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Fulltext A new sensors-based covert channel on android

Al-Haiqi A, Ismail M, Nordin R

ScientificWorldJournal, 2014;2014:969628.
PMID: 25295311 DOI: 10.1155/2014/969628

Covert channels are not new in computing systems, and have been studied since their first definition four decades ago. New platforms invoke thorough investigations to assess their security. Now is the time for Android platform to analyze its security model, in particular the two key principles: process-isolation and the permissions system. Aside from all sorts of malware, one threat proved intractable by current protection solutions, that is, collusion attacks involving two applications communicating over covert channels. Still no universal solution can countermeasure this sort of attack unless the covert channels are known. This paper is an attempt to reveal a new covert channel, not only being specific to smartphones, but also exploiting an unusual resource as a vehicle to carry covert information: sensors data. Accelerometers generate signals that reflect user motions, and malware applications can apparently only read their data. However, if the vibration motor on the device is used properly, programmatically produced vibration patterns can encode stolen data and hence an application can cause discernible effects on acceleration data to be received and decoded by another application. Our evaluations confirmed a real threat where strings of tens of characters could be transmitted errorless if the throughput is reduced to around 2.5-5 bps. The proposed covert channel is very stealthy as no unusual permissions are required and there is no explicit communication between the colluding applications.

Matched MeSH terms: Accelerometry/methods
Fulltext The Evaluation of Physical Stillness with Wearable Chest and Arm Accelerometer during Chan Ding Practice

Chang KM, Chun YT, Chen SH, Lu L, Su HT, Liang HM, et al.

Sensors (Basel), 2016 Jul 20;16(7).
PMID: 27447641 DOI: 10.3390/s16071126

Chan Ding training is beneficial to health and emotional wellbeing. More and more people have taken up this practice over the past few years. A major training method of Chan Ding is to focus on the ten Mailuns, i.e., energy points, and to maintain physical stillness. In this article, wireless wearable accelerometers were used to detect physical stillness, and the created physical stillness index (PSI) was also shown. Ninety college students participated in this study. Primarily, accelerometers used on the arms and chest were examined. The results showed that the PSI values on the arms were higher than that of the chest, when participants moved their bodies in three different ways, left-right, anterior-posterior, and hand, movements with natural breathing. Then, they were divided into three groups to practice Chan Ding for approximately thirty minutes. Participants without any Chan Ding experience were in Group I. Participants with one year of Chan Ding experience were in Group II, and participants with over three year of experience were in Group III. The Chinese Happiness Inventory (CHI) was also conducted. Results showed that the PSI of the three groups measured during 20-30 min were 0.123 ± 0.155, 0.012 ± 0.013, and 0.001 ± 0.0003, respectively (p < 0.001 ***). The averaged CHI scores of the three groups were 10.13, 17.17, and 25.53, respectively (p < 0.001 ***). Correlation coefficients between PSI and CHI of the three groups were -0.440, -0.369, and -0.537, respectively (p < 0.01 **). PSI value and the wearable accelerometer that are presently available on the market could be used to evaluate the quality of the physical stillness of the participants during Chan Ding practice.

Matched MeSH terms: Accelerometry/methods*
Accelerometer Profile of Physical Activity and Sedentary Behavior in a Multi-Ethnic Urban Asian Population

Chu AHY, Bernard JY, Koh D, Müller-Riemenschneider F

Res Q Exerc Sport, 2021 Sep;92(3):361-368.
PMID: 32154777 DOI: 10.1080/02701367.2020.1734520

Purpose: Variability in accelerometry-data processing decisions limited data comparability across studies. We aimed to examine different accelerometry-data processing rules: varying bout lengths and allowance of 0- and 2-min interruptions on the total and bout-accumulated time spent in moderate-to-vigorous physical activity (MVPA) and sedentary behavior estimates, and describe the distribution of activity time based on counts per min (CPM) in granular categories. Method: Using the Singapore Health 2 survey, this study included 746 adults (41.8% women, median age 45.0 years) who provided valid ActiGraph GT3X+ accelerometer-data (≥4 valid days with ≥10-h/day). Quantile regression analysis adjusting for accelerometry daily wear time, age, and gender was performed to calculate the median and interquartile range of accelerometry estimates. Results: Median MVPA time accumulated in bouts of 1-min versus bouts of 10-min was 39.2 min/day and 6.0 min/day, respectively. MVPA time was higher when considering a 2-min interruption (range: 1.8-39.2 min/day) compared to 0-min interruption (range: 0-35.5 min/day) across bout lengths of 1- to 15-min. Participants were sedentary (≤100 CPM) for a daily median of 7.6 h/day. Median activities min/day on the lower-intensity activity spectrum (100-2499 CPM) decreased from 63.4 to 4.6 min/day, while on the higher-intensity activity spectrum (≥2500 CPM) was ≤2.9 min/day. Men generally spent more time in MVPA than women. Conclusions: This study highlights the differences in accelerometry estimates based on data processing decisions, and the importance of quantifying accelerometry-based activity time across the granular intensity spectrum. More studies are warranted to understand the determinants and health impact of these behaviors.

