Red Teaming Generative AI and Quantum Cryptography

Penetration Testing
Generative AI and Quantum
Cryptography
Petar Radanliev
Department of Engineering Science
University of Oxford

Red Teaming
Generative AI/NLP,
the BB84 quantum
cryptography
protocol and the
NIST-approved
Quantum-Resistant
Cryptographic
Algorithms

Red Teaming Generative AI/NLP, the BB84
quantum cryptography protocol and the
NIST-approved Quantum-Resistant
Cryptographic Algorithms
Petar Radanliev1, David De Roure1, Omar Santos2
*Corresponding author email: radanliev@yahoo.com
1Department of Engineering Science, University of Oxford,
2Cisco Systems, RTP, North Carolina, United States

RED TEAMING GENERATIVE
AI/NLP, THE BB84 QUANTUM
CRYPTOGRAPHY PROTOCOL AND
THE NIST-APPROVED QUANTUM-
RESISTANT CRYPTOGRAPHIC
ALGORITHMS

Quantum Computing and
Artificial Intelligence
Abstract: In the contemporary digital age, Quantum
Computing and Artificial Intelligence convergence is
reshaping the cyber landscape, introducing both
unprecedented opportunities and potential vulnerabilities
Keywords: AI/NLP Vulnerability Detection, Quantum -
Resilient Protocols, Automated Quantum Pen-Testing Kits,
AI-Infused Platforms, Theoretical design, Knowledge
development, Cybersecurity, BB84 protocol, Quantum
computing, Cryptographic protocols, Ethics and
Responsibility

Introduction: Quantum
Technology, AI, and the Evolving
Cybersecurity Landscape
In the contemporary technological epoch, the
rapid evolution of Quantum Computing and
Artificial Intelligence is reshaping our digital
realm, expanding the cyber risk horizon
As we stand on the cusp of a quantum revolution,
the cyber-attack surface undergoes a
transformation, heralding a future rife with
potential cyber threats

Theoretical Underpinning
This research endeavours to construct a robust cybersecurity framework, ensuring AI's
harmonious and secure integration with the Quantum Internet
Central to our exploration is evaluating AI/Natural Language Processing models and
their interaction with quintessential quantum security protocols, notably the BB84
method and select NIST-endorsed algorithms
Leveraging the computational prowess of Python and C++, we aim to critically assess
the resilience of these quantum security paradigms by simulating AI -driven cyber-
attacks

Research Objectives
This vision encapsulates our primary objective: to ensure that
the digital advancements of the future, powered by AI, remain
benevolent and secure
This research study is crafted with a primary endeavour to
construct a formidable cybersecurity framework, aiming for
seamless integration between AI and the Quantum Internet
Our focal point lies in the rigorous safety assessments of
AI/NLP models and a comprehensive evaluation of quantum
computing security protocols, notably the BB84 method and
specific algorithms endorsed by NIST

Methodological Approach
Our research methodology is rooted in comprehensive literature reviews,
enabling a profound understanding of the current quantum communication
landscape and the inherent AI risks
We introduce AI elements by integrating Python and C++, probing for
potential vulnerabilities w ithin these security frameworks
Utilising AI models, enriched by datasets from esteemed sources such as
Cornell ArXiv and Penn Treebank, w e simulate cyber -attacks on these
quantum defences to uncover and fortify any detected vulnerabilities
Our objective over a meticulous five -year research trajectory is to champion
the cause of AI integrations that stand beneficial and intrinsically secure

Methodological Approach
Our first step to methodically undertake this challenge involves an
exhaustive literature review, gleaning insights into the present landscape of
quantum communication and associated AI vulnerabilities

Knowledge Dissemination and Broader Implications
We envision a global knowledge-sharing ecosystem, disseminating our findings through
diverse channels, from academic journals to public workshops
As we navigate the quantum future, the pertinence of our research will only amplify,
laying the groundwork for a secure and responsible quantum era
Our overarching aspiration is to ensure that as quantum technology permeates
industries, governments, and societies, its immense power is harnessed judiciously and
securely

DEFINING THE
TERMS AND
INTRODUCING THE
AIMS AND
OBJECTIVES

Cryptography
Good cryptography depends on the hardness of the match
problem
Symmetric key cryptography is when one key is used to encrypt
and decrypt information, and the most well -known standard in
this category is the Advanced Encryption Standard , also known
as Rijndael , based on the name of the creator Vincent Rijmen
Asymmetric cryptography is also known as public -key
cryptography, uses two different keys, one is public key that is
used for encryption and is known to all, and second is the
private key that is used for decryption and is only known by one
party

