A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack

Crowdsensing is a technique leveraging the crowd power to accomplish sensing tasks collaboratively at a low cost. The participants in crowdsensing networks sense the information and upload the sensed data to crowdsensing platforms voluntarily. As a result, the quality of sensing tasks heavily relies on whether the number of participants is sufficient. However, due to the consumption on time, battery and data, recruiting the participants in crowdsensing networks is difficult, although some incentive mechanisms were proposed [1]. Therefore, to guarantee the sensing quality of accomplished tasks, mobile crowdsensing as the complement of traditional statically deployments has been extensively investigated [2,3].

In recent years, the combination of crowdsensing and Industrial Internet of Things (IIoT) has drawn extensive attention [4,5]. There are a lot of benefits in introducing crowdsensing to IIoT, including: (1) providing mobile and scalable measures; (2) monitoring new areas without installing additional dedicated devices; (3) integrating human wisdom into machine intelligence straight forwardly; (4) sharing information and making decision among the whole industrial community [4]. The performance of personal monitoring, process monitoring and product quality checking in IIoT will be improved with the help of crowdsensing [5].

With the proliferation of wireless sensor devices, the security of transmitting data in such IIoT based crowdsensing networks deserves much attention, especially for the confidential data related with commercial interest and privacy concern. To protect the security of crowdsensing networks, some security encryption schemes were proposed, such as privacy-preserving participant selection scheme [6] and reputation management schemes [7]. Moreover, some encryption schemes for IIoT were presented in [8]. The encryption schemes are feasible for devices with sufficient computing capability and power, such as smart phones or tablet computers. However, the encryption schemes may not be suitable for power-constraint sensor devices in crowdsensing networks (e.g., pulse-sensor-embedded wrists) and machinery in factories, since these schemes often require conducting compute-intensive tasks, consequently consuming a lot of power.

Different from the security encryption schemes, friendly-jamming schemes have been recognized as a promising approach to enhance the network security without bringing extra computing tasks [9,10,11,12,13]. The main idea of friendly-jamming schemes is introducing some friendly jammers to wireless networks, where these friendly jammers can generate a jamming signal to increase the noise level at the eavesdroppers, so that they cannot successfully wiretap the legitimate communications [14,15,16]. Using friendly-jamming schemes to decrease the possibility of eavesdropping attacks has received extensive attention [17,18]. The benefits of friendly jamming schemes is that there is no requirement for strong-computing capability of nodes, and no necessity for centralizing security schemes [19]. Therefore, friendly-jamming schemes can be applied in crowdsensing networks with power-constraint devices.

To mitigate the eavesdropping attack of crowdsensing networks, we propose a novel friendly jamming scheme in this paper. In this scheme, we place multiple jammers at a circular boundary around the protected communication area. Being implied by previous studies [20,21], we also consider equipping directional antennas at jammers. We name such jamming scheme with directional antennas as DFJ. Moreover, we also consider equipping omnidirectional antennas at jammers. We name such a jamming scheme with omnidirectional antennas as OFJ. For comparison purposes, we also consider the case without jammers (named as NFJ).

The main contributions of this paper are summarized as follows.

Our proposed schemes have many more merits than other existing anti-eavesdropping schemes. Firstly, our schemes are less resource-intensive (i.e., no extensive computing resource needed) and it does not require any modifications on existing network infrastructure. Secondly, our schemes are quite general since the circular area with jammers can essentially circumscribe any buildings due to the feature that every simple polygon (i.e., the shape of a building) always has a circumscribed circle [22]. As a result, the effective jamming to eavesdroppers can be achieved. Moreover, our schemes can offer a larger effective protection area compared with other friendly jamming schemes like placing jammers at polygons [14] or other shapes [23] due to the largest coverage area of a circle.

In this section, we introduce the models used in this paper. We mainly focus on the uplink transmission from sensor devices (legitimate transmitter) to the receiver. The descriptions of notations are given in Table 1.

In this section, we investigate the impacts of different schemes on the legitimate communications. In particular, we consider the probability of successful transmission as a metric to evaluate the transmission quality of legitimate communications. The probability of successful transmission is defined as follows,

