Mobile Information Systems

Volume 2018 (2018), Article ID 5032934, 9 pages

https://doi.org/10.1155/2018/5032934

## Asynchronous Channel-Hopping Scheme under Jamming Attacks

^{1}Korea Military Academy, Seoul, Republic of Korea^{2}Department of Computer Science, North Carolina State University, Raleigh, NC, USA

Correspondence should be addressed to Yongchul Kim

Received 6 September 2017; Accepted 29 November 2017; Published 19 February 2018

Academic Editor: Francesco Gringoli

Copyright © 2018 Yongchul Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

Cognitive radio networks (CRNs) are considered an attractive technology to mitigate inefficiency in the usage of licensed spectrum. CRNs allow the secondary users (SUs) to access the unused licensed spectrum and use a blind rendezvous process to establish communication links between SUs. In particular, quorum-based channel-hopping (CH) schemes have been studied recently to provide guaranteed blind rendezvous in decentralized CRNs without using global time synchronization. However, these schemes remain vulnerable to jamming attacks. In this paper, we first analyze the limitations of quorum-based rendezvous schemes called asynchronous channel hopping (ACH). Then, we introduce a novel sequence sensing jamming attack (SSJA) model in which a sophisticated jammer can dramatically reduce the rendezvous success rates of ACH schemes. In addition, we propose a fast and robust asynchronous rendezvous scheme (FRARS) that can significantly enhance robustness under jamming attacks. Our numerical results demonstrate that the performance of the proposed scheme vastly outperforms the ACH scheme when there are security concerns about a sequence sensing jammer.

#### 1. Introduction

The unlicensed spectrum band has become overcrowded as the demand for smart phones and portable devices has increased, while the licensed spectrum band is always underutilized (e.g., the occupancy of the licensed spectrum is less than 6% [1]). To solve the spectrum scarcity issue in wireless communications, the Federal Communications Commission (FCC) allows the unlicensed users (i.e., secondary users) to make use of the licensed spectrum as long as they do not interfere with the licensed users (i.e., primary users) [2, 3]. This promising paradigm introduces the use of cognitive radio networks (CRNs) as a key technology for opportunistically exploiting the spectrum. In CRNs, secondary users (SUs) must establish a link before communicating with each other. In other words, two SUs should meet on a common channel, which is not occupied by primary users (PUs), to exchange handshake information. This is often referred to as a rendezvous process. The best known approach to solving the rendezvous problem is using a common control channel (CCC) [4, 5]. The advantages in using this approach are the simple implementation and management of a rendezvous. However, maintaining a CCC in CRNs is not feasible since the availability of the spectrum will change dynamically over time. Moreover, this approach may result in a bottleneck, and it potentially creates a single point of failure. Therefore, the rendezvous process in a distributed manner without having any centralized controller or dedicated CCCs is preferable in a more practical scenario. This process is often referred to as a blind rendezvous. To achieve blind rendezvous, a channel-hopping (CH) technique is used as a fundamental strategy to visit the available channels. Most research regarding CH algorithms consider that the time is divided into slots; thus, a successful rendezvous can be achieved when two SUs hop on the same channel in the same timeslot. The number of timeslots that are required until the successful rendezvous after all SUs have begun their CH sequences is defined as time to rendezvous (TTR). According to the geographical locations of the SUs, the number of available channels sensed by each SU might not be the same. If all SUs have the same number of available channels, we call this the symmetric system. All others are asymmetric systems. For reliable performance in CRNs, most CH schemes must guarantee rendezvous in more than one channel within a sequence period, and the TTR value must be bounded and small. To evaluate the performance of proposed CH schemes, two critical metrics are commonly used: the maximum TTR (MTTR) and the expected TTR (ETTR).