Matched MeSH terms: Accelerometry/methods*
Physical activity, but not sedentary time, influences bone strength in late adolescence

Tan VP, Macdonald HM, Gabel L, McKay HA

Arch Osteoporos, 2018 Mar 20;13(1):31.
PMID: 29556801 DOI: 10.1007/s11657-018-0441-9

Physical activity is essential for optimal bone strength accrual, but we know little about interactions between physical activity, sedentary time, and bone outcomes in older adolescents. Physical activity (by accelerometer and self-report) positively predicted bone strength and the distal and midshaft tibia in 15-year-old boys and girls. Lean body mass mediated the relationship between physical activity and bone strength in adolescents.
PURPOSE: To examine the influence of physical activity (PA) and sedentary time on bone strength, structure, and density in older adolescents.
METHODS: We used peripheral quantitative computed tomography to estimate bone strength at the distal tibia (8% site; bone strength index, BSI) and tibial midshaft (50% site; polar strength strain index, SSIp) in adolescent boys (n = 86; 15.3 ± 0.4 years) and girls (n = 106; 15.3 ± 0.4 years). Using accelerometers (GT1M, Actigraph), we measured moderate-to-vigorous PA (MVPAAccel), vigorous PA (VPAAccel), and sedentary time in addition to self-reported MVPA (MVPAPAQ-A) and impact PA (ImpactPAPAQ-A). We examined relations between PA and sedentary time and bone outcomes, adjusting for ethnicity, maturity, tibial length, and total body lean mass.
RESULTS: At the distal tibia, MVPAAccel and VPAAccel positively predicted BSI (explained 6-7% of the variance, p

Matched MeSH terms: Accelerometry/methods
Fulltext Sleep timing is associated with diet and physical activity levels in 9-11-year-old children from Dunedin, New Zealand: the PEDALS study

Harrex HAL, Skeaff SA, Black KE, Davison BK, Haszard JJ, Meredith-Jones K, et al.

J Sleep Res, 2018 08;27(4):e12634.
PMID: 29160021 DOI: 10.1111/jsr.12634

It is well documented that short sleep duration is associated with excess body weight and poor food intake in children. It has been suggested that sleep timing behaviour may also be an important predictor of weight and other related behaviours, independent of sleep duration; however, there is a lack of research investigating these relationships. The present study investigated sleep timing in association with diet and physical activity levels in 439 children aged 9-11 years old from New Zealand. Sleep and physical activity data were collected using accelerometry, and food choice using a short food-frequency questionnaire. Participants were classified into one of four sleep timing behaviour categories using the median split for sleep-onset and -offset times. Differences between sleep timing groups for weekly consumption frequency of selected food groups, dietary pattern scores and minutes of moderate-to-vigorous physical activity were examined. Children in the late sleep/late wake category had a lower 'Fruit & Vegetables' pattern score [mean difference (95% CI): -0.3 (-0.5, -0.1)], a lower consumption frequency of fruit and vegetables [mean weekly difference (95% CI): -2.9 (-4.9, -0.9)] and a higher consumption frequency of sweetened beverages [mean weekly difference (95% CI): 1.8 (0.2, 3.3)] compared with those in the early sleep/early wake category. Additionally, children in the late sleep/late wake category accumulated fewer minutes of moderate-to-vigorous physical activity per day compared with those in the early sleep/early wake category [mean difference (95% CI): -9.4 (-15.3, -3.5)]. These findings indicate that sleep timing, even after controlling for sleep duration, was associated with both food consumption and physical activity.

Matched MeSH terms: Accelerometry/methods*