Design of MDM System using BLE Beacon and Extended Kalman Filter

Transcription

1 Indian Journal of Science and Technology, Vol 9(29), DOI: /ijst/2016/v9i29/94761, August 2016 ISSN (Print) : ISSN (Online) : Design of MDM System using BLE Beacon and Extended Kalman Filter Lim II-Kwon 1, Lee Seoung Hyeon 2, Lee Jae-Gwang 1, Mo Eun-Su 1, Lee Jun-Hyeon 1 and Lee Jae-Kwang 1 * 1 Department of Computer Engineering, Hannam University, Daedeok-gu, Daejeon, 34430, Korea; iklim@netwk.hnu.kr, jplee@netwk.hnu.kr, esmo@netwk.hnu.kr, jhlee@netwk.hnu.kr, jklee@hnu.kr 2 Industrial Control System Research Section, ETRI, 34129, Korea; duribun2@gmail.com, tmraj@mech.sastra.edu Abstract Background/Objectives: For the security control, MDM effectively limits functionality of smart phone. However, the control and monitoring of mobile devices causes the user to suffer much inconvenience. Methods/Statistical Analysis: We performed experiments applying the Kalman filter and the BLE to improve location accuracy for MDM system. And designed a MDM system using the BLE and the central server, smart phones, CCTV, WiFi, etc. Findings: In the system proposed in this study, regardless of security zones and other regions through the existing RFID tags or input/output gates, the user s access information is sent to the mobile security server depending on the precise indoor position by using beacons regarding the staff who has entered the security zone. Also, PUSH messages are transmitted so that mobile security control policies can be applied depending on the security classification of each zone of the house. For the proposed system, we were experimented on using six virtual BLE beacons in the system server. And noises included correction values obtain into more accurate correction values by applying the Kalman filter. Application/Improvements: The error of location measurement contained the noise turned out (11, 9.6) in the positioning (x, y). However, reduce error to (3.47, 5.02) if applying the extended Kalman filter. Keywords: BLE Beacon, Bluetooth 4.0, Kalman Filter, MDM 1. Introduction Smart phones are highly utilized, compared to desktop PCs, due to built-in GPSs, high-resolution cameras, etc. The BYOD environment of taking advantage of smart phones to work propagated widely. With the expansion and spread of smart devices and BYOD, shares of desktop PCs in 2012 fell to less than half 1. The introduction of BYOD allowed the user to take advantage of smart phones for their tasks anytime, anywhere business. While the introduction of mobile terminals and wireless networks to various works caused new threats problems. MDM (Mobile Device Management) is attracting attention as a solution to the security problems. Thus, MDM has been designated as the item subject to Common Criteria (CC) and thus the CC certification is being promoted. Also, according to the Radicati Group s report, the worldwide market for MDM revenue will grow by 21% from 2012 to 2016 and is expected to reach 11 billion dollars 1-3. As for the security of mobile devices using the MDM, the user is highly dissatisfied, unlike PC-based security. Because mobile units are a very personal equipment. Through cameras, voice recorders, USBs, etc., laboratories, knowledge-based industries, military agencies, etc. strictly prohibit key information inside their facilities from being leaked. Thus, they *Author for correspondence