There has been a great deal of research directed toward providing guaranteed rendezvous as well as minimizing MTTR. In particular, quorum-based rendezvous algorithms are well-known schemes for providing some level of security under hostile jamming attack scenarios with low time latency. However, these schemes remain vulnerable to sophisticated jamming attacks. In this paper, we present a noble sequence sensing jamming attack (SSJA) in which the jammer can estimate the SU’s channel-hopping sequences quickly and begin jamming the rest of the timeslots. We then examine the limitations of those quorum-based rendezvous schemes including frequency quorum rendezvous (FQR) [6] and asynchronous channel-hopping (ACH) [7] schemes under a sophisticated jamming attack. Since FQR requires time synchronization between SUs, we focus more on ACH rendezvous scheme for evaluating the effectiveness of SSJA. Moreover, we introduce our proposed fast and robust asynchronous rendezvous scheme (FRARS) that can reduce TTR as well as increase robustness significantly against jamming attacks.

The contributions of this paper are twofold: first, we analyze the limitations of the well-known quorum-based rendezvous scheme under a sophisticated jamming attack by introducing a novel SSJA model. In the SSJA, a jammer can detect the sender’s entire CH sequence of ACH schemes on time frames, where *N* is the number of available channels. Thus, the rendezvous success rates of ACH schemes will be dramatically decreased under SSJAs. Second, we present our proposed FRARS in order to evaluate the performance under an SSJA. We include a theoretical analysis in addition to extensive numerical analysis under SSJAs. Our numerical results demonstrate that our proposed scheme outperforms others that are recently proposed. The balance of this paper is organized as follows. In Section 2, we review related work in CRNs. In Section 3, we introduce SSJA model and present several CH schemes including FQR and ACH as well as our proposed FRARS. The numerical analysis of our jamming attack for both ACH and FRARS and the results are discussed in Section 4. Section 5 concludes this paper.

#### 2. Related Work

Due to the drawbacks of using a centralized controller or dedicated CCC, many studies have focused on blind rendezvous systems. To solve the blind rendezvous problem in CRNs, a purely random [8] or an improved random algorithm [9] provides a trivial CH algorithm where each SU hops from one channel to another among available channels in a purely random way. That is, when two SUs hop on the same channel at the same time by chance, rendezvous occurs. These schemes can be applied to almost any system but cannot guarantee a bounded TTR between any two SUs.

##### 2.1. Synchronous Rendezvous Algorithms

To achieve guaranteed rendezvous in finite time, several algorithms have been proposed with the assumption of global time synchronization [10–12]. Bahl et al. [10] proposed a link-layer protocol called Slotted Seeded Channel Hopping (SSCH) that increases the capacity of an IEEE 802.11 network by utilizing frequency diversity. Krishnamurthy et al. [11] proposed a two-phase autoconfiguration algorithm that enables SUs to dynamically compute the globally common channel set in a distributed manner. Bian et al. [12] introduced quorum-based two CH schemes, namely, M-QCH and L-QCH: the first design ensures ETTR by minimizing the MTTR and the second design guarantees the even distribution of the rendezvous points in terms of both time and frequency. However, these synchronous systems may not be feasible in certain types of networks, for example, ad hoc networks. Moreover, under the assumption of synchronization, the impact of a jamming attack can be significant.

