• Journal of Communications and Networks
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• v.11 no.6
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• pp.544-555
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• 2009

This work continues a trend of developments aimed at exploiting the physical layer of the open systems interconnection (OSI) model to enhance wireless network security. The goal is to augment activity occurring across other OSI layers and provide improved safeguards against unauthorized access. Relative to intrusion detection and anti-spoofing, this paper provides details for a proof-of-concept investigation involving "air monitor" applications where physical equipment constraints are not overly restrictive. In this case, RF fingerprinting is emerging as a viable security measure for providing device-specific identification (manufacturer, model, and/or serial number). RF fingerprint features can be extracted from various regions of collected bursts, the detection of which has been extensively researched. Given reliable burst detection, the near-term challenge is to find robust fingerprint features to improve device distinguishability. This is addressed here using wavelet domain (WD) RF fingerprinting based on dual-tree complex wavelet transform (DT-$\mathbb{C}WT$) features extracted from the non-transient preamble response of OFDM-based 802.11a signals. Intra-manufacturer classification performance is evaluated using four like-model Cisco devices with dissimilar serial numbers. WD fingerprinting effectiveness is demonstrated using Fisher-based multiple discriminant analysis (MDA) with maximum likelihood (ML) classification. The effects of varying channel SNR, burst detection error and dissimilar SNRs for MDA/ML training and classification are considered. Relative to time domain (TD) RF fingerprinting, WD fingerprinting with DT-$\mathbb{C}WT$ features emerged as the superior alternative for all scenarios at SNRs below 20 dB while achieving performance gains of up to 8 dB at 80% classification accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.979-982
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• 2013

위치정보를 이용한 서비스가 요구가 증가함에 따라, 실외를 중심으로 이뤄지던 위치정보서비스는 실내를 중심으로 요구되고 있다. 더불어 좀더 정확한 실내측위 시스템에 대한 필요성도 증가되고 있다. 최근의 위치 정보 서비스는 스마트폰의 보급과 함께 모바일 기기의 환경이 이용되고 있다. 본 논문은 스마트 디바이스 기반으로 WLAN(Wireless Local Area Network)과 DATABASE 를 이용한 Fingerprinting 방식을 제안한다. 또한 기존의 Fingerprinting 방식에 스마트 디바이스에 내장된 Gyroscope sensor 를 이용하여 모바일 환경에서 일부 영역에서 발생할 수 있는 신호의 오차를 보정하는 새로운 방법도 제시한다. 실제 테스트 환경을 구축하여 실험한 결과도 제시하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.631-646
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• 2020

The government is pursuing a policy to remove plug-ins for public and private websites to create a convenient Internet environment for users. In general, financial institution websites that provide financial services, such as banks and credit card companies, operate fraud detection system(FDS) to enhance the stability of electronic financial transactions. At this time, the installation software is used to collect and analyze the user's information. Therefore, there is a need for an alternative technology and policy that can collect user's information without installing software according to the no-plug-in policy. This paper introduces the device fingerprinting that can be used in the standard web environment and suggests a guideline to select from various techniques. We also propose a user authentication model using device fingerprints based on machine learning. In addition, we actually collected device fingerprints from Chrome and Explorer users to create a machine learning algorithm based Multi-class authentication model. As a result, the Chrome-based Authentication model showed about 85%~89% perfotmance, the Explorer-based Authentication model showed about 93%~97% performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1197-1209
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• 2016

As Indoor Positioning System demands due to increased penetration and utilization of smart device, Indoor Positioning System using Wi-Fi or BLE(Bluetooth Low Energy) beacon takes center stage. In this paper, a terminal location of the user is calculated through Microscopic Trilateration using RSSI based on BLE. In the next step, a fingerprinting map appling approximate value of Microscopic Trilateration increases an efficiency of computation amount and energy for Indoor Positioning System. I suggest Indoor Positioning Algorithm based on BLE fingerprinting considering efficiency of energy by conducting precise Trilateration that assure user's terminal position by using AP(Access Point) surrounding targeted fingerprinting cells. And This paper shows experiment and result based on An Suggesting Algorithm in comparison with a fingerprinting based on BLE and Wi-Fi that be used for Indoor Positioning System.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1179-1195
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• 2018

