Introduction to Professor Yuhong Liu and Her Lab at Santa Clara University
1. Could you briefly introduce yourself (and your University/Lab)?
I’m currently an associate professor at the Department of Computer Science and Engineering, Santa Clara University. I received my B.S. and M.S. degree from Beijing University of Posts and Telecommunications in 2004 and 2007 respectively, and the Ph.D. degree from University of Rhode Island in 2012. I was the recipient of the 2019 Researcher of the Year Award at School of Engineering, Santa Clara University, and the 2013 University of Rhode Island Graduate School Excellence in Doctoral Research Award. My research interests mainly focus on trustworthy computing and cyber security on emerging applications, such as Internet-of-things, blockchain and online social media. I have published over 60 papers on prestigious journals and peer reviewed conferences. My papers have been selected as the best paper at the IEEE International Conference on Social Computing 2010 (acceptance rate = 13%) and the 9th International Conference on Ubi-Media Computing (UMEDIA 2016). I am actively contributing to professional societies including IEEE and Asia-Pacific Signal and Information Processing Association (APSIPA). I have contributed as an organizing committee member for over 10 international conferences and a TPC member for over 20 conferences. I am currently serving as the IEEE Computer Society Region 6 Area 4 coordinator, a member of the IEEE Computer Society Technical Meeting Request Committee, a member of the Multimedia Security and Forensics (MSF) TC for APSIPA, and an APSIPA Distinguished Lecturer (2021-2022).
Located in the heart of Silicon Valley, Santa Clara University (SCU) is a private Jesuit university in Santa Clara, California. Established in 1851, SCU is the oldest operating institution of higher learning in California. It is ranked by U.S. News & World Report among the top 15 percent of universities nationwide. I’m directing the Trustworthy Computing lab at SCU and serving as the co-director of the SCU Internet of Things (SIoT) lab. Our lab currently has 5 Ph.D. students, 3~4 master students and over 15 undergraduate students working on different security related research projects.
2. What have been your most significant research contributions up to now?
The hyper-connection of today’s digital infrastructures enables rapid evolving of cyberspace. However, it also brings variety of threats, undermining the public’s trust and ability to fulfill their tasks in the cyberspace. The current trust studies, however, are lagging behind the security challenges. In particular, the rapid emergence of systems across computing and social boundaries requires the trust models to consider social relationship and intervention from human operators. Also, the complex distributed systems and fast evolving threats require trust analysis to be scalable and efficient. Such requirements are beyond the capability of existing trust theories. My most significant research contributions focus on advancing the next generation trust theories and applying them on emerging applications.
One important domain of my research is trustworthy online social networks (OSNs). With more people getting used to make their economic, political, and even daily life decisions by referring to information from online social media, most of them are not aware how their decisions are actually influenced by malicious attackers, companies or politicians through fabricating and propagating false information on OSNs. To address the information manipulations and ensure the security, privacy and trust in OSNs, in this line of research, we mainly utilized probability-based signal processing techniques and machine learning algorithms to perform anomaly detection and trustworthy online recommendations. Meanwhile, we also studied information manipulations and privacy attacks from the attacker’s point of view, with the ultimate goal as to help resolve the vulnerabilities of current defense schemes. This research stream is significant because security, privacy, and trust issues on online social media are closely related with everyone’s daily lives and attracts increasing attention from both academia and industry.
Another major domain of my research is to ensure trustworthy computing and communications on resource-constrained IoT edge devices. In this line of research, we have successfully established a WiFi based comprehensive IoT testbed with real devices. Based on this testbed, we have (1) quantitatively evaluated the energy consumption of edge devices when they execute the state-of-the-art cryptographic algorithms and security protocols; (2) analyzed the impact of DDoS and energy based DDoS attacks on the edge devices; (3) proposed lightweight features for machine learning algorithms to perform malicious traffic detection; and (4) explored effective approaches to offload computation/communication overhead from edge devices to trustworthy fog nodes. The adoption of real testbed differentiates our work from most existing studies, making our research outcomes particularly practical and transformative.
Recently, our lab starts to explore trustworthy solutions via Blockchain systems. So far, we have proposed to adopt Blockchain for secure IoT software updates, where the high-cost cryptographic operations, such as authentication and encryption/decryption, can be offloaded from resource-constrained IoT devices to the Blockchain. In addition, we have also proposed an efficient and secure multi-signature protocol for Blockchain based consensus. We are currently working on ensuring fair trade of digital goods between untrustworthy parties on Blockchain. Our research shows promising results for developing the next generation trustworthy solutions via Blockchain techniques.
3. What problems in your research field deserve more attention (or what problems will you like to solve) in the next few years, and why?
Recently, data-driven approaches, such as machine learning and deep learning techniques, have shown promising performances in different domains. It is also the trending direction to adopt these approaches for security studies. However, there are still many challenges to be resolved. For example, to ensure trustworthy online social media, an urgent issue right now is how to fight against misinformation propagation, especially since the general public has witnessed the massive misleading information during the COVID-19 pandemic and the U.S. presidential elections. In order to adopt data-driven approaches for misinformation detection and propagation studies, one fundamental challenge is how to extract ground truth and make such extraction scalable. Furthermore, due to the complex rationale behind humans’ social decision makings (especially in online platforms), collaborations are required among different disciplines, including but not limited to computer science, psychology, sociology, journalism, and even public health studies. How to integrate such human factors into the data-driven approaches is another challenging issue to address. On the other hand, to adopt data-driven approaches for securing resource-constrained IoT devices, one of the most challenging issues is how to reduce or offload the computational overhead to fog nodes or cloud, and furthermore, how to identify trustworthy fog nodes for such offloading.
4. What advice would you like to give to the young generation of researchers/engineers?
My advice is to identify significant research problems/gaps from practice. The engineering fields, especially the computing field, are evolving really fast. So, the best way to make the research impactful and transformative is to address real-world practical problems. In addition, these real-world problems are often complex and require collaborations from multiple disciplines. Many good ideas are generated through talks and discussions with people from different backgrounds. Being open minded is essential.