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Dr Priyanka Singh
Dr

Priyanka Singh

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Overview

Background

I am a passionate researcher with a background in computer science and a strong commitment to leveraging technology for the betterment of society. I hold a PhD in Image Forensics and have had the privilege of conducting postdoctoral research at prestigious institutions such as SUNY Albany and Dartmouth College, where I had the opportunity to collaborate closely with Prof. Hany Farid.

During my postdoc at Dartmouth College, I focused my research efforts on addressing a critical societal issue - real-time child pornography detection. This research not only garnered recognition within the academic community but also earned praise from luminaries like Prof. Ramesh Raskar at MIT, who invited me to share my insights through a talk at MIT.

I primarily works in the area of Cyber Security, Digital Forensics, Privacy and Security Aspects, Homomorphic Encryption and Cloud Computing.

As I continue my research journey, I remain committed to making a positive impact through innovation and collaboration. I am excited about the opportunities that lie ahead and the potential for technology to create a safer and more inclusive world.

Availability

Dr Priyanka Singh is:
Available for supervision

Qualifications

  • Bachelor of Information Technology, Uttar Pradesh Technical University
  • Masters (Research) of Image Processing, Motilal Nehru National Institute of Technology
  • Doctor of Philosophy of Image Processing, Motilal Nehru National Institute of Technology

Research interests

  • Towards Mitigation of AI Based Attacks

    The adoption of Artificial Intelligence (AI) has made a paradigmatic shift in the cybersecurity challenges. On the positive side, AI enables faster detection of anomalies, automated responses to attacks, and predictive threat modeling. This helps organisations to proactively combat cyber threats and minimise the impact of attacks. On the contrary, the integration of AI also opens new avenues for adversaries. Cybercriminals are increasingly leveraging AI to craft sophisticated attacks, such as automated phishing schemes, deepfake technology, and AI-driven malware that can adapt to traditional defence mechanisms. The existing cybersecurity frameworks lack adequate update to address this sophistication.

  • Facilitating confidential and effective Cyber Threat Intelligence sharing

    Cyber Threat Intelligence (CTI) data is shared 24/7 between industry organisations and government agencies to provide incident responders real-time information about attackers' tactics and origins. Theoretically, this collaborative approach uplifts sectors’ cyber resilience but in reality, CTI sharing is often done inefficiently and ineffectively due to organisations' reticence to share full information which may unknowingly reveal organisational data (e.g., to competing or unknown entities within the community). This project aims to urgently address these challenges through a secure, collaborative CTI sharing approach with robust privacy protection built for AI-driven cybersecurity systems facilitating swift sector-wide incident response.

  • Security and Privacy of Large Language Models

    As Large Language Models (LLMs) become increasingly pervasive in applications ranging from natural language understanding to creative content generation, the need for robust privacy protections becomes more critical. These models, which are trained on vast amounts of data, raise significant concerns regarding data security, user privacy, and ethical implications. This project aims to explore the privacy challenges inherent in LLMs, addressing both technical and legal dimensions while highlighting best practices for privacy-preserving AI development.

  • Combat Propagation of Dis/Misinformation on Social Media

    Disinformation refers to deliberate misleading of people by manipulating narrative or facts. The unprecedented propagation of disinformation on social media can influence one’s mindset and cause an adverse impact on the society. AI-enabled tracking of the entire pipeline of disinformation by identifying the source, the target audience, the hidden agenda, the media of propagation, and the kind of influence can potentially combat this problem by reverse-identification of the origin of disinformation narratives and helping authorities to address the falsification problem.

  • From Prediction to Explanation: Multimodal, Explainable, and Interactive Deepfake Detection Framework for Non-Expert Users

    The proliferation of deepfake technologies poses urgent challenges and serious risks to digital integrity, particularly within critical sectors such as forensics, journalism, and the legal system. While existing detection systems have made significant progress in classification accuracy, they typically function as black-box models-offering limited transparency and minimal support for human reasoning. This lack of interpretability hinders their usability in real-world decision-making contexts, especially for non-expert users.

