DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...最新文献_第9页

Lower power data transport protection for Internet of Things (IoT) 物联网(IoT)的低功耗数据传输保护

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073865

Chih-Ta Lin, Cheng-Yu Tsai, Chuan-Kai Kao

{"title":"Lower power data transport protection for Internet of Things (IoT)","authors":"Chih-Ta Lin, Cheng-Yu Tsai, Chuan-Kai Kao","doi":"10.1109/DESEC.2017.8073865","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073865","url":null,"abstract":"The concerns over IoT (Internet of Things) data transport security impede the development of smart service. The current data are transported mainly in clear text with a lack of privacy protection. IoT equipment resources are limited, thus complex encryption and decryption are not applicable. Google disclosed a Randomized Aggregatable Privacy-Preserving Ordinal Response (RAPPOR) algorithm that provides strong privacy guarantees for data transport, which has been efficiently implemented in Chrome for privacy protection of anonymous reporting. However, the data restoration rate is still subject to 1 to 5% confidence error. In this study we improved the Randomized Response process and proposed a Time Based Dynamic Response method. Experimental results demonstrate that the data transport error rate can be reduced to 0% in a limited range. Moreover, the computational operations can save more than 90% of time cost as compared to the common encryption and decryption techniques (such as AES), which is suitable for the applications in data transport protection between lower-power lightweight IoT devices.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"6 1","pages":"468-470"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75471445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SVM point-based real-time emotion detection 基于SVM点的实时情绪检测

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073838

W. Swinkels, L. Claesen, Feng Xiao, Haibin Shen

{"title":"SVM point-based real-time emotion detection","authors":"W. Swinkels, L. Claesen, Feng Xiao, Haibin Shen","doi":"10.1109/DESEC.2017.8073838","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073838","url":null,"abstract":"Face recognition is nowadays implemented in security systems to grant access to areas that are only allowed for authorized persons. However an additional layer of security can be added to these systems by detemining if the person in front of the camera is present in real-life and that the detected object is not a 2D representation of that person. Forcing people to interact with the system by for example posing a certain emotion can be an additional layer of complexity to deny the access for unauthorized persons. This paper focuses on that aspect i.e. real-time emotion detection. Therefore a novel algorithm is developed to extract emotions based on the movement of 19 feature points. These feature points are located in different regions of the countenance such as the mouth, eyes, eyebrows and nose. To obtain the feature points an Ensemble of Regression Trees [1] is constructed. After the extraction of the feature points 12 distances, in and around these facial regions, are calculated to be used in displacement ratios. In the final step, the algorithm inputs the displacement ratios to a classification algorithm, which is a cascade of a multi-class support vector machine (SVM) and a binary SVM. Experimental results on the Extended Cohn-Kanade dataset (CK+) [2], [3] indicate that the proposed algorithm reaches an average accuracy of 89,78% at a detection speed of less than 30 ms. The accuracy is comparable with state-of-the-art emotion detection algorithms and outperforms these algorithms when detecting the emotions Contempt, Disgust, Fear and Surprise. The detection speed evaluation of the proposed algorithm was perfomed on a Windows 8.1 laptop with an Intel-Core i7-5500U CPU (2.40 GHz) and 8,00GB of RAM.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"3 1","pages":"86-92"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75582070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Single-clock-cycle, multilayer encryption algorithm for single-channel IoT communications 用于单通道物联网通信的单时钟周期多层加密算法

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073841

Shahzad Muzaffar, O. T. Waheed, Z. Aung, I. Elfadel

{"title":"Single-clock-cycle, multilayer encryption algorithm for single-channel IoT communications","authors":"Shahzad Muzaffar, O. T. Waheed, Z. Aung, I. Elfadel","doi":"10.1109/DESEC.2017.8073841","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073841","url":null,"abstract":"Pulsed-Index Communication (PIC) is a novel technique for single-channel, high-data rate, low-power dynamic signaling that does not require any clock and data recovery. It is fully adapted to the simple yet robust communication needs of Internet of Things (IoT) devices and sensors. However, securing PIC using available conventional symmetric block cipher techniques is not feasible as it significantly degrades PIC attributes of low power, small area, and high data rates. For instance, symmetric stream ciphers such as A5/1 need several clock cycles to encrypt the data, which would reduce the PIC data rate. In this paper, we present a modified A5/1 cipher technique, called MA5/1, that generates a full keystream in one clock cycle, this securing PIC while satisfying all its requirements. Furthermore, using PIC's salient feature of transmitting index pulse streams, we provide an additional layer of packet security that makes it difficult for an attacker to receive and decode the packet before targeting MA5/1. When combined, these two techniques present a two-layer, hard-to-break challenge to an attacker, thus protecting PIC communication in an IoT network. The secure PIC is prototyped and verified in both FPGA and ASIC. In particular, we show that for an ASIC implementation in 65nm technology, the low-power operation of PIC is maintained, consuming only 27μW of power at a clock frequency of 25MHz.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"21 1","pages":"153-158"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78134849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

