1. Research Area

  Information Security & Intelligent IoT Laboratory comprises four research and development areas: Cryptography & Security, Blockchain, AI, and IoT, which are the core technologies that will inevitably lead the 4th Industrial Revolution. Currently, we are conducting 38 diverse projects, ranging from smart factory security, smart city, open high-performance standards for IoT devices, intelligent software development, as well as IoT convergence blockchain platform security. Our lab is steadily expanding, with current members of more than 20 members.

2. Research Overview

[Cryptography & Security]

- Hardware and Software Optimized Implementation (FPGA/ASIC) of Crypto-algorithms

- Lightweight Cryptography for Resource Constrained IoT Device

- IoT protocol security enhancement: OneM2M, LwM2M, TLS/DTLS, etc.

- Smart Factory Security

- Privacy-Preserving Protocol with zk-SNARK (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge)

- Next Generation Post-Quantum Cryptography

* Development of Security Chip and Real-time Control Protocol Security Technology for Smart Factory Network Infrastructure

√ Control protocol (real-time) security and CPS security protocol / cloud security technology integration (SW)

√ TLS 1.2 and IEEE 802.1AE/AEbn security chip (FPGA/ASIC) and KCMVP certification for smart factory security chip

√ End-to-end security technology between production facilities/gateways/servers, factory site demonstration, and open source to share domestic technology

[Blockchain]

- Research on security technology for blockchain

- Optimize of Byzantine consensus algorithm

- Research on fully-distributed ledger transaction

- Research on crytocurrency privacy-preserving scheme

- Research on resource-optimized mining of blockchain Improve confidentiality of ledger transaction

* IoT Privacy with Blockchain

√ Trustworthy data integrity of heterogeneous IoT Platforms devices by using Blockchain

√ Interworking of heterogeneous IoT Platforms by mapping services of device on Blockchain

[Artificial Intelligence and Intelligent IoT]

- Research on intelligent IoT technology based on artificial intelligence techniques such as machine learning, deep learning, statistics, and inference

- Research on Machine learning-based behavioral analysis, propensity analysis, and prediction technology research, such as SVM, Random Forests, and Decision Tree

- R&D Deep learning based energy analysis and energy usage prediction technology research such as CNN, RNN, LSTM

- Research on security technology, including AI attack and countermeasure technologies based on machine learning and deep learning

- Research on Intelligent Cognitive Framework for Intelligent IoT

* Energy monitoring and prediction system (NILM)

√ Household appliance data acquisition using a sensing device (MCP39F511)

√ Data processing, recognition model, and storage at Jetson TX2

√ API webpage development for visualizing energy monitoring and prediction result   

* AI security: Spatially Localized Perturbation GAN (SLP-GAN) for Generating Invisible Adversarial Patch

√ Generation of invisible adversarial patch based on GAN

√ Improve the attacking ability using spatially localized perturbation method based on Grad-CAM

3. Research Achievements

  Since the lab establishment in 2008, 6 doctors and 18 masters had earned their degrees. While an alumni student become a professor at domestic university (Hansung university), 4 alumni served at government-funded (ETRI research institute) as researcher, Venture CEO, Naver Labs, Korea Housing Finance. Besides, currently, our laboratory have achieved 180 research papers, 28 patents, and 33 technical report by undergraduate and graduate student’s performance. In last two years, we have published academic research papers on international journal SCI indexing standard with high impact factor as follows.

- Thi-Thu-Huong Le, Hyoeun Kang and Howon Kim, "Household Appliance Classification Using Lower Odd-Numbered Harmonics and the Bagging Decision Tree", IEEE Access, Vol. 8, pp. 55937-55952, March 2020 (SCI)

- Zhe Liu, Hwajeong Seo, Aniello Castiglione, Kim-Kwang Raymond Choo and Howon Kim, "Memory-Efficient Implementation of Elliptic Curve Cryptography for the Internet-of-Things", IEEE Transactions on Dependable and Secure Computing, Vol. 16, No. 3, pp. 521-529, 1 May-June 2019 (SCI)

- Thi-Thu-Huong Le, Yongsu Kim and Howon Kim, "Network Intrusion Detection Based on Novel Feature Selection Model and Various Recurrent Neural Networks", Applied Sciences, Vol. 9, No. 7, pp.1392-1420, April 2019 (SCI)

- Thi-Thu-Huong Le and Howon Kim, “Non-Intrusive Load Monitoring Based on Novel Transient Signal in Household Appliances with Low Sampling Rate”, energies 11(12), Dec 2018 (SCI)

- Taehwan Park, Hwajeong Seo, Junsub Kim, Haeryong Park, and Howon Kim, “Efficient Parallel Implementation of Matrix Multiplication for Lattice-Based Cryptography on Modern ARM Processor”, Security and Communication Networks Vol 2018, Nov 2018 (SCI)

- Taehwan Park, Hwajeong Seo, Sokjoon Lee, and Howon Kim,“Secure Data Encryption for Cloud-Based Human Care Services”, Journal of Sensors Vol 2018, 2018 (SCI)

- etc.