Biblio

This Innovative Practice Work-in-Progress paper presents a virtual, proactive, and collaborative learning paradigm that can engage learners with different backgrounds and enable effective retention and transfer of the multidisciplinary AI-cybersecurity knowledge. While progress has been made to better understand the trustworthiness and security of artificial intelligence (AI) techniques, little has been done to translate this knowledge to education and training. There is a critical need to foster a qualified cybersecurity workforce that understands the usefulness, limitations, and best practices of AI technologies in the cybersecurity domain. To address this import issue, in our proposed learning paradigm, we leverage multidisciplinary expertise in cybersecurity, AI, and statistics to systematically investigate two cohesive research and education goals. First, we develop an immersive learning environment that motivates the students to explore AI/machine learning (ML) development in the context of real-world cybersecurity scenarios by constructing learning models with tangible objects. Second, we design a proactive education paradigm with the use of hackathon activities based on game-based learning, lifelong learning, and social constructivism. The proposed paradigm will benefit a wide range of learners, especially underrepresented students. It will also help the general public understand the security implications of AI. In this paper, we describe our proposed learning paradigm and present our current progress of this ongoing research work. In the current stage, we focus on the first research and education goal and have been leveraging cost-effective Minecraft platform to develop an immersive learning environment where the learners are able to investigate the insights of the emerging AI/ML concepts by constructing related learning modules via interacting with tangible AI/ML building blocks.

Over the past few decades, radio frequency identification (RFID) technology has been an important factor in securing products along the agri-food supply chain. However, there still exist security vulnerabilities when registering products to a specific RFID tag, particularly regarding the ease at which tags can be cloned. In this paper, a potential attack, labeled the "Hilt Shao attack", is identified which could occur during the initial phases of product registration, and demonstrate the type of attack using UID and CUID tags. Furthermore, a system is proposed using blockchain technology in order for the attacker to hide the cloned tag information. Results show that this attack, if carried out, can negate the profits of distributors along the supply chain, and negatively affect the consumer.

Over the past few decades, radio frequency identification (RFID) technology has been an important factor in securing products along the agri-food supply chain. However, there still exist security vulnerabilities when registering products to a specific RFID tag, particularly regarding the ease at which tags can be cloned. In this paper, a potential attack, labeled the "Hilt Shao attack", is identified which could occur during the initial phases of product registration, and demonstrate the type of attack using UID and CUID tags. Furthermore, a system is proposed using blockchain technology in order for the attacker to hide the cloned tag information. Results show that this attack, if carried out, can negate the profits of distributors along the supply chain, and negatively affect the consumer.