| 大平 修慈 | M, 2回目発表 | 情報基盤システム学 | 藤川 和利, 林 優一, 新井 イスマイル |
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title: Sender Identification Method Based on High-Resolution Observation of Delay-Time in In-Vehicle Network
abstract: Currently, due to the increase in the number of automobiles that connect to the internet, cyber attack on Controller Area Network (CAN) are becoming a severe problem. CAN is one of in-vehicle network protocol that is used to communicate among Electronic Control Units (ECUs) and has been de facto standard. The CAN is simple and has several vulnerabilities such as unable to distinguish spoofing message due to no authentication and no sender identification. Hence, identifying the sender node of CAN frame is a challenging task. In previous work, a delay-time based method to identify sender node has been proposed. This method is able to identify ECUs in an inexpensive device to avoid requiring costly equipment. However, if ECUs' delay-time are similar variation, this approach may not classify correctly legitimate ECUs because the time resolution to measure the delay-time is coarse. Therefore, we should focus on enhancing the accuracy of sender identification. In this presentation, we propose a sender identification method based on high resolution observation of delay-time using Time-Digital Converter. We implemented the experimental devices using FPGA and microcomputer to verify conventional method for identification. As the result, we confirm that the conventional method achieved identifying ECUs with a mean accuracy rate of 79.07% in CAN bus prototype, 87.06% in real-vehicle. language of the presentation: Japanese | |||
| 山﨑 勇二 | M, 2回目発表 | 情報基盤システム学 | 藤川 和利, 林 優一, 新井 イスマイル |
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title: Proposal of Client-Side XSS Protection Method by Primitive Trusted Types
abstract: The Web has become one of the most important platforms on the Internet. On the other hand, the vulnerability of Cross-site Scripting (XSS) that allows attackers to insert and execute malicious scripts in vulnerable web applications has become a problem. In recent years, Client-Side XSS, which is a kind of XSS, has become a problem with the increase in client-side functions. To deal with this problem, detection / protection measures using taint tracking have been proposed, but this is not practical because it affects performance. In this presentation, we propose a client-side XSS protection method based on the primitive Trusted Types that verifies whether it is a safe character string by considering the performance. language of the presentation: Japanese | |||
| STIRAPONGSASUTI SOPICHA | M, 2回目発表 | ユビキタスコンピューティングシステム | 安本 慶一, 林 優一, 荒川 豊, 諏訪 博彦 |
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title: K-Anonymity Based Decision Making Support on Activity Data Upload in Smart Home abstract: Several services from a service provider can increase the smart-home dwellers' quality of life. For example, a smart home can automatically identify daily living activities from sensor/appliance data. To obtain such services, uploading sensor data to the cloud server is mandatory. However, it is risky for dwellers to upload all the data generated in the home. In this research, we define a threat model in which an attacker(s) can access all or part of the smart home data uploaded to the untrusted cloud server and can physically observe activities. Hence, the attacker can identify the relation between the data and the home by matching the uploaded data and the observed data. The proposed method employs k-anonymity for dwellers to make a decision on whether the data should be uploaded or not. We computed values of k from the open datasets. The k values were used to create an adaptive questionnaire. 18 participants were invited to answer upload/no-upload for each pair of activities and time zone. As a result, our k-anonymity based method can reflect the dweller's sensitivity of privacy in uploading the data.language of the presentation: English | |||
| 川端 康平 | M, 2回目発表 | ネットワークシステム学 | 岡田 実, 林 優一, 東野 武史, Dong Duong Thang |
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title: An experimental investigation of equivalent circuit for large scale WPT system with multiple receivers
abstract: This presentation demonstrates equivalent circuit model for large scale WPT system with multiple receivers. Many articles have shown the method for determining optimum load impedance at receiver and power distribution in multiple-receiver environment. These analysis indicate requirement of an equivalent circuit when a transmitter side and receiver sides are coupled. This paper newly assumes that transmitter side is large scale so that equivalent circuit have to combination of concentrated/distributed constant. Propose model is experimentally investigated under the assumption that single parallel line feeder coupled with multiple receiver with difference location. language of the presentation: Japanese | |||
| 穴井 達 | M, 2回目発表 | 数理情報学 | 池田 和司☆, 松本 健一, 川鍋 一晃(客員）, 森本 淳（客員）, 吉本 潤一郎 |
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Title:Brain mechanisms of value acquisition, maintenance and updating through long-term conditioning and reversal conditioning
Choosing valuable objects is critical for survival so individuals should adaptively learn better behavior depending on their located context or environment. In an unchanging environment, it may be an optimal to maintain their values for a long. If an environment changes, individuals should update their values flexibly. To make clear the neural mechanism of adaptive learning (i.e., acquisition, maintenance and updating value), we conducted the experiment that consisted of three weeks conditioning task and one-day reversal conditioning task, and analyzing both the behavioral and neuroimaging data. I will present some results of analysis which examine the relationship between neural and behavioral data. Language of the presentation: Japanese | |||