Cryptography
The most famous algorithm for public-key cryptography is the RSA
cryptosystem developed in 1977 Other well-known and frequently used
algorithms include: the Digital Signature Algorithm , which is based on the
Schnorr and ElGamal signature schemes ; the Diffie–Hellman key exchange
over public channels ; or as others have referred to as a method for ‘secure
communications over insecure channels’ ; or the Elliptic-curve
cryptography that is based on algebraic structure of elliptic curves over
finite fields

Quantum cryptography
Quantum cryptography utilises specific physical law s to enhance the
computational complexity of mathematical algorithms for securing
information
Quantum cryptography exploits the so -called superposition of quantum
particles
The most w ell-known quantum cryptography protocol, "quantum key
distribution" , involves the transmission of a random sequence of quantum
bits or "qubits" betw een tw o parties
The best -known QKD is the BB84 protocol published by Bennett and
Brassard in 1984 IoT devices and other embedded systems w ith limited
computational pow er can find it particularly challenging to generate strong
cryptographic keys today

Aims and objectives
Risk scenario one is a future large-scale quantum computer that can be
used to attack the progress and development of protocol and hardware
implementation
Risk scenario two is what we can describe as a ‘time-travel’ attack, which
means that a future large-scale quantum computer can go back in time and
rewrite history, it could forge medical records and replace existing patient
records, it could cause a denial of service, or even replace the complete
history

Methodology to determine the
importance of the study
Our study is underpinned by the seminal pronouncements made at
the Black Hat and DEF CON 31 conferences by governmental
dignitaries and titans of the tech world
At DEF CON 31, a congregation witnessing our active participation
and logistical contribution in the Red Hat Village, the hacking
cohort, and pivotal stakeholders in Generative AI discourse
underwent a paradigmatic shift
On Black Hat's concluding day, the White House unexpectedly
disclosed its collaborative venture with AI luminaries - including
OpenAI, Google, Antrhopic, Hugging Face, Microsoft, Nvidia, and
Stability AI, culminating in a public appraisal of generative AI
ecosystems at DEF CON

Methodology to determine the quality of
the study
Our postulate asserts that a specialised red team approach,
amalgamating AI/NLP blueprints with the quantum cryptographic
tenets of the BB84 protocol and NIST-sanctioned algorithms,
unveils latent security lacunae, thereby fortifying quantum
internet infrastructure
Through the synergistic capabilities of C++ and Python, our
investigation is poised for intricate depth and adaptability to
surmount multifaceted quantum cryptographic enigmas
The methodological core is anchored in the versatile roles of
Python and C++, exemplifying their composite prowess in
achieving strategic orchestration and granular computational
might

Methodology to determine the potential impact
The expanding acclaim of large language models like ChatGPT indicates a
transformative phase in textual and communicative paradigms
In accord and conjunction with the White House's Office of Science, Technology, and
Policy, we are poised to helm a research expedition dedicated to the forensic
assessment of these emergent generative AI constructs
With the White House's explicit endorsement for such autonomous evaluative
endeavours , we posit our methodology, rooted in Red Teaming paradigms, as a beacon
aligning with the foundational principles of the Biden administration's AI Bill of Rights
and the AI Risk Management edicts decreed by the National Institute of Standards and
Technology

Timeliness Given Current Trends, Context, and Needs
During DEF CON 31, the AI Village's founder accentuated a crucial challenge: the
prevailing issues with Generative AI models remain unresolved owing to a knowledge
gap in their red team evaluation
Building upon insights from the PETRAS project , our study develops the design for
executing the UK's most comprehensive red team exercise on select AI models
Our study will differentiate from contemporaneous endeavours by targeting quantum
cryptography, emphasising the BB84 protocol and NIST's Quantum -Resistant
Cryptographic Algorithms

Impacts on World-leading Research, Society, Economy, or the
Environment
The intricacies of securing Large Language Models became strikingly
evident at DEF CON 31, where participants interacted with LLMs in a
controlled environment
Given DEF CON's massive participation, our research, conducted under the
stringent ethical and privacy standards of the University of Oxford, offers a
more secure avenue for assessing LLM vulnerabilities than a convention -
based approach

Impacts on World-leading Research, Society, Economy, or the
Environment
In Figure 2, the flowchart provides a visual representation of the research
methodology, starting with the initial research proposal and moving
through various stages, including theoretical design, background research,
objectives definition, model training, environment setup, penetration
testing, data collection, anomaly detection, reverse engineering, and
feedback integration

