We develop a vulnerability detection module to identify three important security vulnerabilities in the IMS system that supports 4G/5G multimedia services. We have validated them in 4 carriers from TaiwanU.S. using smartphones from 7 brands,shown that they can be exploited to launch a stealthy call DoS attack, a social engineering attack with ghost calls,a call ID spoofing attack. Moreover, attackers can detect attackable users using an AI technique with only the users＇ phone numbers. We finally propose solutionsdevelop an AI-based technique of call ID spoofing detection.

The network technology plays an important role in the industrial control systems (ICS)then has become the target of cyber-attackers. For industrial internet-of-things (IIoT) applications with limited computing resources, designing an effective NIDS is challenging. A compacteffective NIDS for IIoT is proposedvalidated by using the more recent UNSW-NB 15 dataset to improve the detection capability against new types of attacks in the real world. Experimental results show that the proposed method achieves better performance than previous methods.

The pills detection system is built based on the Feature Pyramid NetworkConvolution Normal Network (CNN). Two-stage CNN architecture is used for pills localizationpill classification. The accuracyexecution time of the pill detection are 900.02s, respectively.

The smoke removal device with smart detection has the capability of gas detectionindoor air circulation. The system is internally equipped with a sensing device. If an abnormal PM2.5 valuea high concentration of dangerous gas is detected, the fan can be automatically activated immediately to quickly filter the air,both preventivemonitoring functions can be achieved.

"We will demonstrate the following three technical achievements of our joint project: 1. Deployment of HarDNet on GPU (power consumption: 200 Watts) 2. Deployment of HarDNet on FPGA (power consumption: several tens of Watts) [winning 2nd place in the FPGA track, LPCVC 2020] 3. Deployment of HarDNet on lightweight edge devices such as Raspberry Pi (power consumption: single-digit, 10 Watts) [winning 3rd place in the DSP track4th place in the CPU track, LPCVC 2020]"

With the astronomically growing trade flows, customs administrations need effective and explainable methods to detect suspicious transactions. This project presents a novel artificial intelligence-based model named DATE that ranks trade flows in the order of fraud risk and to maximize customs revenue. We confirm the superiority of DATE over state-of-the-art AI models, with a remarkable precision of 92.7% on illegal cases and a recall of 49.3% on revenue after inspecting only 1% of all trade flows. Predictions of DATE are also interpretable from the attention mechanism. We are deploying DATE in Nigeria and Malawi Customs Services, in collaboration with the World Customs Organization (WCO). DATE has been published in ACM KDD 2020, which is an AI top conference.

1. CDX is to provide an environment for long periods of time in coordination with school courses, including the simulation of a real company＇s network environment with randomly selected vulnerabilities in cyber defense contests. 2. HoneynetMalware Knowledge Base simulates systemapplication vulnerabilitiesthen monitors the cyber-attacksthe corresponding traffic flow.

"Introduce dielectric-fuse breakdown OTP (dFuse-OTP) technology: a.) dFuse is a newly discovered OTP mechanism which is totally different from the conventional mechanisms of anti-fuse, eFuse,charge-storage b.) IPs of dFuse OTPs have been protected globally c.) dFuse OTPs are totally integratedcompatible in the standard CMOS technologies without any additional masks d.) small layout celllow cost e.) dFuse OTPs have been at the phase of trial production in the first two big Taiwanese foundries."

We proposed a dynamic-key secure DFT structure that can generate the keys dynamicallydefend scan-basedmemory attacks without decreasing the system performancethe testability. Analysis results show that our method can achieve a very high security levelthe security level will not decrease no matter how many times the attacker guesses due to the dynamic characteristic of our method.

This work presents a low powersecure IoT communication scheme. A physical unclonable function (PUF) based mutual authentication scheme in conjunction with a trusted third party (TTP),the low power transceiver with secure wake-up mechanism are integrated for networkhardware security thereby enabling to extend the battery lifetimeensuring reliability for the IoT systems.