Optical Wireless Interception Vulnerability Analysis of Visible Light Communication System

Transcription

1 Optical Wireless Interception Vulnerability Analysis of Visible Light Communication System Jie Lian, Xu Wang, Mohammad Noshad and Maïté Brandt-Pearce University of Virginia, Charlottesville, VA VLNcomm, Charlottesville, VA, Abstract Visible light communication is a solution for highsecurity wireless data transmission. In this paper, we first analyze the potential vulnerability of the system from eavesdropping outside the room. By setting up a signal to noise ratio threshold, we define a vulnerable area outside of the room through a window. We compute the receiver aperture needed to capture the signal and what portion of the space is most vulnerable to eavesdropping. Based on the analysis, we propose a solution to improve the security by optimizing the modulation efficiency of each LED in the indoor lamp. The simulation results show that the proposed solution can improve the security considerably while maintaining the indoor communication performance. Index Terms visible light communication, security, physical layer, interception, eavesdropping, receiver aperture, modulation efficiency I. INTRODUCTION In the age of fourth generation communications, faster speed data transmission is still in high demand, especially indoors. Visible light communication (VLC) systems use white LEDs for communication, and can become the dominant indoor communication method because of their many advantages: LEDs can be simultaneously used for illumination and data transmission, they provide high-speed transmission, they are efficient lighting sources, and they have long life expectancy. VLC is also being considered as an alternative to Wi-Fi systems to provide wireless network access in indoor areas due to some critical shortcomings of Wi-Fi. A major-draw back of Wi-Fi system is its susceptibility to eavesdropping, which has limited its use in security sensitive environments. Radio frequency (RF) signals that are used in Wi-Fi systems can penetrate through walls, and this leakage can expose the information carried by these signals to hackers. Unlike Wi- Fi systems, the signals in VLC systems are blocked by any opaque object, and therefore, the signals cannot pass through the walls. We can assume the RF leakage from the VLC modulator is controlled. As a result, 1% security against outside eavesdroppers can be guaranteed in VLC systems if no light escapes the room. However, this is usually not the case in real scenarios: the light leaks out through glass doors and windows, which can impose security risks on the VLC users. In [1], the security risks of VLC systems due to the light leaked from under the door and through the key hole have been analyzed for various room setups. In [2], Mostafa and Lampe analyze the security of VLC systems in an indoor area against an internal hacker and, in [3], they propose a multiple input and single output (MISO) system to increase the privacy of VLC systems through pulse shaping. [4] presents a high security code division multiple access (CDMA) scheme for VLC systems, and derives an information leakage expression. Pan et. al. investigate the secrecy performance of a VLC system with a group of randomly distributed eavesdroppers in [5]. There have been more general analyses on the security of FSO systems that can also be extended to VLC systems [6]. To the best of our knowledge, there is no study on the information leakage of VLC systems through a window and its security risks. In this work we present an analysis for the strength of the VLC signals leaked through windows, and based on this, we calculate the specifications of devices required for eavesdropping. We divide the area outside the window into high risk and low risk regions based on the access to the line of sight (LOS) signals, and calculate the size of the minimum aperture in each region to achieve the minimum SNR required for detection of the information. We then propose a technique to reduce the size of the high-risk region by optimizing the modulation efficiency that controls the percentage of the optical power for carrying the data. This algorithm can provide a flexible highly secure communication link for indoor users and minimize the possibility of data interception in outdoor areas. The remainder of the paper is organized as follows. The VLC system is described in Section II, including the channel model, performance analysis, system security and optimization to minimize the security risk. In Section III, simulation results and analysis are presented. Finally, the paper is concluded in Section IV. A. Channel Model II. SYSTEM DESCRIPTION In this paper, we assume intensity-modulation and directdetection (IM/DD) because of the incoherence of the LED light. We consider an LED lamp fixture as illustrated in Fig. 1: a multi-led lamp model consisting of multiple LEDs with different inclination angles [7]. This structure is proposed to

