恶意WiFi检测与防护技术的研究与实现

发布时间：2018-06-24 00:51

  本文选题：恶意WiFi定位 + 特征指纹　； 参考：《北京交通大学》2017年硕士论文

【摘要】：随着WiFi技术的成熟和手机的普及,手机通过WiFi热点接入Internet已经成为移动数据访问的主要方式之一。但是WiFi接入面临各种安全问题,比如WiFi钓鱼、位置信息或者服务提供商的隐私数据的泄露等,给移动应用的发展带来巨大的安全风险。在这种情形下,研究恶意WiFi检测和防护技术是十分必要和迫切的。本文重在研究恶意WiFi检测和防护技术,结合国内外已有的工作研究,分析了恶意WiFi带来的钓鱼AP、DNS欺骗攻击、SSLStrip攻击等安全问题,研究了适应当前WiFi安全需求的恶意WiFi检测和防护技术,并在移动终端和服务器端上设计和实现了原型系统。本文的主要研究工作如下:首先,分析了恶意WiFi的安全威胁,总结了已有的检测和防护技术方法和特点。其次,研究了恶意WiFi检测和防护的关键技术,包括WiFi热点特征指纹提取技术、特征指纹相似度检测技术、恶意WiFi热点定位技术、中间人攻击的检测和防护技术。第三,设计了恶意WiFi检测和防护系统。最后,在移动终端和服务器端上实现了检测和防护原型系统,并完成了测试工作。本文的主要成果是:第一,本文通过对设备帧字段信息的分析,提出了 WiFi设备特征指纹提取算法和指纹相似度检测算法,并将两个算法应用于接入前WiFi环境的检测和接入时WiFi的恶意性检测。第二,本文提出了 WiFi热点定位算法,利用移动终端对恶意WiFi热点位置定位,提供了一种对恶意WiFi热点的主动防护能力。第三,本文通过对恶意中间人攻击的原理分析,首先采用MAC对比法和域名拨测法实现恶意性检测,其次采用静态绑定路由器IP和MAC的方法实现恶意性检测,解决了接入后恶意WiFi的检测的问题。本文研究成果可以解决恶意WiFi带来的多种安全问题,利用恶意WiFi检测技术和中间人攻击检测技术,支持接入前和接入后的恶意性检测;当检测到恶意WiFi后,利用恶意WiFi定位技术来发现恶意WiFi的位置,实现对恶意WiFi热点的主动防护。通过测试,结果证明本系统能够满足本文所提出的系统目标和需求。
[Abstract]:With the maturity of WiFi technology and the popularity of mobile phones, mobile phone access to the Internet through WiFi hotspots has become one of the main ways of mobile data access. However, WiFi access faces a variety of security problems, such as WiFi fishing, location information or privacy data disclosure from service providers, which brings huge security risks to the development of mobile applications. In this case, it is necessary and urgent to study malicious WiFi detection and protection technology. This paper focuses on the study of malicious WiFi detection and protection technology, combined with the existing work at home and abroad, analyzes the malicious WiFi brought by the phishing APN DNS spoofing attack and SSLStrip attacks and other security issues. The malicious WiFi detection and protection technology adapted to the current WiFi security requirements is studied, and a prototype system is designed and implemented on the mobile terminal and server. The main work of this paper is as follows: firstly, the security threats of malicious WiFi are analyzed, and the existing methods and characteristics of detection and protection are summarized. Secondly, the key technologies of malicious WiFi detection and protection are studied, including WiFi hot spot feature fingerprint extraction technology, feature fingerprint similarity detection technology, malicious WiFi hot spot location technology, man-in-the-middle attack detection and protection technology. Thirdly, the malicious WiFi detection and protection system is designed. Finally, the prototype system of detection and protection is implemented on the mobile terminal and server, and the testing work is completed. The main achievements of this paper are as follows: first, by analyzing the field information of the device frame, this paper proposes a WiFi device feature fingerprint extraction algorithm and fingerprint similarity detection algorithm. The two algorithms are applied to the detection of WiFi environment before access and malicious detection of WiFi during access. Secondly, this paper proposes a WiFi hot spot location algorithm, which uses mobile terminals to locate malicious WiFi hotspots, and provides an active protection against malicious WiFi hotspots. Thirdly, this paper analyzes the principle of malicious man-in-the-middle attack. Firstly, it uses MAC contrast method and domain name dialing method to realize malicious detection, and then uses static binding router IP and MAC method to realize malicious detection. Solve the problem of malicious WiFi detection after access. The research results of this paper can solve many kinds of security problems brought by malicious WiFi, using malicious WiFi detection technology and man-in-the-middle attack detection technology to support malicious detection before and after access, when malicious WiFi is detected, The malicious WiFi location technology is used to detect the malicious WiFi location and to protect the malicious WiFi hotspots. The test results show that the system can meet the system objectives and requirements proposed in this paper.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN92

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相关硕士学位论文 前3条

1 顾杨;基于无线设备特征指纹的无线钓鱼接入点检测技术研究[D];南京邮电大学;2014年

2 杨骏元;基于多特征指纹的舆情数据重复识别方法[D];南京大学;2016年

3 徐龙雨;恶意WiFi检测与防护技术的研究与实现[D];北京交通大学;2017年

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本文编号：2059221