2 Design of MDM System using BLE Beacon and Extended Kalman Filter cannot help using MDM. For that reason, the industry tries to lowering the user s complaint by shutting off the device in a way of blocking it automatically only when it entered the security zone. To this end, indoor positioning and control technologies are required, Thus, various ways such as existing base stations, AP-based methods, or access control systems (Speed Gate, etc.) linking based methods have been presented, and various studies on the areas conducted. Thus, this study attempted to identify indoor location using the BLE beacon and thereby designed MDM to be operated only in controlled areas. Also, this study presented the preparedness for security vulnerabilities using of the BLE beacon and confirmed the efficiency through an experiment of the Kalman filter 4, Related Works 2.1 MDM Service MDM refers to a system using OTA (mobile radio transmission technology, Over The Air), which can remotely manage a mobile device anytime, anywhere if it is in a state of Power On. MDM was designed to manage mobile devices such as mobile phones regarding deployment of applications, changing data and environment settings, losing mobile devices, etc. It was aimed to optimize mobile security and functionality via short service downtime and at minimum costs. However, as the need for security management regarding mobile devices has emerged, MDM is becoming a key element of mobile security. MDM is providing comprehensive protection functions against a variety of communication channels, such as mails, web and groupware, USB storage media, etc. Where data that can disclosed in the corporate business environment by providing secured communication services and at the same time is performing enterprise monitoring and control over the user s environment Bluetooth Low Energy Beacon In June 2010, Bluetooth 4.0 (so called BLE (Bluetooth Low Energy), BT-LE) equipped with low-energy technology was announced. Of these Bluetooth LE technologies, the technology getting the most attention is beacon technology. In this regard, close services can be developed by utilizing a small amount of information included accordingly. As the beacon periodically broadcast a small data, terminals that act as an observer or play a central role receive the data and show the user messages such as advertising by analyzing the information contained in the data. In these data, the following information as shown in [Table 1] is carried on. As such, the beacon has received the most attention among existing indoor location positioning technologies due to its advantages, such as proximity service possible by using a small amount of information, low power consumption, wide radius (50m), low prices, etc 7-13, 18, 19. Table 1. BLE beacon transmitting information Name Proximity UUID(Universally Unique Identifier): Description The identifier used to distinguish the beacon from others; for example, it identifies a certain brand. Major number Minor number Tx power Used to group related beacons installed in the shop; for example, the beacons installed on the ship use the same beacon. Used to identify individual beacons Value used to infer how close the user located from the signal strength 2 Indian Journal of Science and Technology

3 Lim II-Kwon, Lee Seoung Hyeon, Lee Jae-Gwang, Mo Eun-Su, Lee Jun-Hyeon and Lee Jae-Kwang Figure Extended Kalman Filter Algorithm of the Extended Kalman Filter. The Kalman filter is a recursive filter tracking the linear and non-linear state containing noises, first proposed by Rudolf Kalman in 1960 [ ]. The Kalman filter accepts the measured value as an input and processes it internally to output an estimated value (). Since the Kalman filter applied basically to the linear system, it is not used in the real life composed of mostly non-linear systems. The extended Kalman filter developed to solve these problems. The extended Kalman filter undergoes the estimating and forecasting process as seen in [Figure 1] below 14, Design of MDM System 3.1 Design of Reference Points for Positioning [Figure 2] illustrates the design of reference points for positioning by selecting beacons as a base station (BS). Each BS (Base Station) order is given to the six beacons and the locations and of the remaining five beacons are calculated. Based on this, the design was proceeded to calculate x, y of the user and the measuring equipment via. Distance values measured in beacons and beacon. Figure 2. Layout of Beacons and Design of Reference Points. Indian Journal of Science and Technology 3

4 Design of MDM System using BLE Beacon and Extended Kalman Filter Table 2. EKF Processing for Positioning Beacons Indoor 3.2 Location Value Correction Utilizing Extended Kalman Filter For beacons, the distance value is calculated by transmitting the signal strength the data at an interval of 100ms and receiving the values from the mobile device. These distance values were divided into 4 stages, including immediate (0-20cm), near (20cm~2m), far (2m~70m), and unknown (impossible to measure), to show proximities. Due to the nature of beacons, it is impossible to measure the accurate distance value more than 2m. Thus, the instrumental values measured at mobile devices are corrected into an exact value through the process as shown in [Table 2] using the algorithm of the extended Kalman filter as shown in [Figure 1]. 4. Experiment of Application of Extended Kalman Filter 4.1 Design and Construction of Experiment Environment For the location information authentication between the mobile device and the server, the following [figure 3] as communication protocol was designed, A combination of unique ID values, major IDs, minor IDs, and signal strengths of beacon; information of beacons over the distance and location accordingly, AP eigenvalues of WIFI, MAC addresses; and signal strength values. The combination was encrypted to a private key of the mobile device. Figure 3. Protocol Structure. 4 Indian Journal of Science and Technology

5 Lim II-Kwon, Lee Seoung Hyeon, Lee Jae-Gwang, Mo Eun-Su, Lee Jun-Hyeon and Lee Jae-Kwang Figure 4. Entire System Structure. In the system proposed in this study, regardless of security zones and other regions through the existing RFID tags or input/output gates, the user s access information is sent to the mobile security server depending on the precise indoor position by using beacons regarding the staff who has entered the security zone. Also, PUSH messages are transmitted so that mobile security control policies can be applied depending on the security classification of each zone of the house. For the device of the user who has received the control message, the functions of cameras and removable storage devices become under control in the control zone. When the user, who has completed the work, comes to go out again to the regions out of control through the door. The mobile security server will receive the door entry information. The push message unblocking the security control policy applied accordingly will be transmitted to the device. Also, physical security is reinforced utilizing CCTVs, etc., as shown in the following [Figure 4]. Table 3. Experimental System Configuration Segment Item Configuration Operating system CentOS release 6.5 (Final) Software configuration Number of OS KERNEL BITS 64 Developed language C DB Oracle Database Express Edition 11g Release 2 Hardware specifications Graph CPU Memory freemat Intel(R) Core(TM)2 Quad CPU 2.50GHz 5,990,856 kb Indian Journal of Science and Technology 5