Research impacts

My work focusses on using cutting-edge technology to tackle real-world challenges, particularly in the realm of online safety and security. I am driven by the belief that responsible and ethical technology can play a transformative role in protecting the most vulnerable in our society.

Works

Search Professor Priyanka Singh’s works on UQ eSpace

67 works between 2012 and 2025

1 - 20 of 67 works

2025

Conference Publication

Continual contrastive learning on tabular data with out of distribution

Ginanjar, Achmad, Li, Xue, Singh, Priyanka and Hua, Wen (2025). Continual contrastive learning on tabular data with out of distribution. European Symposium on Artificial Neural Networks 2025, Bruges, Belgium, 23-25 April 2025. Louvain-la-Neuve, Belgium: Ciaco. doi: 10.14428/esann/2025.es2025-141

Continual contrastive learning on tabular data with out of distribution

2024

Conference Publication

Towards Explainable Network Intrusion Detection using Large Language Models

Houssel, Paul R. B., Singh, Priyanka, Layeghy, Siamak and Portmann, Marius (2024). Towards Explainable Network Intrusion Detection using Large Language Models. 2024 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), Sharjah, United Arab Emirates, 16-19 December 2024. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/bdcat63179.2024.00021

Towards Explainable Network Intrusion Detection using Large Language Models

2024

Conference Publication

An evaluation of enigma machine online emulators for teaching and learning

Utami, Dyah Puji, Singh, Priyanka and Manoharan, Sathiamoorthy (2024). An evaluation of enigma machine online emulators for teaching and learning. 2024 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE), Bengaluru, India, 9-12 December 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/tale62452.2024.10834342

An evaluation of enigma machine online emulators for teaching and learning

2024

Conference Publication

Unsupervised learning for insider threat prediction: a behavioral analysis approach

Mehmood, Rahat, Singh, Priyanka and Jeffery, Zoe (2024). Unsupervised learning for insider threat prediction: a behavioral analysis approach. 2024 17th International Conference on Security of Information and Networks (SIN), Sydney, Australia, 2-4 December 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/sin63213.2024.10871807

Unsupervised learning for insider threat prediction: a behavioral analysis approach

2024

Conference Publication

FakeFaceDiscriminator: discrimination of AI-synthesized fake faces

Liu, Xufeng, Vu, Quoc Hoan and Singh, Priyanka (2024). FakeFaceDiscriminator: discrimination of AI-synthesized fake faces. 2024 17th International Conference on Security of Information and Networks (SIN), Sydney, Australia, 2-4 December 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/sin63213.2024.10871737

FakeFaceDiscriminator: discrimination of AI-synthesized fake faces

2024

Conference Publication

IRIS-SAFE: privacy-preserving biometric authentication

Listiyani, Devi and Singh, Priyanka (2024). IRIS-SAFE: privacy-preserving biometric authentication. 2024 17th International Conference on Security of Information and Networks (SIN), Sydney, Australia, 2-4 December 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/sin63213.2024.10871371

IRIS-SAFE: privacy-preserving biometric authentication

2024

Conference Publication

CDCEF: a cloud-based data volatility & CSP reliance eradication framework

Sharma, Pankaj Hariom and Singh, Priyanka (2024). CDCEF: a cloud-based data volatility & CSP reliance eradication framework. 2024 17th International Conference on Security of Information and Networks (SIN), Sydney, Australia, 2-4 December 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/sin63213.2024.10871550

CDCEF: a cloud-based data volatility & CSP reliance eradication framework

2024

Conference Publication

Exploiting correlation between facial action units for detecting deepfake videos

Vu, Quoc Hoan and Singh, Priyanka (2024). Exploiting correlation between facial action units for detecting deepfake videos. 2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR), San Jose, CA, United States, 7-9 August 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/mipr62202.2024.00106

