Abstract

     Physical layer security (PLS) in Internet-of-Things (IoT) has attracted great attention in recent years. As an important and intrinsic property in an IoT system, node mobility is not fully investigated when designing a PLS scheme. Existing PLS works with mobility are designed with typical random mobile models, which cannot represent a real scenario. Considering this challenge, we propose a friendly jamming handover scheme to protect the downlink transmission from a controller to an actuator, with the help of multiple cooperative jammers to fight against a mobile conscious eavesdropper. In particular, we first introduce a conscious eavesdropping model (CEM) to characterize a real mobile wiretapping scenario. Second, we present a handover scheme to enhance security in a mobile scenario and then define handover efficiency to discuss the handover performance. Finally, numerical results are provided to verify the effectiveness of the proposed handover scheme, which demonstrates that our scheme can efficiently fight against a conscious mobile eavesdropper.

Introduction

     Internet of Things (IoT) is expected as a promising technique to achieve ubiquitous connectivity and intelligent information processing for the intelligent future life [1, 2]. Since the IoT is penetrating our daily life, the security and privacy are of the utmost importance [3–5]. Physical layer security (PLS) techniques have been attracted growing interests for the scenarios with resource-constrained IoT sensors and actuators [6–8]. A PLS scheme taking advantage of the unique properties of wireless channels can guarantee the information-theoretic communication security, regardless of the computing capability of eavesdroppers [9]. Various PLS schemes have been investigated to enhance secrecy in IoT networks, including multi-antenna beamforming and precoding [10, 11], artificial noise (AN) [12], intermittent cooperative jamming [13], and sociability-enabled PLS [8, 14, 15].

Conclusion

     This work investigated secure downlink transmmission in an IoT system with a mobile eavesdropper, and proposed a handover scheme to enhance PLS with the help of multiple cooperative jammers. In order to reflect the real situation, the conscious eavesdropping model was proposed to compare with the typical RWP model. Moreover, we introduced a metric called handover efficiency to reflect the handover performance. The numerical results verified that the handover scheme could efficiently improve the secrecy performance and effectively confront the conscious eavesdropper. The proposed scheme is feasible to provide security enhancement in many real mobile eavesdropping scenarios.

Conventional mobile communication systems often use one single channel for data transmission, i.e., mobile devices use cellular network to transfer multimedia information. However, if attackers successfully hijack the single transmission channel, they can recover the communicated data. Focused on this issue, we introduce a Multichannel Communication System (MSYM), which aims to improve the data communication security for Android devices. The key idea of our approach is to leverage the diversity of communication mechanisms (e.g., Wi-Fi/cellular network, Bluetooth, and SMS) for transferring sensitive data in a secure way. More specifically, we use the VpnService interface provided by the Android platform to intercept the network data delivered by a sender program. Then, we split the network data into different fragments and improve the security by disordering and encrypting them via multiple transmission channels. When the target Android device receives the data fragments from different channels, it can decrypt and reorder them to reassemble the original data. In the end, we reuse the VpnService interface to inject the network data into the receiver program. Our approach can be deployed in Android devices to secure communication without the need of modifying the communication programs. In the evaluation, as a proof of concept, we implemented our approach on Android system. The experimental results show that our prototype system can secure data transmission with moderate performance cost.

Introduction

Mobile communication plays an increasingly important role in recent years, as more and more people exchange information via mobile devices. For example, over 2 billion people are using the instant messaging apps (e.g., WeChat and WhatsApp) on their mobile phones for exchanging messages, pictures and videos [6]. In addition, 90% of enterprises utilize mobile communication to boost productivity and streamline various business processes. Traditionally, most mobile devices only use one single wireless transmission channel (e.g., cellular network) for mobile communication. However, due to the openness of the wireless channel, it is possible for advanced attackers to eavesdrop the transmission and recover the sensitive data. For instance, adversaries can make use of bogus base stations to conduct man-in-the-middle (MITM) attack on modern Samsung mobile devices and obtain the sensitive information [23]. To prevent the communication data from being eavesdropped and recovered, a conventional solution is to leverage cryptographic protocols to perform data encryption and endpoint authentication. For example, the Wi-Fi Protected Access (WPA) and its subsequent standards (WPA2, WPA3) attempt to secure the wireless networks by applying multiple security protocols [13]. However, they may still suffer from eavesdropping attacks like the KRACK [35] attack. This attack shows that an attacker can exploit the vulnerability of WPA2 to read previously encrypted information. On the other hand, most mobile applications adopt the client-server model, which requires that all the communication data between two or more clients should be firstly forwarded to a central server. Nevertheless, some service providers may not be fully trusted. Taking the messaging server as an example, once it is hacked by adversaries, the recorded information would be leaked.

