmaceuticals, finance, and logistics. This could reinforce the existing power asymmetries in the global digital economy. Given these challenges, proactive and forward-looking policy frameworks are critical.

What Should Quantum Computing Policy Cover?

Commercial quantum computing will transform many industries. Policy will have to be flexible and be developed in iterations to account for fast-paced developments in the field. It will also require enduring international collaboration to effectively address a broad range of concerns, including ethics, security, privacy, competition, and workforce implications.

1. Cybersecurity and Encryption: Quantum policy should prioritise the development and standardisation of quantum-resistant encryption methods. This includes ongoing research into Post-Quantum Cryptography (PQC) algorithms and their integration into digital infrastructure. Global policy will need to align national efforts with international standards to create unified quantum-safe encryption protocols.

2. Market Competition and Access: Given the high barriers to entry, regulatory frameworks should promote fair competition, enabling smaller players like startups and developing economies to participate meaningfully in the quantum economy. Frameworks to ensure equitable access, interoperability, and fair competition will become imperative as the quantum ecosystem matures so that society can reap its benefits as a whole.

4. Ethical Considerations: Policymakers will have to consider the impact on privacy and security, and push for the responsible use of quantum capabilities. This includes ensuring that quantum advances do not contribute to cybercrime, disproportionate surveillance, or human rights violations.

5. International Standard-Setting: Setting benchmarks, shared terminologies, and measurement standards will ensure interoperability and security across diverse stakeholders and facilitate global collaboration in quantum research and infrastructure.

6. Military and Defence Implications: Militarisation of quantum technologies is a growing concern, and national security affairs related to quantum espionage are being urgently explored. Nations will have to develop regulations to protect sensitive data and intellectual property from quantum-enabled attacks.

7. Workforce Development and Education: Policies should encourage quantum computing education at various levels to ensure a steady pipeline of talent and foster cross-disciplinary programs that blend quantum computing with fields like machine learning, AI, and engineering.

8. Environmental and Societal Impact: Quantum computing hardware requires specialised conditions such as extreme cooling. Policy will have to address the environmental footprint of the infrastructure and energy consumption of large-scale quantum systems. Broader societal impacts of quantum computing, including potential job displacement, accessibility issues, and the equitable distribution of quantum computing benefits, will have to be explored.

Conclusion

Like nuclear power and AI, the new wave of quantum technologies is expected to be an exciting paradigm shift for society. While they can bring numerous benefits to commercial operations and address societal challenges, they also pose significant risks to global information security. Quantum policy will require regulatory, strategic, and ethical frameworks to govern the rise of these technologies, especially as they intersect with national security, global competition, and privacy. Policymakers must act in collaboration to mitigate unethical use of these technologies and the entrenchment of digital divides across countries. The OECD’s Anticipatory Governance of Emerging Technologies provides a framework of essential values like respect for human rights, privacy, and sustainable development, which can be used to set a baseline, so that quantum computing and related technologies benefit society as a whole.

References

• https://www.weforum.org/stories/2024/07/explainer-what-is-quantum-technology/
• https://www.paconsulting.com/insights/what-is-quantum-technology
• https://delinea.com/blog/quantum-safe-encryption#:~:text=This%20can%20result%20in%20AES,%2D128%20to%20AES%2D256.
• https://www.oecd.org/en/publications/a-quantum-technologies-policy-primer_fd1153c3-en.html

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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

Attempts at countering the spread of misinformation can include various methods and differing degrees of engagement by different stakeholders. The inclusion of Artificial Intelligence, user awareness and steps taken on the part of the public at a larger level, focus on innovation to facilitate clear communication can be considered in the fight to counter misinformation. This becomes even more important in spaces that deal with matters of national security, such as the Indian army.

IIT Indore’s Intelligent Communication System

As per a report in Hindustan Times on 14th November 2024, IIT Indore has achieved a breakthrough on their project regarding Intelligent Communication Systems. The project is supported by the Department of Telecommunications (DoT), the Ministry of Electronics and Information Technology (MeitY), and the Council of Scientific and Industrial Research (CSIR), as part of a specialised 6G research initiative (Bharat 6G Alliance) for innovation in 6G technology.

Professors at IIT Indore claim that the system they are working on has features different from the ones currently in use. They state that the receiver system can recognise coding, interleaving (a technique used to enhance existing error-correcting codes), and modulation methods together in situations of difficult environments, which makes it useful for transmitting information efficiently and securely, and thus could not only be used for telecommunication but the army as well. They also mention that previously, different receivers were required for different scenarios, however, they aim to build a system that has a single receiver that can adapt to any situation.

Previously, in another move that addressed the issue of misinformation in the army, the Ministry of Defence designated the Additional Directorate General of Strategic Communication in the Indian Army as the authorised officer to issue take-down notices regarding instances of posts consisting of illegal content and misinformation concerning the Army. 

Recommendations

Here are a few policy implications and deliberations one can explore with respect to innovations geared toward tackling misinformation within the army:

1. Research and Development: In this context, investment and research in better communication through institutes have enabled a system that ensures encrypted and secure communication, which helps with ways to combat misinformation for the army.
2. Strategic Deployment: Relevant innovations can focus on having separate pilot studies testing sensitive data in the military areas to assess their effectiveness.
3. Standardisation: Once tested, a set parameter of standards regarding the intelligence communication systems used can be encouraged.
4. Cybersecurity integration: As misinformation is largely spread online, innovation in such fields can encourage further exploration with regard to integration with Cybersecurity.

Conclusion

The spread of misinformation during modern warfare can have severe repercussions. Sensitive and clear data is crucial for safe and efficient communication as a lot is at stake. Innovations that are geared toward combating such issues must be encouraged, for they not only ensure efficiency and security with matters related to defence but also combat misinformation as a whole.

References

1. https://timesofindia.indiatimes.com/city/indore/iit-indore-unveils-groundbreaking-intelligent-receivers-for-enhanced-6g-and-military-communication-security/articleshow/115265902.cms
2. https://www.hindustantimes.com/technology/6g-technology-and-intelligent-receivers-will-ease-way-for-army-intelligence-operations-iit-official-101731574418660.html