To guarantee the successful transmission of legitimate communication, the signal-to-interference- noise-ratio (SINR) at the legitimate receiver, denoted by ${SINR}_T$, must be no less than a threshold T. In particular, when we consider the communication between a reference transmitter $t_0$ and the receiver with distance $r_0$, ${SINR}_T$ can be expressed as where $P_t$ is the transmission power of transmitters, $G_t$ and $G_r$ are the antenna gains of the reference transmitter and the receiver, respectively (where we have $G_t=G_r=1$ since that the transmitters and receivers are equipped with omni-directional antennas), $I_t={\displaystyle \sum _{i\in \Phi /t_0}}{G}_t{G}_r{P}_t{h}_i{r}_i^{-\alpha }={\displaystyle \sum _{i\in \Phi /t_0}}{P}_t{h}_i{r}_i^{-\alpha }$ is the cumulative interference from legitimate users (where $r_i$ is the distance between the ith transmitter and the receiver), $I_j={\displaystyle \sum _{k=1}^N}{G}_j{G}_r{P}_j{h}_k{R}^{-\alpha }={\displaystyle \sum _{k=1}^N}{G}_j{P}_j{h}_k{R}^{-\alpha }$ is the cumulative interference from N jammers to the receiver (where $P_j$ is the transmission power of the jammers and $G_j$ is the antenna gain of the jammers), and ${\sigma }^2$ is the noise power.

Thus, we have the probability of successful transmission, denoted by ${\mathbb{P}}_T$, as follows, where $f_r\left(r_0\right)$ is the probability density function of the distance between the reference transmitter and the receiver $r_0$.

Then, we investigate the probability of successful transmission ${\mathbb{P}}_T$ according to the three jammer strategies: NFJ, OFJ, and DFJ schemes.

In this section, we analyze the influence of friendly jammers on the probability of an eavesdropping attack of this network. In particular, we use the probability of an eavesdropping attack as the metric to evaluate the possibility of being eavesdropped on in this network. We assume that if the eavesdropper can wiretap any of the transmitters, this network can be seen as being attacked. Based on this assumption, we give the definition of the probability of eavesdropping attack as follows.

Before we analyze the probability of an eavesdropping attack, we first analyze the probability that a certain transmitter can be wiretapped by the eavesdropper, denoted by ${\mathbb{P}}_e$. If the eavesdropper can wiretap a transmitter $t_0$ with distance $l_0$, the SINR at the eavesdropper, denoted by $SIN{R}_E$, has to be no less than a threshold $\beta$. Thus, ${\mathbb{P}}_e$ can be expressed as follows, where $G_e$ is the antenna gain of the eavesdropper (we have $G_e=1$ since the eavesdropper is equipped by an omni-directional antenna), $I_{te}={\displaystyle \sum _{i\in \Phi /t_0}}{G}_t{G}_e{P}_t{h}_i{l}_i^{-\alpha }={\displaystyle \sum _{i\in \Phi /t_0}}{P}_t{h}_i{l}_i^{-\alpha }$ is the cumulative interference from transmitters to the eavesdropper (where $l_i$ is the distance between the ith transmitter and the eavesdropper), $I_{je}$ is the cumulative interference from the jammers to the eavesdropper, which will be elaborated later according to different jammer schemes, and $f_l\left(l_0\right)$ is the probability density function of $l_0$.

Next, based on the analysis of ${\mathbb{P}}_e$, we give the probability of eavesdropping attack, denoted by $P_E$, as follows,

The impact of friendly jammers on the eavesdropping attacks will then be investigated. In particular, we will derive the probability of an eavesdropping attack ${\mathbb{P}}_E$ of an eavesdropper in the NFJ scheme, OFJ scheme and DFJ scheme as follows, respectively.

In this section, we present the simulation results of probability of successful transmission ${\mathbb{P}}_T$ and probability of eavesdropping attack ${\mathbb{P}}_E$ considering the NFJ, OFJ and DFJ schemes. The simulation results are generated via Monte Carlo simulations with 50,000 runs and the parameters are given in Table 2.

In Figure 5, we present the numerical and simulation results of probability of successful transmission ${\mathbb{P}}_T$ and probability of eavesdropping attack ${\mathbb{P}}_E$ with different schemes. From Figure 5a, we find ${\mathbb{P}}_T$ decreases when the number of legitimate transmitters denoted by M increases. Since the receiver only receives the information from the protected transmitter, the cumulative interference from legitimate transmitters to the receiver increases with M. When we introduce friendly jammers into the network, compared with the NFJ scheme, ${\mathbb{P}}_T$ decreases. The performance of ${\mathbb{P}}_T$ with DFJ scheme is better than ${\mathbb{P}}_T$ with OFJ scheme. This is because the lower antenna gain of side lobe in the DFJ scheme leads to less interference to the legitimate transmission.

