Security of Intelligent Voice Systems
Talk, School of Computer Science and Technology(School of Artifical Intelligence), Jinhua, Zhejiang, China
This talk’s Chinese name is 智能语音系统安全.
Talks and Presentations
Acoustics and Voice: From Tools to Security
Talk, School of Computer Science, Nanjing, Jiangsu, China
This talk’s Chinese name is 声波与语音：从工具到安全.
Security of Intelligent Voice Systems
Talk, HHME 2023 Tuitorials - PCC Session 1, Harbin, Heilongjiang, China
This talk’s Chinese name is 智能语音系统安全.
ActListener: Imperceptible Activity Surveillance by Pervasive Wireless Infrastructures
Talk, Session 2B (IoT Applications and Security, IoT), IEEE ICDCS 2022, Bologna, Italy
Due to the epidemic prevention policy of COVID-19 in China, I did not attend the IEEE ICDCS 2022 held in Bologna, Italy. I made the slide for the paper presentation, and my labmate@Rutgers, Wenjin Zhang, presented the paper on behalf of me.
Model-Driven Universal Voice Sensing Threat based on Built-in Sensors
Talk, Young Scholar Workshop: Sensing (青年论坛：感知专场), CCF HHME 2021, Virtual, Online
The Chinese title of this talk is 模型驱动的通用内建传感器语音感知威胁研究.
VocalLock: Sensing Vocal Tract for Passphrase-Independent User Authentication Leveraging Acoustic Signals on Smartphones
Talk, Session 1A: Security, Privacy, and Acceptance, ACM UbiComp 2020, Virtual, Online
Recent years have witnessed the surge of biometric-based user authentication for mobile devices due to its promising security and convenience. As a natural and widely-existed behavior, human speaking has been exploited for user authentication. Existing voice-based user authentication explores the unique characteristics from either the voiceprint or mouth movements, which is vulnerable to replay attacks and mimic attacks. During speaking, the vocal tract, including the static shape and dynamic movements, also exhibits the individual uniqueness, and they are hardly eavesdropped and imitated by adversaries. Hence, our work aims to employ the individual uniqueness of vocal tract to realize user authentication on mobile devices. Moreover, most voice-based user authentications are passphrase-dependent, which significantly degrade the user experience. Thus, such user authentications are pressed to be implemented in a passphrase-independent manner while being able to resist various attacks. In this paper, we propose a user authentication system, VocalLock, which senses the whole vocal tract during speaking to identify different individuals in a passphrase-independent manner on smartphones leveraging acoustic signals. VocalLock first utilizes FMCW on acoustic signals to characterize both the static shape and dynamic movements of the vocal tract during speaking, and then constructs a passphrase-independent user authentication model based on the unique characteristics of vocal tract through GMM-UBM. The proposed VocalLock can resist various spoofing attacks, while achieving a satisfactory user experience.
Dynamically Adjusting Scale of a Kubernetes Cluster Under QoS Guarantee
Talk, Session IV: Distributed & High Performance Computing & High Performance Computing, IEEE ICPADS 2019, Tianjin, China
Nowadays, the container-based virtualization technologies have become very popular due to lightweight nature, scalability, flexibility and others. Kubernetes is one of the most popular container cluster management systems, which enables users to deploy applications on the container easily, so more and more web applications are deployed in a Kubernetes clusters. However, a Kubernetes cluster is generally designed to handle the peak of workloads, so that most of resources are idle in usual time, which results in an huge waste of resource. Hence, it is necessary to design a system to improve the cluster resource utilization and promise Quality of Service (QoS) in a Kubernetes cluster. In this paper, we propose a generic system to dynamically adjust the scale of a Kubernetes cluster, which is able to reduce the waste of resource on the premise of QoS guarantee. The proposed system contains four modules: monitor module, QoS module, scaling module, and executing module. First, the monitor module uses two open-source tools, Heapster and InfluxDB, to monitor and store real-time status of a Kubernetes cluster. Then, to guarantee QoS in the Kubernetes cluster, the QoS module presents a method to automatically decide a threshold of CPU utilization that is able to meet requirements of a specific application. Next, the scaling module provides a cluster scaling algorithm to get an ideal number of nodes in the Kubernetes cluster, which is used to allocate resources in a cluster-level allocation. Finally, according to the ideal number of nodes, the executing module adjusts the scale of the Kubernetes cluster to carry out the application.