Abstract

In this paper, we present an eavesdropping-based gossip algorithm (EBGA). In the novel algorithm, when a node unicasts its values to a randomly selected neighboring node, all other nodes, which eavesdrop these values, simultaneously update their state values. By exploiting the broadcast nature of wireless communications, this novel algorithm has similar performance to broadcast gossip algorithms. Although broadcast gossip algorithms have the fastest rate of convergence among all gossip algorithms, they either converge to a random value rather than the average consensus, or need out-degree information available for each node to guarantee convergence to the average consensus. Utilizing non-negative matrix theory and ergodicity coefficient, we have proved that this novel algorithm can converge to the average consensus without any assumption which is difficult to be realized in real networks.

I. INTRODUCTION

For gossip algorithm, each node holds an estimating state value of the network. At the beginning, the initial state value is captured by each node. At one iteration, one node is randomly activated and exchanges state values with one of its randomly selected neighbors. By convex combination, these two nodes can update their state values to the average of their previous state values. By iterating this procedure, all nodes can eventually arrive at the average consensus that is the average of the initial state values at each node Copyright (c) 2012 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org. The work was supported by the National Science Foundation of China under grant No. 61201147.

The authors are with the Department of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China (e-mail: scwu@hit.edu.cn; liubo90113@126.com; x bai@hit.edu.cn; yuguanhou@hit.edu.cn). [1]. The drawback of this gossip algorithm is slow rate of convergence [2]. To accelerate convergence, eavesdropping method was first introduced by Deniz et al. in their greed gossip with eavesdropping (GGE) algorithms [3]. During the operation of GGE, when a node decides to gossip, instead of randomly choosing one of its neighbors, it chooses the node which has the state value most different from its own. Although GGE can accelerate convergence, it is still too slow to converge because only two nodes are allowed to exchange state values at each iteration.

To further accelerate convergence, a more competitive algorithm called broadcast gossip algorithm [4] was proposed. For broadcast gossip algorithms, when a node transmits its state value, all of its neighbors can hear about this state information and simultaneously update their state values. Although broadcast gossip algorithms have been studied for several years, the best trade-off between the rate of convergence and the error of convergence is still an open problem. As our knowledge, only three types of broadcast gossip algorithms have been proposed. One of them (called BGA-1 in the sequel) cannot converge to the average consensus [4]. Although recent research results indicate that the error upon the average in BGA-1 is small on large networks [5], we are more interested to propose a novel algorithm that can converge to the average consensus for any network in this paper. Another broadcast gossip algorithm (called BGA-2 in the sequel) converges more slowly than BGA-1, and no proof of convergence is available [6]. The third one (UBGA) proposed by us in a previous research [7] can converge to the average consensus with companion values and a strong assumption that all nodes should know its out-degree information (the same assumption is also needed for BGA-2), which is somewhat difficult to be satisfied in real networks. In this paper, we also utilize companion values as a compensation rule to preserve average consensus. This kind of compensation rules was firstly proposed for linear gossip algorithms in BGA-2. Then this method was further expanded for digraphs in [7] and [8]. All these algorithms can preserve average at the cost of out-degree information available for each node. All above drawbacks motivate us to propose a novel gossip algorithm that has the same rate of convergence as broadcast gossip algorithms and can be proven convergence to the average consensus without any assumption which is difficult to be realized.