## 5 LPWAN Security Analysis
### Availability  
Availability refers to a situation whereby network resources are always available for authorized user when required [57; 58]. Data availability prevents bottleneck situations which hinders information flow. The most prominent availability menace is Denial of Service (DoS) attacks. DoS attack is described as an attempt by malicious attackers to consume network resources or bandwidth [55]. The most common DoS attack include DNS flood, Internet Control Message Protocol (ICMP) broadcast and SYN flood [75; 76]. The authors in [67] highlighted jamming attack (a subset of DoS attack) as a major security issue in LoRa and LoRaWAN. With regards to LPWAN availability menaces mitigations, several encryption models, IDSs and other security measures have been proposed in the literature. IDS are security systems or models that monitor and collect information from various infrastructures within a network and analyzes the data in an attempt to detect malicious events that threaten the network. The data collected overtime aids the network and network administrators in preparing for, and deal with intrusion and intrusion attempts on their networks. The major types of IDS are network-based and host-based. While host-based IDS deal with internal monitoring whereby it collects information about activities on a particular single host that is well known to be susceptible to possible attacks, network-based IDS collect information from the entire network traffic stream. For more details on IDSs, the authors refer readers to [77; 78; 79; 80; 81]. With regards to IoT security, various approaches including machine learning and deep learning models have been proposed for IDSs in the literature. The authors in [82] proposed an IDS using an ensemble of boosted and bagged trees, subspace discriminant and RUS boosted trees for detecting routing attacks against IPv6 Routing Protocol. Testing their algorithms on RPL-NIDDS17 dataset, the authors acknowledged the ensemble of boosted trees with an accuracy of 94.5% outperformed the other models. Similarly, the authors in [83] combined network virtualization with deep learning algorithms as IDS for detecting various prominent attacks including DoS on IoT network. The authors in [84] also proposed an IDS for the detection of DDoS attacks in IoT networks using the hybridization of multi-objective optimization algorithms and deep learning algorithms. Also, [85] proposed an IDS using multi-layered perceptron neural network for detecting DoS attacks in IoT networks. The proposed scheme achieved an accuracy of 92.84% in successfully detecting various form of DDoS/DoS attacks. Despite the numerous varieties of IDS works on the general IoT domain, only a few studies in the literature have specifically considered IDSs for mitigating the various security challenges in LPWANs. The authors in [19] proposed a Kullback Leibler Divergence (KLD) and Hamming Distance (HD) based IDS for detecting jamming attacks in a developed LoRaWAN testbed. In the developed experimental testbed that is made up of hardware devices which includes raspberry pi 2, Arduino uno and LoRa SX1272 mbed shield that are used as gateway and end node devices. In the study, a network server that is written in python was programmed by the authors. In a similar mitigation study, the authors in [86] addressed the issue of lack of forward secrecy, flaw in delegation of join procedure in case of fall-back, and limitations in replay protection that are peculiar with LoRaWAN v1.1. The authors proposed countermeasures that tackles the application data integrity and confidentiality violations in case of join procedure delegation and malicious network server. Apart from the cyber security issue which covers the application layer and network layer of LPWA networks, security issues and attacks can be perpetrated at LPWAN physical layer as well. As IoT and LPWAN devices are extensively deployed in an open environment, these have allowed larger attack surfaces and physical access to network hardware devices such as sensors, nodes and actuators.