【摘要】：智能手表作為可穿戴設備的一種,功能齊全、使用便捷,在健康監(jiān)測等方面有重要的作用。智能手表的監(jiān)測數據可以應用于電子取證案件,幫助偵查人員分析人物特征,為偵破案件提供有效的證據或者線索。但是,由于智能手表是近兩年爆發(fā)式增長的電子產品,目前還沒有智能手表數據提取、解析的專門設備,限制了智能手表數據在電子取證領域的廣泛應用。因此,本文目的是初步探索智能手表數據的提取與解析方法并進行手表數據的人物特征分析實驗研究,為電子數據的取證分析提供借鑒。本文主要采用文獻研究法和實驗研究法。文獻研究法通過閱讀相關文獻掌握智能手表運動和健康監(jiān)測的基本工作原理,國內外的發(fā)展現狀。實驗研究法借助FL—900手機取證塔、Oxygen Forensic Analyst和IBM SPSS Statistics 22.0進行智能手表健康和運動監(jiān)測數據的提取、解析及數據分析的實驗研究。本文根據智能手表的用戶傾向性,共選取25名20~30歲的青年實驗對象,每人佩戴手表一周左右,歷時總計7個月進行智能手表數據的人物特征分析實驗。實驗一是基礎性研究實驗,主要測試數據提取、解析方法的可行性和手表數據的內容及存儲位置。實驗二區(qū)別清醒狀態(tài)和睡眠狀態(tài),清醒狀態(tài):心率不穩(wěn)定,卡路里消耗大部分在8~15之間,心率變異系數在10%以上;睡眠狀態(tài):心率在一段時間內呈水平狀,卡路里消耗大部分在4~8之間,心率變異系數在10%以下。實驗三區(qū)別喝酒狀態(tài)和正常狀態(tài),酒后心率總體上高于正常狀態(tài),平均心率高于正常狀態(tài)約10%,變異系數低于正常狀態(tài)約30%。實驗四區(qū)別運動狀態(tài)和正常狀態(tài),運動前和運動后的步數、卡路里、心率數值都相對較小,運動過程中步數、卡路里、心率數值較大,當心率和步數同時出現數值在100以上且占比最大時,考慮處于運動或健身狀態(tài)。通過基本狀態(tài)的研究可以有效掌握智能手表用戶案發(fā)時的狀態(tài),為犯罪現場重現提供電子數據支撐。
[Abstract]:As a wearable device, smartwatch has full function, convenient use, and plays an important role in health monitoring and so on. Smart watch monitoring data can be used in electronic forensics cases to help investigators analyze character characteristics and provide effective evidence or clues for detection cases. However, because smartwatch is a explosive growth of electronic products in recent two years, there is no special equipment for data extraction and analysis of smart watches, which limits the wide application of smart watch data in the field of electronic forensics. Therefore, the purpose of this paper is to preliminarily explore the method of extracting and analyzing the data of smart watch and to carry out the experimental research on the character characteristic analysis of the watch data, which can provide reference for the forensic analysis of electronic data. This article mainly uses the literature research method and the experimental research method. The literature research method grasps the basic working principle of smart watch movement and health monitoring by reading the relevant documents, and the development status at home and abroad. The experimental research method uses FL-900 mobile phone forensics tower, Oxygen Forensic Analyst and IBM SPSS Statistics 22.0 to extract, analyze and analyze the data of smart watch health and movement monitoring. According to the user orientation of smart watches, 25 young people aged 20 or 30 years were selected to wear watches for a week or so for a total of 7 months. Experiment one is the basic research experiment, which mainly tests the data extraction, the feasibility of analytical method and the content and storage location of watch data. Experiment 2 distinguishes awake state from sleep state: heart rate is unstable, calorie consumption is mostly between 815 and coefficient of heart rate variability is more than 10%; Sleep state: heart rate is horizontal for a period of time, calorie consumption is mostly between 4g / 8 and HRV is less than 10%. In experiment 3, the drinking state and the normal state were distinguished, the drunk heart rate was higher than the normal state, the average heart rate was about 10 times higher than the normal state, and the coefficient of variation was about 30% lower than the normal state. Experiment 4 distinguishes the movement state from the normal state, the number of steps, calories, heart rate are relatively small before and after exercise, the number of steps, calories, heart rate are larger during exercise. When the heart rate and the number of steps at the same time more than 100 and the largest proportion, consider in exercise or fitness state. Through the research of basic state, we can effectively grasp the state of smart watch user at the time of crime, and provide electronic data support for crime scene reproduction.
【學位授予單位】：中國政法大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：D918

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相關碩士學位論文 前1條

1 王春露;基于智能手表數據的人物特征分析技術研究[D];中國政法大學;2017年

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本文編號：2308378