發(fā)布時間：2018-04-13 23:21

  本文選題：智能手機 + Android�。� 參考：《山西大學》2014年碩士論文

【摘要】：自2007年以來,智能手機的發(fā)展越來越快。智能手機已也不再是僅僅只有電話和短信等基本功能,而是集多媒體、辦公、娛樂、上網等于一體的多功能手機。它能通過移動網絡與遠程互聯(lián)網的不同服務端相連,下載大量信息存入手機,而這些信息對于許多用戶而言,不知道安全與否。一旦用戶錯誤下載了惡意軟件或者其它錯誤信息,就有可能將自身的所有正常信息全都泄露出去,給用戶自身帶來無可估量的后果。因此,智能手機入侵檢測的研究迫在眉捷。本文根據(jù)這個現(xiàn)狀針對智能手機異常入侵檢測進行了研究。入侵檢測技術作為計算機安全領域的關鍵技術,其發(fā)展理論已經逐步走向成熟。但由于智能手機的起步較晚,在智能手機入侵檢測領域的研究可以說處于起步階段。本文在面向Android智能手機平臺下,選用異常入侵檢測作為研究方向,將異常入侵檢測與智能手機相結合,從而達到提高手機系統(tǒng)對異常入侵的防范能力。文中依據(jù)異常入侵檢測的思想與原理,設計并給出了面向Android手機平臺下的異常入侵檢測系統(tǒng)的總體框架設計,并對數(shù)據(jù)特征選取、數(shù)據(jù)采集模塊、數(shù)據(jù)庫模型以及處理算法和響應模塊進行了詳細的分析。其中還給出了數(shù)據(jù)采集的詳細過程及關鍵代碼。文中在Android平臺下采集CPU利用率、內存信息、進程信息、網絡流量信息等智能手機系統(tǒng)信息以及用戶操作信息,將其作為數(shù)據(jù)來源,經過篩選整理形成訓練集以及測試集后,采用不同的SVM算法進行實驗分析,并統(tǒng)計記錄不同的實驗結果。而本文實驗采用了原始的C-SVM算法以及改進的VC-SVM算法對設計的系統(tǒng)采集整理的數(shù)據(jù)進行實驗。實驗過程中選用了不同的核函數(shù)以及不同的參數(shù)對數(shù)據(jù)進行分析計算,取得了較好的實驗結果。最后對得出的結果進行了詳細的分析與對比。結果表明,該算法能很好的適用于Android平臺,得到較高的檢測率和較低的誤報率。將其與Android智能手機平臺相結合,能有效改善手機的主動防御性能力,從而提高手機對異常入侵的防范能力。
[Abstract]:Since 2007, smartphones have been growing faster and faster.Smartphone is no longer just basic functions such as telephone and SMS, but a multi-functional mobile phone that integrates multimedia, office, entertainment and Internet.It can connect to different services of the remote Internet via mobile network and download a large amount of information into the mobile phone which for many users do not know whether safe or not.Once the user has downloaded malware or other wrong information wrongly, it is possible to leak all the normal information, which will bring incalculable consequences to the user himself.Therefore, the research of smart phone intrusion detection is urgent.According to this situation, this paper studies the anomaly intrusion detection of smart phone.As a key technology in the field of computer security, intrusion detection theory has gradually matured.However, due to the late start of smart phone, the research in the field of smart phone intrusion detection can be said to be in its infancy.In this paper, anomaly intrusion detection is chosen as the research direction under the platform of Android smart phone, which combines abnormal intrusion detection with smart phone so as to improve the ability of mobile phone system to prevent abnormal intrusion.According to the idea and principle of anomaly intrusion detection, this paper designs and gives the overall frame design of anomaly intrusion detection system based on Android mobile phone platform, and selects the data feature and data acquisition module.The database model, processing algorithm and response module are analyzed in detail.The detailed process and key codes of data acquisition are also given.In this paper, CPU utilization, memory information, process information, network traffic information and user operation information are collected under the Android platform, which are used as data sources. After screening, training set and test set are formed.Different SVM algorithms are used for experimental analysis and different experimental results are recorded.In this paper, the original C-SVM algorithm and the improved VC-SVM algorithm are used to test the data collected by the designed system.In the experiment, different kernel functions and different parameters are selected to analyze and calculate the data, and good experimental results are obtained.Finally, the results are analyzed and compared in detail.The results show that the algorithm can be well applied to Android platform, with high detection rate and low false alarm rate.Combining it with Android smart phone platform, it can effectively improve the mobile phone's active defensive ability, thus improve the mobile phone's ability to prevent abnormal intrusion.
【學位授予單位】：山西大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.08

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本文編號：1746673