Exploiting correlation between facial action units for detecting deepfake videos

2024

Conference Publication

Guarding against ChatGPT threats: identifying and addressing vulnerabilities

Zhang, Dingzong, Jain, Khushi and Singh, Priyanka (2024). Guarding against ChatGPT threats: identifying and addressing vulnerabilities. 2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR), San Jose, CA, United States, 7-9 August 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/mipr62202.2024.00104

Guarding against ChatGPT threats: identifying and addressing vulnerabilities

2024

Journal Article

PP-PRNU: PRNU-based source camera attribution with privacy-preserving applications

Jena, Riyanka, Singh, Priyanka, Mohanty, Manoranjan and Das, Manik Lal (2024). PP-PRNU: PRNU-based source camera attribution with privacy-preserving applications. Computing, 106 (10), 3309-3333. doi: 10.1007/s00607-024-01330-w

PP-PRNU: PRNU-based source camera attribution with privacy-preserving applications

2024

Conference Publication

SADHE: secure anomaly detection for GPS trajectory based on homomorphic encryption

Singh, Priyanka, Rathi, Jash and Patel, Priyankaben Babulal (2024). SADHE: secure anomaly detection for GPS trajectory based on homomorphic encryption. 39th Annual ACM Symposium on Applied Computing (SAC), Avila, Spain, 8-12 April 2024. New York, NY, United States: ACM. doi: 10.1145/3605098.3636165

SADHE: secure anomaly detection for GPS trajectory based on homomorphic encryption

2024

Conference Publication

Privacy-preserving disease prediction with secure data deduplication on untrusted cloud servers

Jain, Khushi, Singh, Priyanka and Li, Xue (2024). Privacy-preserving disease prediction with secure data deduplication on untrusted cloud servers. 2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR), San Jose, CA, United States, 7 - 9 August 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/MIPR62202.2024.00114

Privacy-preserving disease prediction with secure data deduplication on untrusted cloud servers

2023

Conference Publication

RAFT: evaluating federated learning resilience against threats

Kumar, Mayank, Agrawal, Radha and Singh, Priyanka (2023). RAFT: evaluating federated learning resilience against threats. 2023 16th International Conference on Security of Information and Networks (SIN), Jaipur, India, 20-21 November 2023. Piscataway, NJ, United States: IEEE. doi: 10.1109/sin60469.2023.10474931

RAFT: evaluating federated learning resilience against threats

2023

Conference Publication

BATFL: battling backdoor attacks in federated learning

Kumar, Mayank, Agrawal, Radha and Singh, Priyanka (2023). BATFL: battling backdoor attacks in federated learning. 2023 16th International Conference on Security of Information and Networks (SIN), Jaipur, India, 20-21 November 2023. Piscataway, NJ, United States: IEEE. doi: 10.1109/sin60469.2023.10474981

BATFL: battling backdoor attacks in federated learning

2023

Journal Article

PP-JPEG: A Privacy-Preserving JPEG Image-Tampering Localization

Jena, Riyanka, Singh, Priyanka and Mohanty, Manoranjan (2023). PP-JPEG: A Privacy-Preserving JPEG Image-Tampering Localization. Journal of Imaging, 9 (9) 172, 1-15. doi: 10.3390/jimaging9090172

PP-JPEG: A Privacy-Preserving JPEG Image-Tampering Localization

2023

Conference Publication

PPAuth: A privacy-preserving framework for authentication of digital image

Jena, Riyanka, Singh, Priyanka and Mohanty, Manoranjan (2023). PPAuth: A privacy-preserving framework for authentication of digital image. 7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023, Be'er Sheva, Israel, 29–30 June 2023. Cham, Switzerland: Springer. doi: 10.1007/978-3-031-34671-2_14