2 cover more illumination area and provide more power to the corner areas. Furthermore, each LED can be configured to transmit light either bearing or not bearing information, giving the system more control. Below, we show how this type of structure can be used to advantage to diminish the security threat caused by windows in VLC systems. area of the reflection surface, ρ represents the reflection coefficient. d is the distance between LED q and user k. r qa is the unit vector pointing from the LED q towards the differential area of the reflection plane. Similarly, r and r ak are unit vectors pointing from LED q towards the kth user and from da to user k, respectively. In addition, l q represents the radiation unit direction vector from the center of the beam of LED q. z a is the normal unit vector of da. z k represents the kth user s normal unit vector. In (2) and (3), the notation x, y represents the angle between vectors x and y. Fig. 3 illustrates this notation. In addition, m is the Lambertian mode of the light source, which is related to the LED s half power semiangle Φ 1/2 by m = ln 2/ ln(φ 1/2 ) [9]. LED q Fig. 1. Multi-LED lamp model, (a) side view, (b) bottom view LED Lamp r, l q Radiation Direction da r, z k r, z ak k User k Fig. 2. A typical indoor VLC system. Fig. 3. LOS and non-los angles between the LED and the user In a typical indoor VLC environment as shown in Fig. 2, the transmitted light can be modeled as the combination of line of sight (LOS) and diffuse components. The diffuse component is caused by reflections off walls, ceiling, furniture and so on. In this work, only the reflections from the walls are taken into account. Since the intensity of the light diminishes through diffusion, only a single reflection is considered for the diffuse component. For the data rate of interest, we consider the channel as temporally non-dispersive. Thus, the channel loss between LED q and user k can be written as h = h (L) }{{} LOS + h (D), (1) }{{} Diffusion where the LOS and diffused parts can be represented as [8] and h (L) h (D) = = (m + 1) cosm r, l q cos r, z k S 2πd 2 ρ (m + 1) cos m r qa, l q cos r qa, z a 2πd 2 qa cos m r ak, z a cos r ak, z k da, πd 2 ak respectively, where S is the integrated area of the entire reflection surface in the indoor environment, da is a differential (2) (3) B. System Performance The criteria used to evaluate the performance of the VLC system are the bit error rate (BER) and the data rate. The relationship between these two metrics is discussed in this section. Since IM/DD is employed in VLC, M-ary pulse amplitude modulation (M-PAM) can be used to increase the data rate for a fixed transmitter bandwidth. Using M-PAM, a (log 2 M)-fold increase in the data rate compared with onoff keying (OOK) can be achieved. The choice of modulation constellation size M depends on the signal to noise ratio (SNR) at the receiver. In this paper, an adaptive technique is assumed, where the largest constellation size allowed by the SNR of the intended user is used to get the highest data rate [1]. We assume the desired-user SNR is determined by the channel quality, transmitted power, and the size of photodetector (PD). For a given channel, the SNR for user k in the indoor area can be calculated as ) 2 (rp A in Qq=1 β qh γ kin = where r represents the the responsivity of the PD. P is the transmitted power and Q is the number of LEDs. β q represents the modulation efficiency that describes the percentage of the qth LED s optical power used for data transmission. β q would σ 2 n (4)

3 3 m 5 m Fig m Vulnerable area outside the room Vulnerable Zone not affect the total emitting power of the LEDs. A in is the area of the intended receiver s PD in indoor area, which is small in VLC systems, where the receiver is in the room, a few meters from the transmitter. In this paper, we model that the noise includes thermal noise and shot noise. In indoor area, we assume that the thermal noise dominates the system. The variance of the thermal and shot noise (σ 2 n in (4)), can be computed as σ 2 thermal = 4κT κ R s /R L, and σ 2 shot = 2qrP r R s (5) where q is the electronic charge, κ is Boltzmann s constant, R s is the transmitted symbol rate. R L is the resistor in the circuit of the receiver. P r is the received optical power that can be calculated as P r = P A in Q q=1 h + P b, (6) where P b is the received optical power of background light. Using M-PAM, R s = R b /log 2 M, where R b represents the bit rate. For user k, if the modulation constellation size and the received SNR are fixed, we can find the BER by using [1] BER k M 1 Mlog 2 M erfc ( γkin (M 1) 2 ). (7) In this paper we assume the maximum constellation size for the intended receiver to achieve a BER 1 3 is always used. C. System Security The VLC system has high security because of the characteristics of light that it cannot penetrate opaque objects like walls. It keeps the communication system secure in the wireless physical-layer. When the eavesdroper cannot have a good quality channel, the transmitted information cannot be reconstructed [1]. The size of the receiver aperture (the lens placed in front of the PD) is a significant factor to be considered by eavesdroppers. The smaller the eavesdropper receiver aperture becomes, the harder it is to expose it, since a large receiver aperture makes the eavesdropping equipment easily spotted. However, a too small size receiver aperture cannot support a sufficiently high SNR to intercept the signal. The required eavesdropper SNR depends on the desired modulation constellation size and BER. Consider the case that the eavesdropper is outside the window during the daytime. The background sunlight is dominant, which can be calculated as P b = Φ sun, (8) where Φ sun is the power density of the sunlight on the ground, which can be calculated from the sunlight illumination. represents the desired eavesdropper aperture. The additional shot noise from sunlight helps to lower the received SNR, and therefore improves the security of the communications. In this paper, we assume the sunlight illumination is sufficiently bright to make the shot noise caused by background light the dominant noise source. For this case, the eavesdropper minimum receiver aperture required to obtain a BER 1 3 can be calculated as 2qR s Φ sun γ kout Q r(ηp q=1 β qh ), (9) 2 where γ kout is the SNR for the eavesdropper for outdoor, which can be calculated by 4. η is the transmittance percentage through normal glass. For the indoor area or the outside area at night, we assume the background light is negligible, and therefore the thermal noise is dominant. For this case, the minimum receiver aperture (for both intended and unintended users) can be calculated using γkout σ2 thermal Q rηp q=1 β. (1) qh If a very small size of receiver aperture is necessary, a high gain PD, such as an avalanche photo diode (APD), can be used. The actual PD size can be calculated roughly as  r = A r G, (11) where G is the gain of the APD, and Âr is the effective aperture size. D. LED Modulation Efficiency Optimization In order to reduce the leakage of information and enhance the indoor communication performance, we can optimize the modulation efficiency of each LED. With the help of the lamp model shown in Fig. 1, the security and indoor data transmission quality can be considered at the same time. We assume that the smaller the eavesdropper receiver aperture becomes, the harder it is to expose it. On the other hand, a larger aperture can collect more optical power and achieve a higher SNR to capture the data. To minimize the possibility of interception and guarantee the indoor communications, we can optimize the modulation efficiency by max B min γ kin k in s.t. γ kout γ min, k out β q 1, q = 1, Q, (12)

4 TABLE I PARAMETERS USED IN NUMERICAL RESULTS LED lamp placement (2.5, 2.5, 2.9) m Radiation power of each LED 5 mw Number of LEDs per lamp 25 Semiangles of LEDs 2 o Intended indoor user aperture, A in 1 4 m 2 Wall reflection coefficient, ρ.8 Transmittance percentage through window, η 1 Sunlight illumination lx Thermal noise power, σthermal W Background light noise power, σshot W SNR (db) where B = (β 1, β 2,, β Q ). k in is any user in the indoor area, and k out represents any eavesdropper outside the window. γ min is the minimum SNR for data detection. γ kin and γ kout represent the SNR for the any indoor user and outdoor eavesdropper, respectively, which can be calculated by using (4) ) 2 (rp A in Qq=1 β qh in γ kin = γ kout = σ 2 n (rp η Qq=1 β qh out ) 2 σ 2 n, (13) where A in and represent the desired user aperture and eavesdropper aperture, respectively. To find the optimal modulation efficiency, an iterative method, the sequential quadratic programming (SQP) algorithm, can be used [11]. Since the maximin optimization is non-convex, only a locally optimal solution of the modulation efficiency can be obtained. III. SIMULATION RESULTS AND ANALYSIS To test the system vulnerability, we set up a scenario as an empty and unfurnished room with dimensions of 5 m 5 m 3 m. There is only one window of 2 m 2 m in size, and the low edge of the window is 1 m off the floor. The parameters used to obtain the simulation results are shown in Table I. All measurements are simulated at the floor level. A. No LED Modulation Efficiency Optimization In this section we consider the vulnerability of the system when all LEDs transmit data (β q = 