Review of Novel AI and Quantum technologies and their significance
The new design for penetration testing of Generative AI and Quantum computing can
produce several novel technologies in vulnerability management that could have wide -
ranging impacts
Advanced AI/NLP models focused on vulnerability detection in cryptographic algorithms
would be a significant step forward in cybersecurity
Our proposed design is poised to unveil new vulnerabilities, leading to improved
security of new technologies in the domain of vulnerability management, with potential
reverberations across diverse sectors

Red Teaming design
Identifyi ng v ulnerabilitie s in cryptog ra ph ic systems is critical for secure
communicati on in the digital age
T his approach lev erages Art if ici al Intelligence and Natural Language Processing
techniques to detect w eaknesses in cryptogr ap hi c algorithms
AI-d r iv en methods hav e the potential to redefine cybersecur it y standards,
making systems more reliable and secure
T raditional cryptogr ap hi c systems are v ulnerable to quantum computers, making
it necessary to dev elop quantum -res il ien t protocols to ensure safe
communicati on in a post -quantu m w orld
Cutting -e dg e solutions hav e emerged to tackle cybersecur i t y challenges,
harnessing the pow er of AI to optimise rev erse engineerin g tasks and facilitate
payload deliv ery systems that combat quantum exploits

Ethical penetration testing
Our primary objective is to establish a strong and reliable framework for the upcoming quantum internet era
We aim to ensure that all data transmissions remain secure and tamper -proof, w hich is crucial for building trust
in digital communication
We aim to foster an environment of cooperation w here shared know ledge is the driving force behind the
development of quantum -safe innovations
Our main goal is to navigate this unexplored territory and lay the foundation for a future w here the immense
potential of quantum computing can be fully realised w hile minimising any risks that may arise
Our objective is to strengthen the quantum internet and usher in a new era of research and innovation

RED TEAMING
DESIGN –
PENETRATION
TESTING DESIGN

Prototyping &
Development
I n o u r p u r s u i t t o e n h a n c e q u a n t u m c r y p t o g r a p h i c p r o t o c o l s , w e h a v e
s t r a t e g i c a l l y h a r n e s s e d t h e c o m b i n e d s t r e n g t h s o f P y t h o n a n d C + +
O u r f o c u s r e m a i n s o n t h e a d a p t a t i o n a n d e l e v a t i o n o f t h e r e n o w n e d B B 8 4
p r o t o c o l a n d o t h e r N I S T - e n d o r s e d q u a n t u m c r y p t o g r a p h i c m e t h o d o l o g i e s ,
a l g o r i t h m s , , a n d c r y p t o g r a p h i c m e c h a n i s m s ,
O u r a p p r o a c h t o m o d e l d e v e l o p m e n t i s r o o t e d i n l e v e r a g i n g c u t t i n g - e d g e A I / N L P
m o d e l s
U n d e r t h e u m b r e l l a o f G e n e r a t i v e A I / N L P I n t e g r a t i o n , o u r o b j e c t i v e i s t o e m p l o y
G e n e r a t i v e A I i n s i m u l a t i n g b o t h c o n v e n t i o n a l a n d m a l e v o l e n t u s e r b e h a v i o u r s
w i t h i n a q u a n t u m n e t w o r k e n v i r o n m e n t
O u r m e t h o d o l o g y i s a n c h o r e d i n i m p l e m e n t i n g a v a n t - g a r d e N L P t e c h n i q u e s , w i t h
a s p e c i f i c e m p h a s i s o n t r a n s f o r m e r - b a s e d m o d e l s s u c h a s G P T v a r i a n t s

Prototyping & Development
We aim to replicate the BB84 quantum key distribution protocol
meticulously, facilitating AI interactions

Theoretical Framework for Real-
world Quantum Network Testing:
Field Testing and Validation
Q u a n t u m N e t w o r k D y n a m i c s : D r a w i n g f r o m f o u n d a t i o n a l p r i n c i p l e s o f q u a n t u m
m e c h a n i c s a n d n e t w o r k t h e o r y , w e p o s t u l a t e q u a n t u m n e t w o r k s ' p o t e n t i a l
b e h a v i o u r s a n d c h a l l e n g e s i n r e a l - w o r l d s e t t i n g s
U s e r I n t e r a c t i o n w i t h Q u a n t u m S y s t e m s : G r o u n d e d i n h u m a n - c o m p u t e r
i n t e r a c t i o n t h e o r i e s , w e e x p l o r e t h e n u a n c e s o f e n d - u s e r e n g a g e m e n t w i t h
q u a n t u m s y s t e m s , f o c u s i n g o n u s a b i l i t y a n d p o t e n t i a l u s e r - t r i g g e r e d
v u l n e r a b i l i t i e s
C o l l a b o r a t i v e S i m u l a t i o n s : B y p a r t n e r i n g w i t h i n d u s t r y l e a d e r s , w e a i m t o
s i m u l a t e a u t h e n t i c n e t w o r k s c e n a r i o s , b r i d g i n g t h e g a p b e t w e e n t h e o r e t i c a l
p o s t u l a t i o n s a n d p r a c t i c a l a p p l i c a t i o n s

