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dc.contributor.authorBarasa, Kunjira Fredrick
dc.date.accessioned2019-10-28T09:42:45Z
dc.date.available2019-10-28T09:42:45Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/11071/6700
dc.descriptionThesis submitted in partial fulfillment of the requirements for the Degree of Master of Science in Information Technology (MSIT) at Strathmore Universityen_US
dc.description.abstractWireless internet access has become common throughout the world. IEEE 802.11 Wireless fidelity (Wi-Fi) is now a common internet access standard almost becoming a requirement in homes, offices, universities and public places due to developments in Bring-Your-Own-Device (BYOD), mobile telephony and telecommuting. With the proliferation of Wi-Fi comes a number of information security challenges that have to be addressed. One of the major security threats that comes with Wi-Fi is the presence of rogue access points (APs) on the network. Unsuspecting employees in a company or attackers can introduce rogue APs to a secure wired network. The problem is amplified if the wireless local area network (WLAN) consist of multivendor APs. Malicious people can leverage on rogue APs to perform passive or active attacks on a computer network. Therefore, there is need for network administrators to accurately, with less effort, detect and control presence of rogue APs on multivendor WLANs. In this thesis, a solution that can accurately support detection of rogues APs on a multi-vendor AP WLAN without extra hardware or modification of AP firmware is presented. In the solution, information from beacon frames is compared to a set of approved parameters. Intervention of a network administrator is included to prevent MAC address spoofing. A structured methodology was adopted in developing the model on a Windows operating system. Python programming language was used in coding the system with Scapy and Tkinter as the main modules. SQLite database was used to store required data. The system was tested on a setup WLAN that composed of three different access points in a University lab. It was able to capture beacon frames sent by the access points and extracted MAC address, SSID and capability information as the key parameters used in identifying and classifying the access points. The system uses the captured information to automatically compare it against an existing database of authorized parameters. It is then able to classify an access point as either rogue or authorized. The system issued alerts that described the detected APs to a network administrator. The rest of this document gives details of scholarly works that are pertinent to the study, the research methodology used, implementation and testing of the model followed by discussions of findings and the conclusions and recommendations made by the researcher.en_US
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectRogue access pointen_US
dc.subjectDetection frameworken_US
dc.subjectMultivendor access pointen_US
dc.subjectWLANen_US
dc.titleRogue access point detection framework on a multivendor access point WLANen_US
dc.typeThesisen_US


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