1, q), unconcerned with security issues. For a typical office room, the illumination level should be around 4 lx [12]. To make this requirements, the SNR distributions in the indoor area and the outdoor area are shown in Figs. 5 and 6, respectively. In these two results, we assume the size of the PD at the intended receiver is 1 4 m 2. For the indoor area, the thermal noise is dominant, and for the outdoor area, the shot noise caused by the background sunlight is dominant. In general, the SNR in the indoor area is more than 38 db and is distributed symmetrically around the LED SNR (db) Window Fig. 5. Indoor Fig SNR distribution in the indoor area Outdoor Vulnerable Zone SNR distribution in the outdoor area, daytime. lamp. The high indoor SNR can support a reliable and high speed wireless data transmission by using a large modulation constellation size. For instance, an SNR of 38 db allows us to use an M = 16. The SNR distribution outside the room varies dramatically depending on where the receiver is placed and the background light levels. The area just outside the window has a higher SNR than other places. The high SNR area outside the window is referred to as the vulnerable zone in Fig. 6. In this plot, we choose a 2 db SNR as a threshold, corresponding to a constellation size of M = 8. The area with SNR greater than 2 db is defined as the vulnerable zone. In the vulnerable area, the LOS light dominates. Fig. 7 shows the relationship between the required gain of the receiver and the received power density. Two extreme

5 Gain (db) Sunlight dominant Required SNR=32dB Required SNR=2dB SNR (db) No background light Received Power Density (W/m 2 ) x =1 m 2, Daytime =1 2 m 2, Daytime =1 4 m 2, Daytime =1 m 2, Nighttime Fig. 7. Gain of the PD requirements for different received power densities. Fig. 8. SNR distribution for outdoor areas by optimizing the LED modulation efficiency using different sizes of aperture, γ min = 1 db. cases are compared in this result. The sunlight dominant case represents an outdoor scenario in daylight. The indoor area and the outdoor area at night can be assumed to experience no background light. From the results in Fig. 7, for the same received power density, the sunlight-dominant case needs around 3 db higher gain than the no-background light case to get the same SNR. Thus, the background sunlight indeed makes it more difficult for the eavesdropper to detect the information. B. LED Modulation Efficiency Optimization to Diminish Vulnerability In this section we consider the vulnerability of the VLC system to eavesdropping when the LED modulation efficiency optimization is adjusted. In this part, we test two environment: daytime and nighttime cases. We assume that the sunlight only affects the outside background light. For the modulation efficiency optimization, we assume the detector of the eavesdropper is on the floor. Fig. 8 shows the SNR distribution outside the window after applying the optimal modulation efficiency of each LED in the lamp. For the optimization results, since we design γ min = 1 db, if the eavesdropper detector uses a = 1 m 2 aperture, it can only obtain up to a 1 db SNR. However, a detector with a 1 m 2 aperture is very easy to be detected. In the meantime, from (7), a 1 db SNR is the minimum value to support a communication system with a 1 3 BER by using 2-PAM. The eavesdropper is unable to demodulate a 16 to 32-PAM signal that is easily demodulated indoors. If the eavesdropper uses a detector with a smaller aperture, such as 1 2 m 2 or 1 4 m 2 as shown in Fig. 8, up to -1 db and -3 db SNR can be obtained, which are too small to recover the data. No matter whether there there is sunlight or not, our algorithm can limit the outdoor SNR to a very low level. The SNR distributions of the sunlight and no sunlight cases are similar. SNR (db) Sunlight, γ min =1 db No sunlight, γ min =1 db Fig. 9. SNR distribution for indoor areas by optimizing the LED modulation efficiency, A D = 1 m 2 and A r = 1 4 m 2. After optimizing the modulation efficiency, the SNR distribution in the indoor area is shown in Fig. 9. Although we assume the sunlight cannot affect the illumination in the indoor area, the optimization of the modulation efficiency depends on the outside sunlight. The strong sunlight can introduce more background shot noise than the case without sunlight. Thus, it is more difficult for the eavesdropper to capture the data under a strong sunlight circumstance. Compared with the nighttime case, the sunlight can allow the system to use a higher modulation efficiency for a better indoor wireless connection. Compared with the results in Fig. 7 and 8, with the help of sunlight, we can guarantee a similar outdoor SNR distribution, which is secure, and provide up to a 4 db enhancement of the indoor SNR.