6 Design of MDM System using BLE Beacon and Extended Kalman Filter For experiments, the distance value in the real environment was virtually created utilizing 6 beacons and including distance values and noises, then, correct values were calculated using the extended Kalman filter. [Table 3] shows the experimental environment. 4.2 Experiment Result [Table 4] shows the results of the simulation experimented in the system server by using six virtual Bluetooth LE beacons. The first column Age of the table shows the number of recursive times. The second and third columns Table 4. Experiment result Age Noises included x Noises included y Filtered x Filtered y Age Noises included x Noises included y Filtered x Filtered x Indian Journal of Science and Technology

7 Lim II-Kwon, Lee Seoung Hyeon, Lee Jae-Gwang, Mo Eun-Su, Lee Jun-Hyeon and Lee Jae-Kwang Figure 5. Simulated Results of Indoor Positioning of Beacons. present the original x, y coordinate values where included noises. The fourth and fifth columns show the x, y coordinate values filtered through the Kalman filter. Regarding the times of recursions, recursion was performed a total of 200 times. [Figure 5] shows a graph of diagrammatic points to express the simulated results as above. * Measurements indicated using * in the graph are x coordinate values and + at the top show y coordinate values. The of the bottom means filtered X coordinate values; refers to Y coordinate values. Filtered values were allowed to be displayed at the bottom by correction values to distinguish it from measured values during graphical representation. Noises included x, y values are wide measured values, not showing consistent numeric values. This explain by the obtained values: the maximum value 3.11 and the minimum value -7.89, the maximum value of the filtered x coordinate -5.17, the minimum value The maximum value of the filtered y coordinate -2.96, the minimum value As such, noises included correction values obtain into more accurate correction values by applying the Kalman filter. 4.3 ISecurity Precautions According to Use of Beacons For beacons, two-way communication is not available according to their characteristics. This means that the call information of the beacon is not encrypted. Beacons broadcast only certain identifying information (Proximity UUID, Major, Minor). It means that the information of beacons can be easily obtained using a Bluetooth protocol analyzer or a mobile application. This thus implies that it is possible to generate beacons by duplicating the identification information to the cloned fake beacon. Also, there is a concern that when the indoor location positioning for the MDM system is made using beacons, an unexpected Location can come out. Beacons do not need external power and are small in size and light in weight. Installation is easy as they are installed by simply attaching or placing them to the wall. Thus, someone can modulate the Location information by replacing a different place for malicious purposes 16, 17. For beacons, security threats exist as above. Thus, a certificate for the Location carry out additionally to prevent the beacon from changing in its Location and to Indian Journal of Science and Technology 7

8 Design of MDM System using BLE Beacon and Extended Kalman Filter Figure 6. How to Prepare Beacons Spoofing. prevent the replicated beacon from spoofing. The location is authenticated in duplicate for additional indoor positioning via the WIFI with less accuracy but with high efficiency, compared to beacons. When the beacon configured and constructed as a WIFI location [Figure 6]. 5. Conclusions The development of communication technology offers convenience by providing some services. However, security threats through mobile devices are getting worse. Accordingly, control and security technologies of various smart phones have been developed. However, users have complained of discomfort as higher security lead to less convenience, especially, they are highly dissatisfied with smart phones due to their nature as a personal device. This study presented the design of an MDM system to limit mobile devices in the controlled area depending on the room location for the ease of the MDM system for internal security. Accordingly, a security frame was also designed at the security issues that may arise. Since the release of the Bluetooth low energy, beacons are in the spotlight as a new marketing strategy and as a technology for indoor positioning. The refection of these beacons on the MDM technology for indoor positioning is expected to minimize the user s inconvenience. However, beacons make it possible only one-way broadcast communication, not two-way communication. Thus, they send only specific information, which may lead to cloning beacons and spoofing attacks. Also beacons transmit the location information in the form attached to a certain place, vulnerable to physical security. Additionally, electronic attacks can be made by jamming of bands and channel signals of beacons. Therefore, the MDM system was designed to makes sure physical security, access control, and security policies go along. Simulation experiments were conducted using a Kalman filter to ensure the effectiveness of the extended Kalman filter. Through these experiments, the application of the extended Kalman filter demonstrated that the error reduced to (3.47, 5.02). In the future, it will be necessary to make more advanced spoof preparedness through a 8 Indian Journal of Science and Technology

