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dc.contributor.author | Muhammad Azam, 01-247202-010 | |
dc.date.accessioned | 2022-12-22T06:23:06Z | |
dc.date.available | 2022-12-22T06:23:06Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | http://hdl.handle.net/123456789/14494 | |
dc.description | Supervised by Dr. Kashif Naseer Qureshi | en_US |
dc.description.abstract | The geolocation information refers to an Internet Protocol (IP) address which is useful for several Internet applications such as cyber security analysis, content delivery, product advertising, fraud detection, and prevention approaches. IP to geo-location mapping requires landmarks values to locate a user IP that conceals its geo-location (latitude longitude). The mapping approach for true IP to geolocation plays a vital role in the protection of databases and software systems-based applications. The accuracy performance of such mapping approaches is directly impacted by delay-distance relations and limited visible landmarks among network entities. Several approaches and mathematical models have been designed to overcome these issues such as trace route, ping, and landmarks. Due to the dynamic nature of the internet, many issues have been observed like weak connectivity, congestion, and delays. Achieving high accuracy in IP location mapping is an uphill task. GeoCAM is a recent approach to finding the real IP to geo-location with maximum accuracy and to finding the delay relation between the target and landmarks. However, accuracy, reliability, and latency can be further improved based on the last route between Target IP and landmarks. This research proposes a multi-measurement (passive active) framework that uses the Last Router Geo-location (LRG) and filtration shortlisting algorithm. Closed-Circuit Televisions (CCTVs) landmarks are used as a high-quality landmark. The proposed framework identifies the exact location of the target by locating the landmarks based on delay distance conversions. Extensive simulation experiments are conducted to find the precise location of a target IP with higher accuracy and reliability. The accuracy of the LRG framework is improved from 94.20 % to 96 % using passive and active approaches | en_US |
dc.language.iso | en | en_US |
dc.publisher | Computer Sciences | en_US |
dc.relation.ispartofseries | MS(CS);T-01884 | |
dc.subject | Mapping Approach | en_US |
dc.subject | Geo-location Mapping | en_US |
dc.title | Mapping Approach for True Internet Protocol Geo-location Information using Active and Passive Methods | en_US |
dc.type | MS Thesis | en_US |