Lightweight and Unobtrusive Data Obfuscation at IoT Edge for Remote Inference

Executing deep neural networks for inference on the server-class or cloud backend based on data generated at the edge of Internet of Things is desirable due primarily to the limited compute power of edge devices and the need to protect the confidentiality of the inference neural networks. However, such a remote inference scheme incurs concerns regarding the privacy of the inference data transmitted by the edge devices to the curious backend. This paper presents a lightweight and unobtrusive approach to obfuscate the inference data at the edge devices. It is lightweight in that the edge device only needs to execute a small-scale neural network; it is unobtrusive in that the edge device does not need to indicate whether obfuscation is applied. Extensive evaluation by three case studies of free spoken digit recognition, handwritten digit recognition, and American sign language recognition shows that our approach effectively protects the confidentiality of the raw forms of the inference data while effectively preserving the backend's inference accuracy.Comment: This paper has been accepted by IEEE Internet of Things Journal, Special Issue on Artificial Intelligence Powered Edge Computing for Internet of Thing

Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices

Home appliance manufacturers strive to obtain feedback from users to improve their products and services to build a smart home system. To help manufacturers develop a smart home system, we design a federated learning (FL) system leveraging the reputation mechanism to assist home appliance manufacturers to train a machine learning model based on customers' data. Then, manufacturers can predict customers' requirements and consumption behaviors in the future. The working flow of the system includes two stages: in the first stage, customers train the initial model provided by the manufacturer using both the mobile phone and the mobile edge computing (MEC) server. Customers collect data from various home appliances using phones, and then they download and train the initial model with their local data. After deriving local models, customers sign on their models and send them to the blockchain. In case customers or manufacturers are malicious, we use the blockchain to replace the centralized aggregator in the traditional FL system. Since records on the blockchain are untampered, malicious customers or manufacturers' activities are traceable. In the second stage, manufacturers select customers or organizations as miners for calculating the averaged model using received models from customers. By the end of the crowdsourcing task, one of the miners, who is selected as the temporary leader, uploads the model to the blockchain. To protect customers' privacy and improve the test accuracy, we enforce differential privacy on the extracted features and propose a new normalization technique. We experimentally demonstrate that our normalization technique outperforms batch normalization when features are under differential privacy protection. In addition, to attract more customers to participate in the crowdsourcing FL task, we design an incentive mechanism to award participants.Comment: This paper appears in IEEE Internet of Things Journal (IoT-J

Defensive behavior is linked to altered surface chemistry following infection in a termite society

The care-kill response determines whether a sick individual will be treated or eliminated from an insect society, but little is known about the physiological underpinnings of this process. We exploited the stepwise infection dynamics of an entomopathogenic fungus in a termite to explore how care-kill transitions occur, and identify the chemical cues behind these shifts. We found collective responses towards pathogen-injected individuals to vary according to severity and timing of pathogen challenge, with elimination, via cannibalism, occurring sooner in response to a severe active infection. However, injection with inactivated fungal blastospores also resulted in increased albeit delayed cannibalism, even though it did not universally cause host death. This indicates that the decision to eliminate an individual is triggered before pathogen viability or terminal disease status has been established. We then compared the surface chemistry of differently challenged individuals, finding increased amounts of long-chained methyl-branched alkanes with similar branching patterns in individuals injected with both dead and viable fungal blastospores, with the latter showing the largest increase. This coincided with the highest amounts of observed cannibalism as well as signs of severe moribundity. Our study provides new mechanistic insight into the emergent collective behaviors involved in the disease defense of a termite society

Transforming Emotional Regime: Pai Hsien- yung’s Crystal Boys

“Transforming Emotional Regime: Pai Hsien- yung’s Crystal Boys” turns towards literature as a means of exploring emotional hierarchies that both inform and organize homophobia and anti-queer violence within the structure of the family. Linshan Jiang takes us through Crystal Boys––a canonical piece of Taiwanese queer lit- erature––a love story between two male lovers up against the social order of fielial piety in Taiwan during the 1960s

Women Writing War Memories: Hayashi Fumiko, Nieh Hualing, and Zhang Ling

In my dissertation, I examine how three female writers, namely, the Japanese writer Hayashi Fumiko and two immigrant writers from China to North America, Nieh Hualing and Zhang Ling, remember and reconstruct memories of war experiences in their works about the Second Sino-Japanese War through the intersection of gendered, transnational, and intergenerational memories. For most of the twentieth century, when women became audible in historical narratives of the war, they usually appear mourning the deaths of their loved ones and are rendered as a trope not of their own suffering but that of the nation’s; they are thus simultaneously silenced and elevated. At the same time, women are also at the core of metaphors that feminize the nation. While narratives of war have been dominated by nationalist, militarist, and masculine discourses, my research transcends this conventional remembrance of war and demonstrates the existence of female subjectivity in transnational spaces through their embodied memories of war, intimacy, sexual violence, and pleasure. By grouping these three writers together, I approach war memories through gendered, transnational, and intergenerational lenses to challenge state-controlled, official narratives of the war and debunk ethnocentric and patriarchal nationalism. My research shows writers’ perpetual entanglement with the legacy of war and their conflicting inclination toward imperialist nostalgia and humanistic cosmopolitanism in various transhistorical and translocal contexts