NIR-based gaze tracking with fast pupil ellipse fitting for real-time wearable eye trackers 基于nir快速瞳孔椭圆拟合的实时可穿戴眼动仪凝视跟踪

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073839

Jia-Hao Wu, Wei-Liang Ou, Chih-Peng Fan

{"title":"NIR-based gaze tracking with fast pupil ellipse fitting for real-time wearable eye trackers","authors":"Jia-Hao Wu, Wei-Liang Ou, Chih-Peng Fan","doi":"10.1109/DESEC.2017.8073839","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073839","url":null,"abstract":"In this work, a NIR (near infrared ray) based fast pupil ellipse fitting based gaze tracking system is developed for the wearable eye tracker. By a near-field and side-view eye camera, the contour of pupil in captured images is an ellipse generally, and that of pupil shape is not always circular. After pre-processing, the pupil contour is recognized by the two-stage binarizations, and the binaried pupil contour is applied to select the possible candidate points for pupil ellipse fittings. After the Random Sample Consensus (RANSAC) based fast pupil ellipse fitting, the centers of pupils are estimated effectively, and the gaze tracking is worked efficiently after calibrations. By experiments, the average estimated errors of pupil ellipse centers are smaller than 2 pixels. At training mode, the average horizontal and vertical accuracies of gaze tracking are 0.66 and 1.84 degrees, respectively. At testing mode, the average horizontal and vertical accuracies of gaze tracking are 1.13 and 2.24 degrees, respectively. Finally, the proposed main function performs up to 266.7 frames/sec by a personal computer with 3.4GHz operational frequency.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"27 1","pages":"93-97"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81281118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Towards fast and accurate machine learning attacks of feed-forward arbiter PUFs 前馈仲裁puf的快速准确的机器学习攻击

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073845

M. S. Alkatheiri, Yu Zhuang

{"title":"Towards fast and accurate machine learning attacks of feed-forward arbiter PUFs","authors":"M. S. Alkatheiri, Yu Zhuang","doi":"10.1109/DESEC.2017.8073845","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073845","url":null,"abstract":"Utilizing integrated circuits' manufacturing variations to produce responses unique for individual devises, physical unclonable functions (PUFs) are not reproducible even by PUF device manufacturers. However, many PUFs have been reported to be “mathematically reproducible” by machine learning-based modeling methods. The feed-forward arbiter PUFs are among the PUFs which have showed strength [1], [2] against machine learning modeling unless large computation time is used in machine learning process and the feed-forward loops are of a special type. In this paper, we develop a signal delay model for the feed-forward arbiter PUFs, through which efficient and accurate machine learning of the PUF's essential features is made possible. Experimental results show that the new model has led to high accuracy and high efficiency for the prediction of the responses of the PUFs with any type of feed-forward loops, and the high prediction accuracy was measured in terms of average prediction rate over all tested all cases. The high efficiency and high accuracy prediction of responses reported in this paper has revealed a weakness of the feed-forward arbiter PUFs that can be potentially utilized by response-prediction-based malicious software.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"11 1","pages":"181-187"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82044010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 47

IoT-equipped UAV communications with seamless vertical handover 配备物联网的无人机通信，实现无缝垂直切换

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073829

A. Gaur, Jyoti Budakoti, Chung-Horng Lung, Alan Redmond

{"title":"IoT-equipped UAV communications with seamless vertical handover","authors":"A. Gaur, Jyoti Budakoti, Chung-Horng Lung, Alan Redmond","doi":"10.1109/DESEC.2017.8073829","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073829","url":null,"abstract":"With advancement in the technology and services in different application areas, UAVs have become a strong market share. Applications range from goods delivery, agriculture, surveillance, mining, industrial inspection, disaster management etc. Furthermore, this vast usability of UAVs can be powered by Internet of Things (IoT) and it can offer a new IoT value-added services. UAVs can be referred to as “things in motion” which can be controlled over the Internet and push the sensor data they collect to the cloud services. But this imposes major challenges with high a volume of data transmissions in some applications. Another area of concern is the choice of mode of communication in LOS (Line of Sight) and BLOS (Beyond Line of Sight) where Wi-Fi could have limited accessibility and other modes like satellite communication have higher cost of data transmissions. In this paper, a RESTful approach to connect UAVs with IoT to stream sensor data to cloud services is presented, providing an efficient solution for data management and transmissions by efficiently gathering, filtering and transmitting data on demand to the cloud services. An efficient vertical handover mechanism is also presented between different modes of communication like Wi-Fi and satellite for BLOS communication challenges to increase reliability or reduce cost.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"1 1","pages":"459-465"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86647630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

The dose makes the poison — Leveraging uncertainty for effective malware detection 剂量产生毒性-利用不确定性进行有效的恶意软件检测

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073803

Ruimin Sun, Xiaoyong Yuan, Andrew Lee, M. Bishop, Donald E. Porter, Xiaolin Li, A. Grégio, Daniela Oliveira