##### 2.2. Asynchronous Rendezvous Algorithms

To overcome these challenges, many asynchronous CH algorithms (i.e., one that does not require clock synchronization) have been proposed recently in the literature [13–21]. DaSilva and Guerreiro [13] proposed a sequence-based rendezvous and was later referred to as the generated orthogonal sequence (GOS) algorithm in which all SUs use the identical predefined CH sequences. This algorithm is used with interspersed permutation channels to guarantee rendezvous even when SUs are not synchronized. Theis et al. [14] showed better performance than that of GOS in terms of ETTR by presenting modular clock (MC) and modified modular clock (MMC) algorithms. In the MC system, the SUs can rendezvous any time although they independently generate their CH sequences by using prime number and rate (forward-hop). Lin et al. [15] proposed a jump-stay (JS) algorithm in which each SU has a jump and stay pattern to find a common channel. Intuitively, SUs jump on available channels during the jump pattern and stay on a specific channel during the stay pattern. The enhanced jump-stay (EJS) algorithm [16] was also proposed by the same authors to improve the MTTR and ETTR performances for asymmetric systems. Liu et al. [17] introduced the ring walk (RW) algorithm to guarantee asynchronous rendezvous by using the concept of velocity. The SUs in this scheme walk on the ring by visiting vertices of channels with different velocities. The higher velocity SU will eventually catch the lower velocity SU. Chuang et al. [18] presents a new alternate HOP-and-WAIT channel-hopping method (E-AHW) to minimize the time to rendezvous (TTR) than existing methods. In this method, each SU has a unique alternating sequence of HOP and WAIT. Most recently, Salehkaleybar et al. [22] proposed periodic jump rendezvous (PJR) and modified version of PJR (mPJR) algorithms for role-based and nonrole-based cases, respectively, in order to reduce TTR. Pu et al. [23] studied the dynamic rendezvous problem in CRNs where the status of the licensed channels varies over time by introducing the available channel probabilities. This work aims to propose more realistic models under adversaries as a future work. Thus, the vulnerability against a sophisticated jamming attack is not addressed. The deterministic rendezvous sequence (DRSEQ) and channel rendezvous sequence (CRSEQ) algorithms proposed in [19, 20] provide fast asynchronous rendezvous under symmetric and asymmetric models, respectively. The upper bounds of MTTR of those algorithms are significantly small as shown in [24]. Yadav and Misra [21] develop an algorithm that generates a deterministic CH sequence, which guarantees rendezvous even faster than the DRSEQ algorithm. However, they are not applicable to jamming attack scenarios due to deterministic CH sequences.

##### 2.3. Jamming Attack Scenarios

Most of the aforementioned algorithms focus on minimizing MTTR without using time synchronization in either symmetric or asymmetric scenarios. None of them are considered to be robust in jamming attack environments. In wireless communications, an adversary (enemy and jammer) is a malicious entity that can easily disrupt legitimate communications by intentionally injecting noise-like signals (or dummy packets) into the wireless medium. To alleviate this vulnerability problem in CRNs, quorum-based rendezvous schemes are proposed in [6, 7]. The FQR algorithm [6] exploits a quorum system where each SU independently constructs a random sequence by scrambling the sender’s frequency quorum sequences for every frame as will be addressed in the next section. This makes jamming difficult and inefficient. An enhanced version of FQR, advanced FQR (AFQR) algorithm [6], adds more timeslots mapping random frequency channels at arbitrary positions within each frame to improve the rendezvous probability while it might degrade time overhead with the increased number of timeslots in a period. However, FQR only supports synchronous systems where any two SUs must start their sequences at the same time in order to rendezvous. Abdel-Rahman and Krunz [25] studied the rendezvous problem in the presence of an insider attack using a game-theoretic framework. This work showed that the rendezvous performance improves if the receiver and jammer are time synchronized and both have a common guess about the transmitter’s strategy. However, the jammer model in this work is not a smart jammer but an insider jammer. Thus, the vulnerability against a sophisticated jamming attack is not addressed. Bian and Park [7] proposed a quorum-based ACH algorithm to ensure that the TTR is upper bounded even if the SU’s clocks are asynchronous, and it maximizes the rendezvous probability between any pair of SUs by enabling rendezvous on every available channel. The sender and the receiver in an ACH algorithm independently generate their own sequences and rendezvous within a favorable amount of time compared to other schemes. Nevertheless, the ACH algorithm is significantly vulnerable to a sophisticated jamming attack. A survey paper [26] on jamming and antijamming techniques shows the classification of jammers. As a reactive channel-hopping jammer, we introduce an SSJA model in this paper to show how effectively it attacks the ACH system by adding more sophisticated capabilities such as estimating the SU’s CH sequence within a short time. To overcome this vulnerability against SSJA, we proposed a FRARS algorithm that employs randomized permutation in every period. Due to the random features of FRARS, it is unfeasible for the SSJA to estimate the CH sequences. Thus, the effectiveness of the SSJA is negligible for the FRARS. Our proposed scheme is comparable to the ACH algorithm since both the sender and the receiver in FRARS independently generate their own sequences like those in ACH. The performance results of FRARS as compared with ACH will be addressed in Section 4.