Theoretical Framework for Real-
world Quantum Network Testing:
Field Testing and Validation
S y n t h e t i c D a t a G e n e r a t i o n : T h i s a p p r o a c h , r o o t e d i n p r e d i c t i v e m o d e l l i n g ,
s e e k s t o e m u l a t e f u t u r e q u a n t u m n e t w o r k b e h a v i o u r s , o f f e r i n g i n s i g h t s i n t o
p r o s p e c t i v e c h a l l e n g e s a n d s o l u t i o n s
A I / N L P - D r i v e n Q u a n t u m N e t w o r k B e h a v i o u r s : I n t e g r a t i n g A I / N L P m o d e l s w i t h
q u a n t u m s i m u l a t i o n s o f f e r s a n o v e l p e r s p e c t i v e o n n e t w o r k t r a f f i c b e h a v i o u r s ,
b o t h t y p i c a l a n d a d v e r s a r i a l
U s e r - C e n t r i c Q u a n t u m S y s t e m D e s i g n : B y u n d e r s t a n d i n g e n d - u s e r i n t e r a c t i o n s
a n d f e e d b a c k , w e c a n t h e o r i s e o p t i m a l d e s i g n s f o r q u a n t u m s y s t e m s t h a t a r e
b o t h s e c u r e a n d u s e r - f r i e n d l y
P e r f o r m a n c e M e t r i c s i n Q u a n t u m N e t w o r k s : W e c a n d e v e l o p t h e o r i e s o n o p t i m a l
q u a n t u m n e t w o r k d e s i g n s b y i d e n t i f y i n g k e y i n d i c a t o r s s u c h a s d e t e c t i o n
e f f i c a c y a n d s y s t e m r o b u s t n e s s

Theoretical Framework for Real-world Quantum Network Testing: Field
Testing and Validation
User Feedback Analysis: A qualitative exploration of user feedback will
contribute to the theoretical understanding of user needs, challenges, and
potential system improvements in the quantum realm

Theoretical Framework for Post-
Evaluation and Iterative
Enhancement in Quantum-AI
Systems
I t e r a t i v e Q u a n t u m - A I S y s t e m D e s i g n : D r a w i n g f r o m i t e r a t i v e d e s i g n p r i n c i p l e s ,
w e p o s t u l a t e t h e s i g n i f i c a n c e o f c o n t i n u o u s r e f i n e m e n t i n q u a n t u m - A I s y s t e m s ,
e n s u r i n g t h e i r a d a p t a b i l i t y a n d r e s i l i e n c e
D o c u m e n t a t i o n a n d S t a n d a r d i s a t i o n i n Q u a n t u m R e s e a r c h : G r o u n d e d i n r e s e a r c h
d o c u m e n t a t i o n t h e o r i e s , w e e x p l o r e t h e i m p o r t a n c e o f t r a n s p a r e n t , r e p l i c a b l e ,
a n d s t a n d a r d i s e d r e s e a r c h p r a c t i c e s i n t h e q u a n t u m - A I d o m a i n
F e e d b a c k - D r i v e n D a t a C o l l e c t i o n : B y h a r n e s s i n g d a t a f r o m f i e l d t e s t i n g , U A T
f e e d b a c k , a n d e m e r g i n g r e s e a r c h , w e a i m t o c r e a t e a c o m p r e h e n s i v e d a t a s e t
t h a t i n f o r m s t h e i t e r a t i v e d e s i g n p r o c e s s

