| Summary: | 博士 === 國立中興大學 === 資訊科學與工程學系 === 96 === The wireless LAN (WLAN), which contains Access Points (AP) and
remote devices, has become increasingly popular due to its low
price and easy installation. However, the popularity of the WLAN
increases the threat of network security. One of the important
security problems is the rogue AP problem. In unprotected areas,
an unauthorized AP can be plugged into the LANs of most
organizations quickly and easily, the matter which results in
serious security problems. Network managers always look at two
useful functions on the AP and the remote device to resist the
invasion of the rogue AP. One is to detect whether illegal APs are
deployed on the managed area. The second is to predict the
position of a remote device from the rogue AP.
To detect an AP, the network manager traditionally takes an
electric wave sensor across the whole protected place. This method
of detection is very difficult and inefficient. This study
presents a new method to detect an AP without additional hardware
and intense effort. This new method determines whether the network
packets of an IP are routed from APs according to client-side
bottleneck bandwidth. The network manager can then perform his job
from his office by monitoring the packets passing through the core
switch. The experimental results indicate that the accuracies of
this method constantly remain above 99%. The proposed method can
effectively reduce the detailed labor of the network manager and
increase the network security.
Once a rogue AP is detected, the next task is to find the location
of the illegal user. Due to the rogue AP problem and the demand
for context-aware services inside buildings, the WLAN-based
location determination has emerged as a significant research
topic.
However, prediction accuracy remains a primary issue in the
practicality of WLAN-based location determination systems. This
study proposes an innovative scheme that utilizes mobile user
orientation information to improve prediction accuracy.
Theoretically, if the precise orientation of a user can be
identified, then the location determination system can predict
that user''s location with a high degree of accuracy by using the
training data of this specific orientation. In reality, a mobile
user''s orientation can be estimated only by comparing variations
in received signal strength; and the predicted orientation may be
incorrect. Incorrect orientation information causes the accuracy
of the entire system to decrease. Therefore, this study presents
an accumulated orientation strength algorithm which can utilize
uncertain estimated orientation information to improve prediction
accuracy. Implementation of this system is based on the Bayesian
model, and the experimental results show the effectiveness of the
proposed approach.
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