Our research in Network Information System Security & Privacy (NIS&P) Lab focuses on three branches of security research: cloud computing security, wireless system security, and big data and artificial intelligence (AI) security. In all fields, we are intrigued by security and privacy problems that underlie various information systems and motivate us to search for practical and meaningful solutions for the physical world.

In cloud security, we aspire to provide secure and privacy-assured data service outsourcing that is usable, scalable, and meets performance goals, through: privacy-preserving and effective search over a large-scale of encrypted data files, privacy-preserving secure cloud storage auditing with strong guarantees of storage correctness, and privacy-preserving and secure outsourcing computations over various engineering problems in large scale.

In wireless system security, our curiosity leads us to address the challenge of establishing robust and secure communication channels by leveraging physical layer (PHY) characteristics and technqiues. In particular, we are intrigued by emerging short-range communication technologies over smart devices, and propose to conduct a joint performance and security design for off-the-shelf smartphones, which considers and integrates advanced techniques from various dimensions. Our ultimate goal is to significantly advance the state-of-the-art and develop innovative and sophisticated security and defense strategies.

In big data and AI security, we are highly motivated to investigate privacy-preserving mechanisms for transformation, utilization and applications in the big data domain. Our main focus is on privacy-preserving machine learning and especially deep learning scheme designs, targeting at providing security solutions for data training, data classification and feature extraction phases etc. In addition, we are also interested in investigating and designing various sophisticated attacks on the existing AI systems, such as face recognition, voice recognition, and automatic driving systems etc. Our research is a multi-disciplinary research effort that optimizes and enhances the state-of-the-art solutions by leveraging various advanced cryptographic tools, differential privacy, machine/deep learning, signal processing techniques.

Announcement

NIS&P Lab looks for highly motivated students to join exciting research projects on Information Security and Privacy! If you are interested in research, please come to visit our lab and join us to have a great time.

Research Highlights

Search over Ciphertexts

Secure Outsourced Computation

Color Barcode Streaming

Gait Identification

Differential Privacy