#### 3. Channel-Hopping Schemes

In this section, we present two well-known quorum-based rendezvous schemes, FQR and ACH algorithms, with a brief definition of a quorum system. Then, we introduce the SSJA model to show how effectively it attacks quorum-based rendezvous schemes. We also present our FRARS algorithm to enhance robustness against jamming attack and compare the effectiveness of the SSJA on ACH and FRARS.

##### 3.1. The Quorum System

A quorum system has two fundamental properties, that is, the intersection property and the rotation closure property [27]. All quorum systems hold the intersection property, but the rotation closure property may not be present in some cases. The FQR exploits a cyclic quorum system [28] to design a set of hopping sequences. We provide those definitions in this subsection, and we borrow all the terminologies defined in [6, 7, 27, 28].

*Definition 1*. Given a finite universal set of *N* elements, a quorum system *Q* under *U* is a collection of nonempty subsets of *U*, which satisfies the intersection property:

Each *p* or is called a quorum, and denotes the set of nonnegative integers less than *n*. Given a nonnegative integer *k* and a quorum *q* in a quorum system *Q* under the universal set *U*, we define

*Definition 2.* A quorum system *Q* under *U* has the rotation closure property if the following holds:

*Definition 3.* A set , , and is called a cyclic difference set if for every there exists at least one ordered pair , where , such that , that is, *d* is a difference value between two elements of *D*.

*Definition 4.* Given a difference set , a cyclic quorum system constructed by *D* is , where . For a (7, 3) difference set , for example, the cyclic quorum system is , where .

##### 3.2. FQR Base System

The authors in [25] apply the abovementioned properties of quorum systems to design a FQR system. The frequency-hopping sequence of an SU in FQR is constructed by assigning frequencies to *t* timeslots in one period *X*, which is denoted by , where contains a tuple of (*timeslot index, frequency index*) and represents the frequency index at timeslot *t* in a period. In FQR, an SU generates two different hopping sequences: a sending sequence and a receiving sequence. If an SU has data to transmit, it follows a sending sequence, otherwise, a receiving sequence. For example, consider that a sender and a receiver use a (7, 3) different set, that is, and . And, a cyclic quorum system is constructed from . Thus, the sender and the receiver can select a random number and obtain a quorum and , respectively (e.g., ). A sender node constructs a sending sequence *X* by assigning a frequency index to the timeslot *i* using , where and . Then, it obtains . A receiver node constructs a receiving sequence *Y* by assigning frequency index to the timeslot *i* using , where and . Then, it obtains . Additionally, permuting frequency indexes in each frame of *X* is done as a last step for constructing FQR sequences.

Figure 1(a) shows FQR sequences of both sender and receiver, respectively. It also shows that the sender and receiver rendezvous on frequency 1 at time . The upper bound of TTR of FQR system is only timeslots, which is approximately, equal to *N*. In AFQR, one more timeslot is added into each frame of the *X* sequence, and it is assigned a random frequency such that , where is a quorum selected by the sender. That is, the selected frequency is inserted into a random timeslot in each frame as shown in Figure 1(c). Although this will increase the length of the time period (i.e., timeslots), the expected number of rendezvous within timeslots also increases to . The selected frequency index 5 is added to the sequence in Figure 1(c); thus, one more rendezvous on frequency 5 at time is provided. The techniques used in FQR and AFQR such as scrambling the hopping sequence and inserting additional timeslots make it difficult for a jammer to predict the hopping sequences. However, these schemes are not appropriate in an emergency or tactical scenario where time synchronization between randomly meeting nodes cannot be assumed. Figures 1(b) and 1(d) show that a clock shift nullifies the guaranteed upper bound of rendezvous.