Ubiquitous Sensing and Computing on Cyber Security and Privacy
Talk, College of Information Engineering, Hangzhou, Zhejiang, China
I was invited to present our work at College of Information Engineering of Zhejiang University of Technology. The talk is mainly about the application of mobile and ubiquitous sensing on cyber security and privacy problems.
WiZoom: Accurate Multipath Profiling using Commodity WiFi Devices with Limited Bandwidth
Talk, A2: Localization and tracking, IEEE SECON 2019, Boston, MA, USA
In IEEE SECON 2019, except for this paper, I also present three other papers for the authors who cannot go to Boston due to visa reasons.
KeyListener: Inferring Keystrokes on QWERTY Keyboard of Touch Screen through Acoustic Signals
Talk, 4-D: Crowdsensing, IEEE INFOCOM 2019, Paris, France
Due to my visit to United States from Oct. 2018, I did not attend the IEEE INFOCOM 2019 held in Paris, France. I made the slide for the paper presentation, and my labmate, Xiangyu Xu, presented the paper on behalf of me.
LipPass: Lip Reading-based User Authentication Leveraging Acoustic Signals on Smartphones
Talk, Sensing, Recognition and Tracking 1, IEEE INFOCOM 2018, Honolulu, HI, USA
To prevent users’ privacy from leakage, more and more mobile devices employ biometric-based authentication approaches, such as fingerprint, face recognition, voiceprint authentications, etc., to enhance the privacy protection. However, these approaches are vulnerable to replay attacks. Although state-of-art solutions utilize liveness verification to combat the attacks, existing approaches are sensitive to ambient environments, such as ambient lights and surrounding audible noises. Towards this end, we explore liveness verification of user authentication leveraging users’ lip movements, which are robust to noisy environments. In this paper, we propose a lip reading-based user authentication system, $LipPass$, which extracts unique behavioral characteristics of users’ speaking lips leveraging build-in audio devices on smartphones for user authentication. We first investigate Doppler profiles of acoustic signals caused by users’ speaking lips, and find that there are unique lip movement patterns for different individuals. To characterize the lip movements, we propose a deep learning-based method to extract efficient features from Doppler profiles, and employ Support Vector Machine and Support Vector Domain Description to construct binary classifiers and spoofer detectors for user identification and spoofer detection, respectively. Afterwards, we develop a binary tree-based authentication approach to accurately identify each individual leveraging these binary classifiers and spoofer detectors with respect to registered users.
Cost-Efficient VM Configuration Algorithm in the Cloud using Mix Scaling Strategy
Talk, CCN-04: Quality of Service and Experience (QoS & QoE) in Cloud Computing, IEEE ICC 2017, Paris, France
Benefiting from the pay-per-use pricing model of cloud computing, many companies migrate their services and applications from typical expensive infrastructures to the cloud. However, due to fluctuations in the workload of services and applications, making a cost-efficient VM configuration decision in the cloud remains a critical challenge. Even experienced administrators cannot accurately predict the workload in the future. Since the pricing model of cloud provider is convex other than linear that often assumed in past research, instead of typical scaling out strategy. In this paper, we adopt mix scale strategy. Based on this observation, we model an optimization problem aiming to minimize the VM configuration cost under the constraint of migration delay. Taking advantages of Lyapunov optimization techniques, we propose a mix scale online algorithm which achieves more cost-efficiency than that of scale out strategy.