Reasoning about the impacts of information sharing

Shared information can benefit an agent, allowing others to aid it in its goals. However, such information can also harm, for example when malicious agents are aware of these goals, and can then thereby subvert the goal-maker's plans. In this paper we describe a decision process framework allowing an agent to decide what information it should reveal to its neighbours within a communication graph in order to maximise its utility. We assume that these neighbours can pass information onto others within the graph. The inferences made by agents receiving the messages can have a positive or negative impact on the information providing agent, and our decision process seeks to assess how a message should be modified in order to be most beneficial to the information producer. Our decision process is based on the provider's subjective beliefs about others in the system, and therefore makes extensive use of the notion of trust with regards to the likelihood that a message will be passed on by the receiver, and the likelihood that an agent will use the information against the provider. Our core contributions are therefore the construction of a model of information propagation; the description of the agent's decision procedure; and an analysis of some of its properties

Balancing value and risk in information sharing through obfuscation

Abstract—Fast-paced data-to-decision systems are heavily dependent on the reliable sharing of sensor-derived information. At the same time a diverse collection of sensory information providers would want to exercise control over the information shared based on their perception of the risk of possible misuse due to sharing and also depending on the consumer requirements. To attain this utility vs. risk trade-off, information is subjected to varying but deliberate quality modifying transformations which we term as obfuscation. In this paper, treating privacy as the primary motivation for information control, we highlight initial considerations of using feature sharing as an obfuscation mechanism to control the inferences possible from shared sensory data. We provide results from an activity tracking scenario to illustrate the use of feature selection in identifying the various trade-off points

ウェアラブルセンサを利用した人間行動の計測のための表現学習に関する研究

学位の種別: 課程博士審査委員会委員 : （主査）東京大学特任准教授 松尾 豊, 東京大学教授 元橋 一之, 東京大学特任教授 阿部 力也, 東京大学准教授 森 純一郎, 上智大学准教授 矢入 郁子University of Tokyo(東京大学