9 Lim II-Kwon, Lee Seoung Hyeon, Lee Jae-Gwang, Mo Eun-Su, Lee Jun-Hyeon and Lee Jae-Kwang unique certification number of the beacons and to conduct research and implementation for the preparation for physical security. 6. Acknowledgment This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014R1A1A ). 7. References 1. Chang-Su Jeon. Rep. of Korea: Information Security Company: Market trends of MDM and issues and countermeasures of introduced agencies. KESIC Issue Report Hyeon-Dae Rha, Su-Kyoung Kang, Chang-Jae Kim, Nam- Yong Lee. A Study on Quality Evaluation Model of Mobile Device Management for BYOD. Journal of The Korean Association of Computer Education. 2014; 17(6): Sang-Su Jeon. Rep. of Korea: Information Security Company: Issues and measures of market trends and introduced institutions on MDM. KESIC Issue Report Song-Hoon Han. Yongin, Rep. of Korea: Dankook University: A Case Study of Implementing a Mobile Security System using MDM System and Physical Access Data. Department of Information and Communications Technology, A Master s thesis Sung-Tae Kang, In-June Jo. Individual users based SmartPhone Remote Management System Design and Implementation. Journal of Korea Institute of Information and Communication Engineering. 2012; 16(12): Kang-Hyun Lee, Doo-Shik Yoon. Effective approach in MDM for mobile security. Journal of Korea Institute of information Security & Cryptology. 2012; 23(2): Gomez Carles, Oller Joaquim, Paradells Josep. Overview and Evaluation of Bluetooth Low Energy: An Emerging Low-Power Wireless Technology. Journal of Sensors ; 12(9): Rep. of Korea: Korea Communications Agency: Beacon, the core infrastructure of location-based services rapid rise, Trend Focus. 2012; Yeong-Jae, Jang. Rep. of Korea: Telecommunications Technology Association: [WPAN] Bluetooth v4.0 - low energy Technology Trends. ICT Standard Weekly. 2011; (16). 10. Kirkland: Bluetooth SIG Proprietary: Specification of the Bluetooth System Version Salas AC. Barcelona Universitat Politecnica de Catalunya: Indoor Positioning System based on Bluetooth Low Energy. A Degree s Thesis Submitted to the Faculty of the Escola Tecnica d Enginyeria de Telecomunicacio Dahlgren Erik, Mahmood Hasan. Chalmers University of Technology: Evaluation of indoor positioning based on Bluetooth Smart technology, Master of Science Thesis in the Programme Computer Systems and Networks. Department of Computer Science and Engineering Yong Zhu Jian, C.Z., Haiyong Luo, Zhaohui Li. RSSI Based Bluetooth Low Energy Indoor Positioning. Rep. of Korea: Proceedings of 2014 International Conference on Indoor Positioning and Indoor Navigation. 2014; Kim Seong-Pil. Rep. of Korea: Ajin Publishing: Understanding of the Kalman filter using MATLAB Kalman RE. A New Approach to Linear Filtering and Prediction Problems. Transactions of the ASME Journal of Basic Engineering. 1960; Singhal Karan. ibeacon Spoofing: Security and Privacy Implications of ibeacon Technology, Development at Tufts University. Date accessed: 24/05/2016: Available at: Anti-spoofing with Aplix Authentication Service. Date accessed: 24/07/2015: Available from: gl/2tvjbm. 18. Priyalakshmi B, Kirthi J. Mini UWB-Bluetooth Antenna Design with Band-Notched Characteristics. Indian Journal of Science and Technology Jan; 9(1). DOI: / ijst/2016/v9i1/ Shyla MV. Computational Analysis of Optimal Sensor Position in Indoor Environment. Indian Journal of Science and Technology Mar; 8(5). DOI: /ijst/2015/ v8i5/ Indian Journal of Science and Technology 9