In Figure 5b, the red curve represents the probability of eavesdropping attack ${\mathbb{P}}_E$ of the NFJ scheme. From numerical results, we find that the red line decreases very slowly, especially when M is larger than 2. For example, when $M=4$, ${\mathbb{P}}_E$ of NFJ scheme is 0.9626, while ${\mathbb{P}}_E$ becomes 0.9619 and 0.9602 when M becomes 6 and 8, respectively. This result lies in the fact that the eavesdropper may eavesdrop any one of the M legitimate transmitters, rather than a specially appointed transmitter. When M increases, the interference on the eavesdropper increases. However, the eavesdropper may tap more transmitters as the total number of transmitters is increased. In addition, the performance of ${\mathbb{P}}_E$ of DFJ scheme is still better than that of the OFJ scheme, because of the higher antenna gain of main lobe.

From Figure 5a,b we find that introducing friendly jammers into the network will lead to the decrement on both ${\mathbb{P}}_T$ and ${\mathbb{P}}_E$. However, the influence of friendly jammers on ${\mathbb{P}}_E$ is more obvious than the influence on ${\mathbb{P}}_E$. For example, when $M=5$, compared with the NFJ scheme, the reduction of ${\mathbb{P}}_T$ with OFJ scheme is $0.0574$ (i.e., $13.4\%$ reduced), while the reduction of ${\mathbb{P}}_E$ is 0.5485 (i.e., $56.99\%$ reduced). When $M=5$, compared with the NFJ scheme, the reduction of ${\mathbb{P}}_T$ with DFJ scheme is $0.023$ (i.e., $5.4\%$ reduced), the reduction of ${\mathbb{P}}_E$ is 0.5935 (i.e., $61.66\%$ reduced). Therefore, the DFJ scheme can reduce the probability of eavesdropping attacks more significantly while maintaining the lower impairment to the legitimate communications than the OFJ scheme. This result implies that using friendly jammers can reduce the eavesdropping attack without causing obvious damage on legitimate transmission.

Figure 6 shows the comparison of ${\mathbb{P}}_T$ and ${\mathbb{P}}_E$ in different schemes with the varied number of friendly jammers denoted by N. In Figure 6a, we find that both ${\mathbb{P}}_T$ of the DFJ scheme and that of the OFJ scheme decrease when N increases. The decrement of ${\mathbb{P}}_T$ lies in the increased cumulative interference from friendly jammers. Moreover, Figure 6b shows that ${\mathbb{P}}_E$ decreases rapidly when the number of friendly jammers N increases, especially when friendly jammers are equipped with directional antennas (i.e., in DFJ scheme). This result can help to verify the effectiveness of OFJ and DFJ schemes in reducing the probability of eavesdropping attacks ${\mathbb{P}}_E$.

The results as shown in Figure 6 imply that it may not be necessary to deploy too many friendly jammers in the network. In particular, in the DFJ scheme, we can significantly reduce the probability of eavesdropping attacks while only slightly impairing legitimate communications by introducing a few friendly jammers. For example, when $N=8$, compared with NFJ scheme, the reduction of ${\mathbb{P}}_T$ in DFJ scheme is $0.0291$ (i.e., $5.66\%$ reduction), while the reduction of ${\mathbb{P}}_E$ in the DFJ scheme is $0.4399$ (i.e., $81.24\%$ reduction).

Figure 7 shows the comparison of ${\mathbb{P}}_T$ and ${\mathbb{P}}_E$ with DFJ, OFJ schemes versus the NFJ scheme with different SINR threshold. It is shown in Figure 7 that ${\mathbb{P}}_T$ decreases with the threshold T and ${\mathbb{P}}_E$ decreases with the threshold $\beta$. From Figure 7a, similarly to Figure 5b, we find that using friendly jammers can always reduce the probability of eavesdropping attacks ${\mathbb{P}}_E$ compared with the NFJ scheme, and the DFJ scheme performs better than the OFJ scheme obviously.

In another set of simulations as presented in Figure 8, we compare the probability of eavesdropping attack ${\mathbb{P}}_E$ of different schemes with varied distance between the eavesdropper and the network boundary D. From Figure 8a, we can find that ${\mathbb{P}}_E$ of NFJ, OFJ and DFJ schemes vary slightly when path loss factor $\alpha =3$. It means when $\alpha =3$, path loss effect has no obvious impact on ${\mathbb{P}}_E$. This result lies in the fact that path loss has the influence on both useful signal and interference. However, when the path loss factor $\alpha$ increases from 3 to 4, as shown in Figure 8b, ${\mathbb{P}}_E$ of three schemes decreases rapidly, especially in the NFJ scheme. This result implies that the path loss has a more obvious influence on useful signal than that on interference. From Figure 8, we also find that using friendly jammers can reduce the probability of eavesdropping attacks ${\mathbb{P}}_E$ compared with the NFJ scheme.