Systems
A n a l y t i c a l T o o l s a n d T e c h n i q u e s : U t i l i s i n g P y t h o n ' s a n a l y t i c a l c a p a b i l i t i e s a n d
C + + ' s c o m p u t a t i o n a l s t r e n g t h s , w e p r o p o s e a m e t h o d o l o g i c a l a p p r o a c h t o
s y s t e m a t i c a l l y i d e n t i f y a n d a d d r e s s a r e a s o f i m p r o v e m e n t
C o n t i n u o u s Q u a n t u m - A I S y s t e m O p t i m i s a t i o n : I n t e g r a t i n g f e e d b a c k a n d
p e r f o r m a n c e m e t r i c s , w e t h e o r i s e a n O p t i m i s a t i o n l o o p t h a t e n s u r e s t h e
e v o l u t i o n a n d r e l e v a n c e o f q u a n t u m - A I s y s t e m s
R e s e a r c h D o c u m e n t a t i o n i n Q u a n t u m C o m p u t i n g : B y c o l l a t i n g r e s e a r c h n o t e s ,
d a t a s e t s , a n d e v a l u a t i o n s , w e p r o p o s e a s t r u c t u r e d a p p r o a c h t o d o c u m e n t i n g
q u a n t u m - A I r e s e a r c h , e n s u r i n g i t s t r a n s p a r e n c y , r e p l i c a b i l i t y , a n d r e l e v a n c e f o r
f u t u r e e n d e a v o u r s

Systems
Performance Metrics in Iterative Design: By comparing
post-optimisation metrics against established
benchmarks, w e aim to develop theories on the
effectiveness of iterative design in quantum-AI systems
Peer Review in Quantum Research Documentation: A
qualitative exploration of peer reviews w ill contribute to
the theoretical understanding of research transparency,
comprehensibility, and replicability in the quantum-AI
domain

Theoretical Framework for Collaborative Red
Teaming in Quantum-AI Systems
Stakeholder-Centric Red Teaming: Draw ing from stakeholder theory, w e
postulate the significance of continuous engagement w ith key stakeholders
in shaping and refining the red teaming process
Adaptive Threat Landscapes: Grounded in adaptive systems theory, w e
explore the dynamics of threat environments that evolve in real -time,
informed by AI/NLP feedback
Countermeasure Design and Iteration: Leveraging iterative design
principles, w e delve into the processes of identifying vulnerabilities and
crafting efficient countermeasures
Collaborative AI Learning: Based on collaborative learning theories, w e
propose harnessing the collective intelligence of multiple AI models and
expert insights to enhance threat simulation realism

Theoretical Framework for Collaborative Red
Teaming in Quantum-AI Systems
Stakeholder Engagement Platforms: We use communication platforms for
virtual engagements and Python -based tools for collaborative data
analysis to create a comprehensive feedback mechanism
Real-time AI/NLP Feedback Systems: We envision a dynamic threat
environment that mirrors advanced persistent threats by allowing AI
models to adapt their strategies
Feedback-Driven Red Teaming: Integrating continuous stakeholder
feedback, w e theorise a red teaming approach that is both responsive and
comprehensive
Adaptive AI Threat Simulations: By allowing AI models to learn from their
actions, w e propose a threat simulation that evolves in real time, offering
a more realistic representation of potential threats

Theoretical Framework for
Collaborative Red Teaming in
Quantum-AI Systems
Iterative Countermeasure Design: Draw ing from the
identified vulnerabilities, w e theorise an iterative
approach to countermeasure design, ensuring maximum
efficiency and adaptability
Ensemble Learning in Red Teaming: By pooling
know ledge from diverse AI models and expert insights,
w e propose a collaborative learning approach that
enhances the realism and depth of threat simulations

Theoretical Framework for Quantum Network
Behaviour Simulation and Refinement
Environment Scanning and Validation: By deploying Python
scripts, we theorise an approach to scan and validate the quantum
environment, ensuring its isolation and integrity
Efficient Quantum Simulation Development: Utilising C++'s
computational strengths, we propose the creation of a robust
quantum simulation backbone, overlaid with Python's scripting
capabilities for enhanced control and variability
Iterative Quantum Environment Optimisation: Drawing from
feedback loop theories, we postulate an iterative refinement
approach for the quantum environment, leveraging AI insights to
identify and rectify areas of enhancement

Continuous Quantum Environment Monitoring: Python's
statistical and ML capabilities will be harnessed to establish
behavioural baselines and detect deviations, complemented by
C++'s efficiency for real-time anomaly detection
Exploit Analysis Tools: Tools like Radare2's r2pipe API, IDA
Pro, and Ghidra will be instrumental in dissecting and
understanding the intricacies of detected exploits
Dashboard Development for Real-time Insights: Visualisation
libraries like Matplotlib, Seaborn, or Dash will be pivotal in
presenting key metrics and findings

