Research

In the field of cryptography, We have a keen interest in several cutting-edge research areas. Firstly, We are focused on developing and applying post-quantum cryptographic algorithms to address complex challenges in cybersecurity and privacy. Alongside this, We are also engrossed in creating Blockchain-based decentralized cryptographic algorithms, aiming to establish fully secure and transparent systems. Additionally, We are fascinated by the prospect of leveraging artificial intelligence and machine learning for vulnerabilities in existing cryptosystems. These multifaceted interests collectively contribute to our ongoing research and engagement in the evolving landscape of cryptography, as we aim to advance digital security and privacy through innovative methods.

In the domain of privacy preservation, Our research interests span several critical areas. One primary focus is on protecting users' sensitive data, including usage patterns, location, and identity. Additionally, We are deeply involved in developing AI-based privacy attacks and countermeasures, an emerging field vital for understanding and safeguarding against sophisticated threats. Defining differential privacy for critical applications, a task essential for ensuring robust privacy across sectors and contexts. These multifaceted interests collectively contribute to our ongoing research and engagement in the evolving field of privacy preservation, as we aim to tackle some of the most pressing challenges in data security and privacy.

In the realm of investigating cyber incidents, our research interests are diverse. A key focus is on detecting malware that exploits encryption schemes, a growing concern with the increasing use of encrypted traffic. Similarly, investigating ransomware threats, understanding their propagation on network and their impact on different types of malware. At the same time, exploiting packet-level information to predict the risk of cybercrimes based on existing threats, offering a more proactive approach to cybersecurity. These varied interests collectively contribute to our ongoing work and research in the rapidly evolving field of cyber incident investigation, as we strive to address some of the most pressing challenges in cybersecurity.

In the context of vulnerabilities associated with AI algorithms, our research interests encompass several vital areas. A primary focus lies in performing exhaustive execution to unearth hidden vulnerabilities that may, otherwise, go unnoticed, thereby bolstering the security of AI systems. Alongside this, we are engaged in investigating inference data poisoning attacks that can severely compromise AI operations. Additionally, we are engaged in investigating inference data poisoning attacks. Additionally, we emphasize on deploying effective countermeasures to mitigate such threats. Lastly, we are conducting research on generating adversarial Generative Adversarial Networks (GANs) for critical applications, a topic of immense importance given the growing reliance on GANs in various domains. These collective areas of inquiry form our pursuit of addressing the threats, weaknesses, and design challenges associated with the deployment of AI systems.