| OSMANI SHAIRA | 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: Support Vector Machine based Detection of Block Withholding Attack in a Bitcoin Mining Pool
abstract: In the Bitcoin system, transactions are recorded in a distributed ledger called blockchain, which is a sequence of blocks including issued transactions. Some special nodes called miners try to create a new valid block in order to acquire rewards (i.e., new Bitcoins) by solving cryptographic puzzles with certain difficulty (i.e., network difficulty). This process is called proof of work (PoW) and it requires a huge number of hash calculations. To acquire the rewards while suppressing the electricity and investment costs, multiple miners tend to form a group called a pool to conduct PoW collaboratively. The manager of the pool, i.e., pool manager, divides the original PoW task into multiple sub-tasks and allocates them to the member miners. It also sets the local difficulty of PoW (i.e., pool difficulty), which is easier than the network difficulty, to confirm the contribution of members. Each member is requested to report their finding blocks and shares, which only satisfy the pool difficulty condition, to the pool manager. The pool manager distributes rewards to members according to their contribution. It has been pointed out that some malicious miners can sabotage the mining process and gain more rewards by hiding found blocks. This attack is called block withholding attack (BWA). Since BWA reduces the pool rewards, it is important for the pool manager to detect it. The pool manager can monitor the behavior of each miner in terms of the number of reported blocks and that of reported shares. If a miner is honest, their ratio will reach the ratio of pool difficulty to network difficulty. Otherwise, it will be lower than the difficulty ratio. Focusing on this characteristic, we apply the support vector machine (SVM) to classify members into honest or malicious. Through simulation experiments using the modified version of the existing simulator PoolSim and the hashrate distribution of miners in the actual mining pool called ViaBTC, we demonstrate the relationship between the detection accuracy and the observation period. language of the presentation: English | ||||||||
| WIRAATMAJA CHRISTOPHER | 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: Cost-Efficient Blockchain-Based Access Control for the Internet of Things
abstract: Blockchain-based access control (BBAC) has been highly promising to prevent unauthorized resource access in the Internet of Things (IoT). However, maintaining BBAC can be potentially expensive due to the storage cost of the blockchain. To address this issue, we propose a layered BBAC architecture by combining blockchain with blockchain oracle and tamper-proof decentralized storage (e.g., IOTA). The proposed architecture consists of three main layers: a blockchain layer, which provides distributed and trustworthy access control, a storage layer, which stores meta data (e.g., subject/object attributes and policies) used in the access control of the blockchain layer, and an oracle layer, which works as a bridge to help transfer data between the blockchain and decentralized storage. This architecture achieves robust, auditable, and cost-efficient ccess control by migrating the meta data from the blockchain to the decentralized storage while keeping the fascinating tamper-proof feature of the blockchain. We implement nd evaluate this architecture in terms of time and monetary cost to demonstrate its feasibility and superiority over existing ones. language of the presentation: English | ||||||||
| 池田 聖華 | M, 2回目発表 | 数理情報学 | 池田 和司, | 松本 健一, | 久保 孝富, | 吉本 潤一郎, | 福嶋 誠, | 日永田 智絵 |
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title: Gaze Behavior Analysis
in Program Comprehension by Contrasting Human and Machine Attention
abstract:Programmers spend much of their working time to comprehend programs. Therefore, efficient program comprehension is expected to improve the overall software development productivity. Previous research works have shown that programmers move their gaze strategically during reading programs. However, there has been no quantitative evaluation of programmers’ gaze, based on their importance of components of source code. Since it is expected that human attention is directed to important components, it might be able to assess programmers' gaze behavior by quantifying their importance. In this study, we aim to clarify the cognitive process of program comprehension by evaluating the importance of components in source codes. To this end, we compare programmers' gaze distribution with the machine learning model's attention as the importance of their programs. languege of the presentation: Japanese 発表題目:アテンションモデルとの対比によるプログラム理解時の視線行動分析 発表概要: プログラムの理解は、ソフトウェア開発においてデバックやテストフェーズなど様々な過程で重要である。ソフトウェア開発においてその作業時間の多くがプログラムを理解するために割かれている。プログラム理解の効率性をあげる手がかりがプログラマの視線行動にあると考えられている。先行研究において、プログラマがプログラム理解時に戦略的に視線を動かすことが示されている。しかし、プログラムの構成要素の重要性を踏まえた定量的視線行動分析はなされていない。本研究では、プログラム理解の認知過程を視線行動分析によって明らかにすることを目的に機械学習モデルのアテンションとヒトの視線分布の対比を行う。 | ||||||||
| 石田 豊実 | M, 2回目発表 | 数理情報学 | 池田 和司, | 松本 健一, | 久保 孝富, | 吉本 潤一郎, | 福嶋 誠, | 日永田 智絵 |
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title: Indentifying brain volumetric features of expert programmers
abstract: Program comprehension requires much time and effort in software development. Previous studies aimed to understand strategies of expert programmers that lead to efficient program comprehension by analyzing their behavioral performance and physiological signals. However, the neural bases for program comprehension in expert programmers are still unclear. The purpose of my study is elucidating the neural bases of program comprehension by analyzing magnetic resonance imaging data of programmers obtained during a program categorization task. In my presentation, I will report basic results for the association between program comprehension and brain structure. language of the presentation: Japanese 発表題目: エキスパートのプログラム理解を支える脳構造の特定 発表概要: ソフトウェア開発時に多くの時間と労力を要するプログラム理解を効率的に獲得するために，開発効率の高いプログラマ(熟練者)の特徴を把握しようとする試みがある． 既存研究では，熟練者とそうでない者でコーディングおよびデバッグのスピードや，視線移動・脳機能といった生体情報に違いがあることが報告されている． しかし，エキスパートプログラマのプログラム理解を支える神経基盤はいまだに明らかにされていない． 本研究ではプログラム理解と脳の構造・活動に関連があるかを調査する． 本発表ではプログラム理解と脳構造の関連についての基礎的検討結果について発表する. | ||||||||