A Method for Detecting Unauthorized Internet Access Node in Private Financial Network
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Recently, many companies make efforts to enhance security to detect and prevent an APT(Advanced Persistent Treat) attack that mainly target on the companies' PC devices. Most global companies run several branch offices that have numerous PC devices, but they are not easily controlled by a central security policy. Although security policies enforce to prevent unauthorized internet access, there are various detour techniques such as using tethering, open VPN or RogueAP. If a company fails to control all end user's PC devices, this can threaten the company's overall security. Especially, this can be the most critical problem in finance business domain. In this paper, we introduce a method to detect unauthorized internet access node in the closed private network. We conduct this method to find out the unauthorized nodes against the security policy. We deploy this detection method in the real network of a finance company in South Korea. As a result, we can classify several types of unauthorized nodes, and improve the detection techniques.
Abstract
Recently, many companies make efforts to enhance security to detect and prevent an APT(Advanced Persistent Treat) attack that mainly target on the companies' PC devices. Most global companies run several branch offices that have numerous PC devices, but they are not easily controlled by a central security policy. Although security policies enforce to prevent unauthorized internet access, there are various detour techniques such as using tethering, open VPN or RogueAP. If a company fails to control all end user's PC devices, this can threaten the company's overall security. Especially, this can be the most critical problem in finance business domain. In this paper, we introduce a method to detect unauthorized internet access node in the closed private network. We conduct this method to find out the unauthorized nodes against the security policy. We deploy this detection method in the real network of a finance company in South Korea. As a result, we can classify several types of unauthorized nodes, and improve the detection techniques.
참고문헌 (10)
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