Theoretical Framework for Quantum Network Behaviour Simulation
and Refinement
Post-Testing Review Mechanisms: Python's data analysis and visualisation capabilities
will be harnessed to dissect findings and inform the review process, complemented by
interactive tools like Jupyter Notebooks
Rapid Implementation of Feedback: C++'s efficiency will be pivotal in swiftly
implementing changes to simulation environments and AI interaction routines, ensuring
quantum systems remain resilient against evolving threats
Feedback Integration in Quantum Red Teaming: By continuously gathering and
integrating feedback, we theorise an approach that ensures red teaming strategies
remain updated and relevant, addressing the ever -evolving threat landscape

Interactive Quantum Red Teaming Reporting: Utilising
Python's Jupyter Notebooks, we propose a comprehensive
reporting methodology that offers clear insights,
narratives, and actionable findings from red teaming
activities
Swift Quantum System Refinements: Drawing from rapid
development principles, we postulate an approach that
swiftly implements feedback-driven changes, ensuring
quantum systems' resilience against contemporary threats

Discussion: Societal Benefits from Penetration Testing of Generative
AI and Quantum Computing
In today's rapidly evolving technological landscape, society must stay ahead of the curve and
ensure that the systems and solutions being developed are secure and advanced
One of the key areas of focus in this regard is quantum cryptography initiatives
By investing in research and development in this field, we can create solutions that are more
resistant to attacks and provide more security for individuals and organisations
Another important aspect of ensuring a safe digital environment is to examine the intricacies of the
AI threat landscape, particularly within quantum frameworks
By understanding the potential vulnerabilities and risks associated with these technologies, we
can better address and mitigate AI-driven cyber threats

This endeavour has the potential to bridge gaps between academia, technology giants, and
cybersecurity experts, leading to holistic solutions, knowledge sharing, and a more
interconnected and informed society
Investing in quantum cryptography initiatives and examining the AI threat landscape are
crucial to ensuring a safe and advanced technological future for us all
In the dynamic fields of quantum mechanics and cybersecurity, it is critical to consistently
fine-tune cryptographic protocols in response to emerging vulnerabilities
We utilise ethical theories and AI principles to investigate the importance of this alignment

Our first approach involves identifying vulnerabilities and refining
cryptographic protocols to address the ever-evolving threat landscape

Conclusion: Towards a
Secure Quantum-AI
Future
U p o n d e l v i n g d e e p e r i n t o t h e i n t r i c a t e i n t e r p l a y b e t w e e n Q u a n t u m
C o m p u t i n g , A r t i f i c i a l I n t e l l i g e n c e , a n d c yb e r s e c u r i t y, w e c a n
g l e a n s o m e n o t e w o r t h y i n s i g h t s
T h e s e t h r e e d o m a i n s a r e i n e x t r i c a b l y l i n k e d , a s t h e u n p r e c e d e n t e d
c o m p u t a t i o n a l p o w e r o f q u a n t u m c o m p u t i n g c a n g r e a t l y e n h a n c e A I
c a p a b i l i t i e s , w h i c h i n t u r n c a n b e h a r n e s s e d t o b o l s t e r
c yb e r s e c u r i t y m e a s u r e s
O u r r e s e a r c h u n d e r s c o r e s t h e i m p e r a t i v e o f p r o a c t i v e
c yb e r s e c u r i t y m e a s u r e s , e n s u r i n g t h a t t h e i m m e n s e p o w e r o f
q u a n t u m t e c h n o l o g y i s h a r n e s s e d j u d i c i o u s l y a n d s e c u r e l y

Limitations
Scope of Study: Our research primarily focused on the BB84 protocol and
specific NIST-approved algorithms
Data Limitations: The AI models w ere trained using datasets like Cornell
ArXiv and Penn Treebank
Technological Constraints: Our reliance on Python and C++ for
simulations, w hile efficient, might not capture the intricacies or
vulnerabilities present in other programming environments or real -world
quantum systems
Red Teaming Limitations: While our red teaming approach simulated
potential hacker activities, real -world cyber threats can be more diverse,
sophisticated, and unpredictable than those replicated in controlled
environments

Limitations
Generalisability: The findings, while pertinent to the
conditions and parameters of our study, might not be
universally applicable across different quantum or AI
configurations or in varied geopolitical or
technological contexts
Temporal Limitations: The rapid evolution of both
quantum computing and AI means that our findings,
though relevant now, may require periodic re-
evaluation to remain current in the face of
technological advancements

Red Teaming Generative AI and Quantum Cryptography

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