Recently, a variety of attacks on web services have been occurring through a multiple access environment such as PC, tablet, and smartphone. These attacks are causing various subsequent damages such as online fraud transactions, takeovers and theft of accounts, fraudulent logins, and information leakage through web service vulnerabilities. Creating a new fake account for Fraud attacks, hijacking accounts, and bypassing IP while using other usernames or email addresses is a relatively easy attack method, but it is not easy to detect and block these attacks. In this paper, we have studied a method to detect online fraud transaction and obsession by identifying and managing devices accessing web service using web-based device fingerprinting. In particular, it has been proposed to identify devices and to manage them by scoring process. In order to secure the validity of the proposed scheme, we analyzed the application cases and proved that they can effectively defend against various attacks because they actively cope with online fraud and obtain visibility of user accounts.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.271-280
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• 2023

Pedestrian Dead Reckoning (PDR) methods using initial sensors are being studied to provide the location information of smart device users in indoor environments where satellite signals are not available. PDR can continuously estimate the location of a pedestrian regardless of the walking environment, but has the disadvantage of accumulating errors over time. Unlike this, WiFi signal-based wireless positioning technology does not accumulate errors over time, but can provide positioning information only where infrastructure is installed. It also shows different positioning performance depending on the environment. In this paper, an integrated positioning technology integrating two positioning techniques with different error characteristics is proposed. A technique for correcting the error of PDR was designed by using the location information obtained through WiFi Measurement-based fingerprinting as the measurement of Extended Kalman Filte (EKF). Here, a technique is used to variably calculate the error covariance of the filter measurements using the WiFi Fingerprinting DB and apply it to the filter. The performance of the proposed positioning technology is verified through an experiment. The error characteristics of the PDR and WiFi Fingerprinting techniques are analyzed through the experimental results. In addition, it is confirmed that the PDR error is effectively compensated by adaptively utilizing the WiFi signal to the environment through the EKF to which the adaptive error covariance proposed in this paper is applied.

• Smart Media Journal
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• v.4 no.2
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• pp.68-76
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• 2015

Recently, research on indoor locating techniques using smart device sensors has been conducted actively, Owing to the exponential increase in the use of various smart devices. However, in order to develop indoor location techniques, there are limitations due to the requirement that the tracking system has to function without GPS. In this paper, we propose an accurate indoor locating system that does not require additional infrastructure. The proposed scheme is developed based on the idea that the advantages and disadvantages of "Wi-Fi Fingerprinting" and "Step Detection" techniques are complementary. In the proposed scheme, we track users with "Step Detection," and correct errors with "Wi-Fi Fingerprinting." In this paper, we demonstrate the effectiveness and feasibility of our proposed scheme through experiments.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.740-750
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• 2018

There are a great number of Internet-connected devices and their information can be acquired through an Internet-wide scanning tool. By associating device information with publicly known security vulnerabilities, security experts are able to determine whether a particular device is vulnerable. Currently, the identification of the device information and its related vulnerabilities is manually carried out. It is necessary to automate the process to identify a huge number of Internet-connected devices in order to analyze more than one hundred thousand security vulnerabilities. In this paper, we propose a method of automatically generating device information in the Common Platform Enumeration (CPE) format from banner text to discover potentially weak devices having the Common Vulnerabilities Exposures (CVE) vulnerability. We demonstrated that our proposed method can distinguish as much adequate CPE information as possible in the service banner.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.9
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• pp.271-282
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• 2015

In the business environment BYOD(Bring Your Own Device) is used and being expanded continuously. According to a survey conducted by Cisco in 2012 on 600 companies, 95% of them are already permitting the use of BYOD in their work environments so that productivity of their employees has improved as a result. Gartner predicted that the use of BYOD will be caused new security threat. They also suggested to introduce NAC(Network Access Control) to resolve this threat, to separate network zone based on importance of their business, to establish the policy to consider user authority and device type, and to enforce the policy. The purpose of this paper is to design and implement the NAC for granular access control based on IEEE(Institute of Electrical and Electronics Engineers) 802.1X and DHCP(Dynamic Host Configuration Protocol) fingerprinting, and to analyze the performance on BYOD environment.