{"title":"The dose makes the poison — Leveraging uncertainty for effective malware detection","authors":"Ruimin Sun, Xiaoyong Yuan, Andrew Lee, M. Bishop, Donald E. Porter, Xiaolin Li, A. Grégio, Daniela Oliveira","doi":"10.1109/DESEC.2017.8073803","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073803","url":null,"abstract":"Malware has become sophisticated and organizations don't have a Plan B when standard lines of defense fail. These failures have devastating consequences for organizations, such as sensitive information being exfiltrated. A promising avenue for improving the effectiveness of behavioral-based malware detectors is to combine fast (usually not highly accurate) traditional machine learning (ML) detectors with high-accuracy, but time-consuming, deep learning (DL) models. The main idea is to place software receiving borderline classifications by traditional ML methods in an environment where uncertainty is added, while software is analyzed by time-consuming DL models. The goal of uncertainty is to rate-limit actions of potential malware during deep analysis. In this paper, we describe Chameleon, a Linux-based framework that implements this uncertain environment. Chameleon offers two environments for its OS processes: standard — for software identified as benign by traditional ML detectors — and uncertain — for software that received borderline classifications analyzed by ML methods. The uncertain environment will bring obstacles to software execution through random perturbations applied probabilistically on selected system calls. We evaluated Chameleon with 113 applications from common benchmarks and 100 malware samples for Linux. Our results show that at threshold 10%, intrusive and non-intrusive strategies caused approximately 65% of malware to fail accomplishing their tasks, while approximately 30% of the analyzed benign software to meet with various levels of disruption (crashed or hampered). We also found that I/O-bound software was three times more affected by uncertainty than CPU-bound software.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"1 1","pages":"123-130"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91330457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Resisting attacks from rogue HeNB 抵抗流氓HeNB的攻击

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073873

Cheng-Yu Tsai, Chuan-Kai Kao, Chuan-Yuan Huang, Zhi-Wei Lin

引用次数: 0

LowLEAC: Low Leakage Energy Architecture for Caches LowLEAC:用于缓存的低泄漏能量架构

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073849

Rashmi Girmal, Arun Kumar Somani

{"title":"LowLEAC: Low Leakage Energy Architecture for Caches","authors":"Rashmi Girmal, Arun Kumar Somani","doi":"10.1109/DESEC.2017.8073849","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073849","url":null,"abstract":"With the ever-decreasing feature sizes, static power dissipation has become a concern in computing devices. On-chip memories are a major contributor towards the processor's leakage power dissipation due to their large transistor count. We propose a Low Leakage Energy Architecture for Caches, called LowLEAC to minimize the static power dissipation in caches made of CMOS SRAM cells. This technique is based on keeping only k most recently used cache lines powered on other lines powered off to reduce the leakage power dissipation. The control However increases the dynamic power due to re-fetching of data. To overcome that, we deploy CMOS compatible non-volatile SRAM cell, called cNVSRAM, to implement caches. The cNVSRAM cell works as a conventional SRAM in the regular mode and saves the data in a non-volatile back up when a cache line is turned off or put in the sleep mode. The non-volatile back up mode helps improve the dependability of the cache and avoids the penalty occurred due to loss of data from the inactive cache lines. With a small area penalty, LowLEAC achieves 18% energy savings with insignificant impact on the performance. LowLEAC is a suitable architecture for cache memory in mobile computing devices to minimize battery power consumption and reduce heat.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"45 1","pages":"288-295"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79342401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PACS: Pemission abuse checking system for android applictions based on review mining PACS:基于评论挖掘的android应用程序请求滥用检查系统

DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International... Pub Date : 2017-08-01 DOI: 10.1109/DESEC.2017.8073813

Jingzheng Wu, Mutian Yang, Tianyue Luo

{"title":"PACS: Pemission abuse checking system for android applictions based on review mining","authors":"Jingzheng Wu, Mutian Yang, Tianyue Luo","doi":"10.1109/DESEC.2017.8073813","DOIUrl":"https://doi.org/10.1109/DESEC.2017.8073813","url":null,"abstract":"The openness and freedom of Android system improve the proliferation of Android applications. According to recent statistics, more than 2.6 million various applications are released in Google Play Store. Unfortunately, due to the limitation of developers' knowledge and the lack of strict development specifications, the quality of the apps can not be guaranteed. This may lead to potential security problems, especially for the over requirements of the apps' permissions, which is called Permission Abuse Problem. Although some previous studies have already analyzed the permission system, investigated the effectiveness of permission model and attempted to resolve the problem, it still needs an effective and practical concentrated method to detect the permission abuse problem. In this paper, we present PACS (Permission Abuse Checking System) based on data and frequent itemsets mining technique to bring an improvement by using the apps' reviews and descriptions. PACS firstly classifies the apps into different categories by mining the apps' meta-data, e.g., the reviews, descriptions, etc. Then, it obtains the maximum frequent itemsets and constructs the permission feature database. Finally, we evaluate PACS on detecting unknown applications of the abused permission. The experiment results show that 726 out of 935 applications, which account for about 77.6%, are suffering from the Permission Abuse Problem. By comparing with the previous tools, PACS has better performances.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"1 1","pages":"251-258"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79695585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7