PPAuth: A privacy-preserving framework for authentication of digital image

2023

Conference Publication

Data poisoning attack by label flipping on SplitFed learning

Gajbhiye, Saurabh, Singh, Priyanka and Gupta, Shaifu (2023). Data poisoning attack by label flipping on SplitFed learning. 5th International Conference, RTIP2R 2022, Kingsville, TX United States, 1-2 December 2022. Cham, Switzerland: Springer Science and Business Media Deutschland GmbH. doi: 10.1007/978-3-031-23599-3_30

Data poisoning attack by label flipping on SplitFed learning

2023

Book Chapter

XAIForCOVID-19: A comparative analysis of various explainable AI techniques for COVID-19 diagnosis using chest x-ray images

Patel, Nisarg, Parmar, Siddhraj, Singh, Priyanka and Mohanty, Manoranjan (2023). XAIForCOVID-19: A comparative analysis of various explainable AI techniques for COVID-19 diagnosis using chest x-ray images. Communications in computer and information science. (pp. 503-517) edited by Deep Gupta, Kishor Bhurchandi, Subrahmanyam Murala, Balasubramanian Raman and Sanjeev Kumar. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-031-31417-9_38

XAIForCOVID-19: A comparative analysis of various explainable AI techniques for COVID-19 diagnosis using chest x-ray images

2022

Journal Article

An image forensic technique based on JPEG ghosts

Singh, Divakar, Singh, Priyanka, Jena, Riyanka and Chakraborty, Rajat Subhra (2022). An image forensic technique based on JPEG ghosts. Multimedia Tools and Applications, 82 (9), 14153-14169. doi: 10.1007/s11042-022-13699-x

An image forensic technique based on JPEG ghosts

2022

Conference Publication

SHELBRS: Location-based recommendation services using switchable homomorphic encryption

Jain, Mishel, Singh, Priyanka and Raman, Balasubramanian (2022). SHELBRS: Location-based recommendation services using switchable homomorphic encryption. 11th International Conference on Security, Privacy, and Applied Cryptography Engineering (SPACE), Kolkata, India, 10–13 December 2021. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-95085-9_4

SHELBRS: Location-based recommendation services using switchable homomorphic encryption

Supervision

Availability

Dr Priyanka Singh is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Available projects

  • Research projects

    • Investigating vulnerabilities of Split Learning/Federated Learning/Split-Fed Learning Models

    • Defenses to build Robust Deep Learning Models

    • Image/Audio/Video Forensic Techniques to Detect Doctored Images/Deep Fakes

    • Privacy Preserving Frameworks for Various Applications

    • Geo-hashing and Location Based Services

Supervision history

Current supervision

  • Doctor Philosophy

    Privacy preservation with Large Language Models

    Principal Advisor

    Other advisors: Professor Xue Li

  • Doctor Philosophy

    Understanding Privacy Concerns About Living in Smart Cities and Enhancing Privacy Awareness

    Principal Advisor

    Other advisors: Professor Xue Li

  • Master Philosophy

    Multi-modal Detection of Video Disinformation

    Principal Advisor

    Other advisors: Professor Xue Li

  • Doctor Philosophy

    Advancing cyberworthiness via integration of AI and Model-Based Systems Engineering (MBSE)

    Principal Advisor

    Other advisors: Professor Ryan Ko

  • Doctor Philosophy

    Weighted Ensembles for Different machine learning model that support non-data-sharing / vertical partition

    Associate Advisor

    Other advisors: Professor Xue Li

  • Doctor Philosophy

    Identification of Disinformation Origins with Evidence-Based Justification

    Associate Advisor

    Other advisors: Professor Xue Li

  • Doctor Philosophy

    Behaviour-Oriented Tracking of Disinformation

    Associate Advisor

    Other advisors: Professor Xue Li

  • Master Philosophy

    Mapping Emerging Narratives Composed of False Information

    Associate Advisor

    Other advisors: Professor Xue Li

Media

Enquiries

For media enquiries about Dr Priyanka Singh's areas of expertise, story ideas and help finding experts, contact our Media team:

communications@uq.edu.au