| 池田 圭佑 | M, 2回目発表 | 数理情報学 | 池田 和司☆, 松本 健一, 川鍋 一晃(客員）, 森本 淳（客員）,吉本 潤一郎 |
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Title:The effect of activity of connectome harmonics on cognitive function in healthy elderly
The neural basis of cognitive decline in healthy elderly is not well understood. In brain function research, conventional methods using functional MRI (fMRI) have mainly focused on functional localization, but recent studies have focused on functional integration (brain networks). When evaluating brain networks, many studies have dealt with functional connectivity and structural connectivity independently. Recently, a method called ‘connectome harmonics’ has been proposed that can understand functional signals as signals on structural networks. The purpose of this research is to test the hypothesis that activity of connectome harmonics affect cognitive decline in healthy elderly. As a preliminary research, we verified relationship between results of cognitive function test and some indicators of connectome harmonics. Language of the presentation: Japanese | |||
| 中村 優太 | M, 2回目発表 | 大規模システム管理 | 笠原 正治, 松本 健一, 笹部 昌弘, 張 元玉 |
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title: Capability-Based Access Control for the Internet of Things: An Ethereum Blockchain-Based Scheme
abstract: The large-scale and trustless nature of the Internet of Things (IoT) calls for distributed and trustworthy access control schemes to prevent unauthorized resource access.This paper proposes a Capability-Based Access Control (CapBAC) scheme by applying the emerging Ethereum blockchain technology.This scheme uses Ethereum smart contracts, i.e., executable codes residing in the blockchain, to store and manage the capability tokens, i.e., special data structures that maintain the allowed actions of a user (i.e., subject) on a certain resource (i.e., object).To provide more fine-grained access control and more flexible token management, this scheme defines capability tokens in units of actions, i.e., by dividing a conventional capability token containing multiple actions into multiple ones with each being associated with a certain action.In addition, this scheme uses a delegation graph instead of the delegation tree in existing smart contract-based CapBAC schemes to store the token delegation relationship among the subjects.By storing the tokens and the delegation graph in smart contracts, this scheme allows object owners to verify the ownership and validity of the capability tokens of the subjects.To demonstrate the feasibility of the scheme, we constructed a local Ethereum blockchain network and conducted extensive experiments. language of the presentation: Japanese | |||
| 豊 美玲 | M, 2回目発表 | 大規模システム管理 | 笠原 正治, 松本 健一, 笹部 昌弘, 張 元玉 |
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title: Using Ethereum Blockchain for Distributed Attribute-Based Access Control in the Internet of Things
abstract: Access control has been recognized as a critical issue for preventing unauthorized access to the resources in Internet of Things (IoT) systems. This paper proposes an Attribute-Based Access Control (ABAC) framework for IoT systems by using the emerging Ethereum smart contract technology. The framework consists of one Policy Management Contract (PMC), one Subject Attribute Management Contract (SAMC), one Object Attribute Management Contract (OAMC) and one Access Control Contract (ACC). The PMC, SAMC and OAMC are responsible for storing and managing the ABAC policies, the attributes of subjects (i.e., entities accessing resources) and the attributes of objects (i.e., resources being accessed), respectively. When receiving access requests, the ACC retrieves the subject attributes and object attributes as well as the corresponding policy from the SAMC, OAMC and PMC to perform the access control. Combining the ABAC model and the blockchain technology, this framework is expected to achieve distributed, trustworthy and fine-grained access control for IoT systems. To show the feasibility of the proposed framework, we construct a local private Ethereum blockchain system to implement the four smart contracts and also conduct experiments to test the monetary and time cost. language of the presentation: Japanese | |||
| REGONIA PAUL ROSSENER | D, 中間発表 | 数理情報学 | 池田 和司, 金谷 重彦, 吉本 潤一郎, 中野 高志 |
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title: Neural Energy Landscapes as Biomarkers for Depressive Functional Brain Networks
abstract: Depression is a mental disorder that disrupts daily life and normal functioning. As a heterogeneous condition, it has varying symptoms and responses to treatment. Biomarkers such as blood samples or hormone levels may help diagnose depression and its subtypes; however, there are currently no robust biomarkers for depression. Our research goal then is to discover depression biomarkers that can contribute to accurate diagnosis. Here, we study neural energy landscapes as potential biomarkers for major depressive disorder (MDD). We analyze the resting-state fMRI of hundreds of healthy subjects and patients with MDD. By fitting a pairwise Maximum Entropy Model, we identify the interactions of different functional brain networks such as default mode and fronto-parietal networks. Our initial results reveal anti-synchronous brain states, which may characterize the neural dynamics of the depressive disorder. language of the presentation: English | |||