Abstract
Given that entropy-based IT technology has been applied in homes, office buildings and elsewhere for IT security systems, diverse kinds of intelligent services are currently provided. In particular, IT security systems have become more robust and varied. However, access control systems still depend on tags held by building entrants. Since tags can be obtained by intruders, an approach to counter the disadvantages of tags is required. For example, it is possible to track the movement of tags in intelligent buildings in order to detect intruders. Therefore, each tag owner can be judged by analyzing the movements of their tags. This paper proposes a security approach based on the received signal strength indicators (RSSIs) of beacon-based tags to detect intruders. The normal RSSI patterns of moving entrants are obtained and analyzed. Intruders can be detected when abnormal RSSIs are measured in comparison to normal RSSI patterns. In the experiments, one normal and one abnormal scenario are defined for collecting the RSSIs of a Bluetooth-based beacon in order to validate the proposed method. When the RSSIs of both scenarios are compared to pre-collected RSSIs, the RSSIs of the abnormal scenario are about 61% more different compared to the RSSIs of the normal scenario. Therefore, intruders in buildings can be detected by considering RSSI differences.
Highlights
Given that entropy is the key concept of IT security systems, diverse kinds of security algorithms based on entropy have been developed and applied
When the received signal strength indicators (RSSIs) of both scenarios are compared to pre-collected RSSIs, the RSSIs of the abnormal scenario are about 61% more different compared to the RSSIs of the normal scenario
This paper proposes an intelligent intruder detection security approach based on received signal strength indicators (RSSIs) of tags collected by access points
Summary
Given that entropy is the key concept of IT security systems, diverse kinds of security algorithms based on entropy have been developed and applied. Tags are one of the broadly utilized approaches in security IT systems. Tags can be replaced by other security systems, but at significantly greater cost. For tag utilization, their weakness should be addressed. Approaches to recognize the owners of tags should be provided. Additional environmental information can be utilized such as the time when tags are utilized or the movement patterns of owners who hold tags. This paper proposes an intelligent intruder detection security approach based on received signal strength indicators (RSSIs) of tags collected by access points. The RSSIs of tags are measured and analyzed to recognize the patterns of the movements of residents.
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