6 IV. CONCLUSION Visible light communication systems provide a new and innovative solution for secure indoor wireless communications. Given the characteristics of light of not being able to penetrate walls, the main security concern is caused by light leakage outside the room from windows. In this article, we first quantitatively analyze the potential vulnerability of the system from eavesdropping by calculating the SNR in different areas outside a window. We also calculate the required gain and aperture size for the receiver in different areas in order to illustrate how big the eavesdropper equipment must be to successfully recover the signal. From the simulation results, the minimum diameter of the lens needs to be a round 2 cm in the vulnerable zone. In the remaining area, an eavesdropper receiver with a gain of 6 db, or equivalently a lens of 2 m, which is impractical. We show that the area where the LOS signal can be received is most vulnerable. We also show that the daytime sunlight greatly reduces the possbility of eavesdropping. Finally, based on our analysis, we propose a solution to improve the VLC system security by implementing a modulation efficiency optimization algorithm that can minimize the possibility of outdoor eavesdropping and maximize the minimum SNR in the indoor area to guarantee a reliable indoor data transmission. The results show that by doing this we can maintain indoor communication system performance while greatly reducing the SNR outside the room. If the eavesdropper uses small detection equipment, the SNR is not hight enough to recover the data. Otherwise, to obtain a acceptable SNR, a large size equipment should be used, which makes the eavesdropper easy to detect. [11], Multiuser MIMO indoor visible light communication system using spatial multiplexing, J. Lightw. Technol., vol. PP, no. 99, pp. 1 1, 217. [12] IESNA Lighting Handbook, 9th ed. IES of North America, New York, NY, USA, 2. REFERENCES [1] J. Classen, J. Chen, D. Steinmetzer, M. Hollick, and E. Knightly, The spy next door: Eavesdropping on high throughput visible light communications, in Proceedings of the 2nd International Workshop on Visible Light Communications Systems. ACM, Sep 215, pp [2] A. Mostafa and L. Lampe, Physical-layer security for indoor visible light communications, in 214 IEEE Intern. Conf. Commun. (ICC), June 214, pp [3], Pattern synthesis of massive LED arrays for secure visible light communication links, in 215 IEEE Intern. Conf. Commun. Workshop (ICCW), June 215, pp [4] D. Li, L. Zhang, and J. Qiu, High security chaotic multiple access scheme for VLC systems, in th Intern. Telecommun. Netw. and Applic. Conf. (ITNAC), Dec 216, pp [5] G. Pan, J. Ye, and Z. Ding, On secure VLC systems with spatially random terminals, IEEE Commun. Lett., vol. 21, no. 3, pp , March 217. [6] F. J. Lopez-Martinez, G. Gomez, and J. M. Garrido-Balsells, Physicallayer security in free-space optical communications, IEEE Photon. J., vol. 7, no. 2, pp. 1 14, April 215. [7] J. Lian, M. Noshad, and M. Brandt-Pearce, Multiuser MISO indoor visible light communications, in th Asilomar Conf. Sign., Syst. and Comput., Nov 214, pp [8] K. Lee, H. Park, and J. R. Barry, Indoor channel characteristics for visible light communications, IEEE Commun. Lett., vol. 15, no. 2, pp , 211. [9] J. Kahn and J. Barry, Wireless infrared communications, Proc. of the IEEE, vol. 85, no. 2, pp , [1] J. Lian and M. Brandt-Pearce, Adaptive M-PAM for multiuser MISO indoor VLC systems, in 216 IEEE Global Communications Conference (GLOBECOM), Dec 216, pp. 1 6.