Ultr-Low Enerygy Cryptography and Its Applications for Beyond 5G

Grant No.：JPMJCR24U1

Research Director

Takanori Isobe

Professor, Information Security Science, Graduate School of Infomation Science, University of Hyogo

Collaborators

Kiichi Niitsu

Professor, Graduate School of Infomatics, Kyoto University

Description

We aim to develop ultra-low energy cryptography with quantum security. In this research, we will not only design cryptographic algorithms but also develop actual integrated circuits, thereby achieving low energy consumption at the hardware level and accerating practical use and standardization. Additionally, by integrating this technology with lightweight key update and key protection schemes, as well as countermeasures against implementation attacks, we will establish an infrastructure for low-energy security mechanisms for Beyond 5G applications.

Acceleration and dissemination of social implementation of fake media detection technologies

Grant No.：JPMJCR24U3

Research Director

Junichi Yamagishi

Professor, Digital Content and Media Sciences Research Division, National Institute of Informatics, Research Organization of Information and Systems

Description

In our AIP-accelerated research, we expand our detection technology to include multimedia and advance our machine learning methods to cope with newly emerging and unknown deep fakes. In addition, basic research on active defense, which considers countermeasures against abuse even before media is generated, will also be conducted.

Development of Adaptive Data Compression Method for Streaming Data on IoT

Grant No.：JPMJCR24U4

Research Director

Shinichi Yamagiwa

Associate Professor, Faculty of Engineering, Information and Systems, University of Tsukuba

Collaborators

Yoshinobu Kawahara	Professor, Graduate School of Information Science and Technology, Osaka University
Hiroshi Sakamoto	Professor, Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology

Description

This research project focuses on low latency and high throughput communication and compact data management among edge devices and cloud servers of IoT application. The project investigates a novel data compression technology that employs approach of artificial intelligence to compress a data block into a single bit according to the data compression method that has been developed to shrink multiple symbols into a single bit during the PRESTO program.

Data / AI-driven decoding and encoding of neural information

Grant No.：JPMJCR24U2

Research Director

Takufumi Yanagisawa

Professor, Institute for Advanced Co-Creation Studies, Osaka University

Collaborators

Shinji Nishimoto

Professor, Graduate School of Frontier Biosciences, Osaka University

Description

This research aims to develop and apply novel neural decoding techniques by applying representational learning and generative AI to large-scale neural activity data. By linking neural activity under various perceptual and cognitive conditions with generative AI models via latent representation, we aim to (1) construct a generic and quantitative neural information representation model, and (2) clinically implement Brain-Computer Interface (BCI) and automatic diagnosis technology using our original neural decoding technology.