A Survey on the Security of Low Power Wide Area Networks: Threats, Challenges, and Potential Solutions

Alimi, Kuburat Oyeranti Adefemi; Ouahada, Khmaies; Abu‐Mahfouz, Adnan M.; Rimer, Suvendi

doi:10.3390/s20205800

Cited by 25 publications

(12 citation statements)

References 77 publications

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“…Authenticity and integrity in LoRaWAN are satisfied by design using two session keys encrypted with 128-bit AES. Each packet encrypted with AES-CTR carries a frame counter (to prevent packet replication) and a message integrity code computed with AES-CMAC (to prevent packet tampering) [ 57 , 58 ]. The cellular network, from 3G onwards and using the 3GPP protocol, guarantees data integrity and allows secure authentication thanks to its three main components: user equipment, a mobile management entity, and a home-subscriber server [ 59 ].…”

Section: Discussionmentioning

confidence: 99%

Addressing Gaps in Small-Scale Fisheries: A Low-Cost Tracking System

Tassetti

Galdelli

Pulcinella

et al. 2022

Sensors

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During the last decade vessel-position-recording devices, such as the Vessel Monitoring System and the Automatic Identification System, have increasingly given accurate spatial and quantitative information of industrial fisheries. On the other hand, small-scale fisheries (vessels below 12 m) remain untracked and largely unregulated even though they play an important socio-economic and cultural role in European waters and coastal communities and account for most of the total EU fishing fleet. The typically low-technological capacity of these small-scale fishing boats—for which space and power onboard are often limited—as well their reduced operative range encourage the development of efficient, low-cost, and low-burden tracking solutions. In this context, we designed a cost-effective and scalable prototypic architecture to gather and process positional data from small-scale vessels, making use of a LoRaWAN/cellular network. Data collected by our first installation are presented, as well as its preliminary processing. The emergence of a such low-cost and open-source technology coupled to artificial intelligence could open new opportunities for equipping small-scale vessels, collecting their trajectory data, and estimating their fishing effort (information which has historically not been present). It enables a new monitoring strategy that could effectively include small-scale fleets and support the design of new policies oriented to inform coastal resource and fisheries management.

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Section: Discussionmentioning

confidence: 99%

Addressing Gaps in Small-Scale Fisheries: A Low-Cost Tracking System

Tassetti

Galdelli

Pulcinella

et al. 2022

Sensors

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“…Basu et al [23] discusses about various security issues of Low Power Wide Area Networks in the context of LoRa networks in their survey paper. Another similar kind of survey on security of Low Power Wide Area Networks, its threats, challenges, and potential solutions are done by Adefemi Alimi et al [24]. Iqbal et al [25] addresses numerous security and authenticity problems involved with the SCADA system for LoRa-based wireless communication.…”

Section: Related Workmentioning

confidence: 99%

Implementing cryptography in LoRa based communication devices for unmanned ground vehicle applications

Manuel

Daimi

2021

SN Appl. Sci.

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In this study, a Long Range (LoRa) based bidirectional secured communication link for controlling and monitoring the robots from a remote location is proposed. The security features and structure of the LoRa is build upon the standard protocol called LoRa wide area networks (LoRaWAN). To take advantage of these features, LoRa devices/end modules need to be connected to a network server through a LoRa gateway. However, for certain military scenarios like war zones, terrorist attack sites, disaster sites etc., the availability of standard network cannot be guaranteed, and therefore, the security features available with LoRaWAN protocol cannot be guaranteed. To overcome this critical limitation, a LoRa based secured device for establishing a bidirectional communication link between the base station and the robots without relying on any network is proposed. To secure the exchanged data, a cryptographic protocol is developed, and confidentiality, authenticity and integrity of the transmitted data between the base station and the robot are ensured. The protocol is then implemented with a pair of LoRa devices and its functionality is tested from a remote location by controlling and monitoring a Pioneer-P3Dx robot from a distance of 1.2 miles. The test shows that the proposed cryptographic protocol can securely control and track the robot from a remote location.

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“…A denial of service (DoS) attack can be described as an attempt by malicious attackers to consume network resources or bandwidth by temporarily or indefinitely disrupting the network services of a computer or any devices connected to a network [12]. They are the most common and dangerous cyberattack against IoT devices which leads IoT systems to total shut down [19].…”

Section: Overview Of Denial-of-service (Dos) Attackmentioning

confidence: 99%

“…The extensive deployment of IoT devices in an open environment has exposed the networks to various cyberattacks and security threats [10]. Numerous cyberattacks such as replay, wormhole, Sybil, man-in-the-middle (MITM), denial of service (DoS), side-channel, etc., have continued to be a menace [11][12][13]. Hence, it is important to develop an effective security measure that can constantly and urgently learn and detect attacks such as DoS attacks in IoT networks.…”

Section: Introductionmentioning

confidence: 99%

Refined LSTM Based Intrusion Detection for Denial-of-Service Attack in Internet of Things

Alimi

Ouahada

Abu‐Mahfouz

et al. 2022

JSAN

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The Internet of Things (IoT) is a promising technology that allows numerous devices to be connected for ease of communication. The heterogeneity and ubiquity of the various connected devices, openness to devices in the network, and, importantly, the increasing number of connected smart objects (or devices) have exposed the IoT network to various security challenges and vulnerabilities which include manipulative data injection and cyberattacks such as a denial of service (DoS) attack. Any form of intrusive data injection or attacks on the IoT networks can create devastating consequences on the individual connected device or the entire network. Hence, there is a crucial need to employ modern security measures that can protect the network from various forms of attacks and other security challenges. Intrusion detection systems (IDS) and intrusion prevention systems have been identified globally as viable security solutions. Several traditional machine learning methods have been deployed as IoT IDS. However, the methods have been heavily criticized for poor performances in handling voluminous datasets, as they rely on domain expertise for feature extraction among other reasons. Thus, there is a need to devise better IDS models that can handle the IoT voluminous datasets efficiently, cater to feature extraction, and perform reasonably well in terms of overall performance. In this paper, an IDS based on redefined long short-term memory deep learning approach is proposed for detecting DoS attacks in IoT networks. The model was tested on benchmark datasets; CICIDS-2017 and NSL-KDS datasets. Three pre-processing procedures, which include encoding, dimensionality reduction, and normalization were deployed for the datasets. Using key classification metrics, experimental results obtained show that the proposed model can effectively detect DoS attacks in IoT networks as it performs better compared to other methods including models from related works.

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A Survey on the Security of Low Power Wide Area Networks: Threats, Challenges, and Potential Solutions

Cited by 25 publications

References 77 publications

Addressing Gaps in Small-Scale Fisheries: A Low-Cost Tracking System

Addressing Gaps in Small-Scale Fisheries: A Low-Cost Tracking System

Implementing cryptography in LoRa based communication devices for unmanned ground vehicle applications

Refined LSTM Based Intrusion Detection for Denial-of-Service Attack in Internet of Things

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