# Random Access Performance of Distributed Sensors Attacked by Unknown Jammers
## 1 Introduction  
With the development of a wide range of intelligent and tiny wireless sensing devices, wireless sensor networks (WSNs) are being used for many applications in the fields of medical, industry, defense, smart homes, etc. In addition to these applications, WSNs currently drive Internet of Things (IoT) and machine-to-machine communications. WSNs consist of numerous sensor nodes (SNs) that are usually interconnected through radio frequency (RF) communication links. Since the signal quality on a wireless medium such as RF easily degrades by unwanted interference, WSNs are vulnerable to malfunctioning SNs. In WSNs, attackers can create malicious SNs that can disrupt desired wireless transmission by generating interference and noise [1, 2], which is so-called jamming [3]. Jamming attacks severely degrade the performance of WSNs, to a large extent, in energy consumption, throughput and delay. Jamming attacks may be viewed as a special case of denial of service (DoS) attacks, which prevent or inhibit the normal use or management of communications through flooding a network with uselessinformation using RF signals [4]. In [5], various techniques for detecting the presence of jamming attacks in WSNs are explored. In [6], jamming attacks and network defense policies are modeled together in order to capture the effect of knowledge available at each side. For LTE systems, jamming is also regarded as a major attack that causes significant DoS [7,8]. While most works have focused on the physical-layer aspects of jamming attacks, reference [9] evaluates the resilience of WSNs to jamming attacks in the aspect of the routing protocol. On the other hand, jamming is also used to prevent eavesdroppers (Eves) from snooping legitimate communications, which is often called friendly jamming [10, 11, 12] or cooperative jamming [13, 14]. The works in [10, 12] investigate system-level issues of introducing friendly jammers. However, most works regarding cooperative jamming are in the direction of recently developing physical-layer security. In [13], multi-antenna jammers use null-space artificial noise (AN) that increases interference of Eves, but is avoided by the legitimate user, for which the right knowledge of the channel between the jammer and the Eves is essential. In [14], the cooperative jammers harvest energy transmitted by a source and use it to generate AN to jam the Eves in cognitive IoT networks, in which an auction framework that formulates the jammer selection and the power allocation together is also provided. In WSNs, the messages are usually short and transmitted through random access (RA) procedures. However, to the best of our knowledge, there is a lack of detailed analysis in RA performance when attacked (or influenced) by jamming. In this paper, we model and investigate RA performance that is degraded by unknown jamming attacks. We assume that a central SN (referred to as the head sensor (HS) in this paper) collects information from distributed SNs through the RA channel (RACH). In order to avoid heavy collisions and contentions among crowded SNs, we assume a collision avoidance mechanism in which SNs transmit short preamble signals first and then send information messages only if they receive an indicator of acquisition (AI) of the preamble from HS. We assume a WSN that adopts direct sequence spread spectrum modulation like in ZigBee [15], IEEE 802.15.4 [16] and UMTS WCDMA [17] applications. Furthermore, two jamming attacks are considered: power and code jamming. In power jamming, attackers (if they are friendly jammers) generate noises and, as a result, degrade the quality of the signal from SNs. Power jamming is equally harmful to all the SNs that are accessing HS. To overcome the prevailing interference, so-called power-ramping by which SNs gradually increase transmitting power in preamble transmission is also modeled in this paper. Power jamming simply induces DoS without any need to hack HS and SNs.