Wireless Technologies in IoT: Research Challenges

Dhanda, Sumit Singh; Singh, Brahmjit; Jindal, Poonam

doi:10.1007/978-981-13-1642-5_21

Cited by 10 publications

(5 citation statements)

References 31 publications

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“…IoT sensors and actuators are being developed for various applications while becoming more cost-effective [ 16 , 17 ]. Moreover, improved wireless protocols offer lightweight solutions with a broader signal coverage, better connection stability and reliability, lower energy demand, and more robust security measures [ 18 , 19 ]. Machine learning also contributes to developing numerous solutions, such as chatbots [ 20 ], automated video analyzers for CCTVs [ 21 ], anomaly detection solutions [ 22 ], and intelligent computer–human interaction technologies [ 23 ].…”

Section: Smart Home Securitymentioning

confidence: 99%

Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack

Abrishamchi

Zainal

Ghaleb

et al. 2022

Sensors

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Smart home technologies have attracted more users in recent years due to significant advancements in their underlying enabler components, such as sensors, actuators, and processors, which are spreading in various domains and have become more affordable. However, these IoT-based solutions are prone to data leakage; this privacy issue has motivated researchers to seek a secure solution to overcome this challenge. In this regard, wireless signal eavesdropping is one of the most severe threats that enables attackers to obtain residents’ sensitive information. Even if the system encrypts all communications, some cyber attacks can still steal information by interpreting the contextual data related to the transmitted signals. For example, a “fingerprint and timing-based snooping (FATS)” attack is a side-channel attack (SCA) developed to infer in-home activities passively from a remote location near the targeted house. An SCA is a sort of cyber attack that extracts valuable information from smart systems without accessing the content of data packets. This paper reviews the SCAs associated with cyber–physical systems, focusing on the proposed solutions to protect the privacy of smart homes against FATS attacks in detail. Moreover, this work clarifies shortcomings and future opportunities by analyzing the existing gaps in the reviewed methods.

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Section: Smart Home Securitymentioning

confidence: 99%

Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack

Abrishamchi

Zainal

Ghaleb

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…The metrics used to compare the two MAC protocols is the Packet Loss Ratio (PLR), defined as the ratio between the number of lost messages (n lostMsg ) and the overall number of transmitted messages (n txMsg ) measured at the Application layer. The PLR is expressed as a percentage, according to Equation (1). PLR = n lostMsg n txMsg * 100 (1)…”

Section: Simulative Assessmentmentioning

confidence: 99%

“…The IoT paradigm is presently successfully applied to a broad set of scenarios with very heterogeneous requirements, such as smart cities, healthcare, and smart environments [1]. For instance, an IoT-based monitoring system such as the virtual biosensor for MEDIcal WARNing precursor (MEDIWARN) helps the medical team to better understand the patients' clinical condition and take prompt action in response to the health conditions [2].…”

Section: Introductionmentioning

confidence: 99%

Comparative Assessment of the LoRaWAN Medium Access Control Protocols for IoT: Does Listen before Talk Perform Better than ALOHA?

et al. 2020

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Low-Power Wide-Area Networks (LPWANs) are emerging as appealing solutions for several Internet of Things (IoT) applications, such as healthcare, smart cities and Industry 4.0, thanks to their ease of deployment, low energy consumption and large coverage range. LoRaWAN is one of the most successful LPWAN standards, as it supports robust long-distance communications using low-cost devices. To comply with the ETSI regulations, LoRaWAN can adopt as medium access control (MAC) layer either a pure ALOHA approach with duty-cycle limitations or a polite spectrum access technique, such as Listen Before Talk (LBT). The two approaches have their pros and cons that need to be carefully evaluated. The studies in the literature that so far have addressed an evaluation of MAC protocols for LoRaWAN refer to a previous and now obsolete version of the ETSI regulations, therefore they do not take into account the current limits on the timing parameters for polite spectrum access, such as that maximum time an end-node is allowed to be transmitting per hour. For this reason, the contribution of this work is two-fold. First, the paper discusses the restrictions that the current ETSI regulations impose on some timing parameters of the two kinds of MAC protocols for LoRaWAN. Second, the paper provides comparative performance assessments of the two protocols through simulations in realistic scenarios under different workload conditions.

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“…There are challenges to solve in IoT, for instance, the amount of energy that each accessory requires and the coexistence of thousands of wireless devices that may use different technologies for communicating [13]. In particular, coexistence is a severe threat to IoT, since the devices that are trying to communicate may collide with each other resulting in data lost, rendering the sensors useless.…”

Section: Energy and Power Consumptionmentioning

confidence: 99%

Smart Campus: An Experimental Performance Comparison of Collaborative and Cooperative Schemes for Wireless Sensor Network

et al. 2019

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Presently, the Internet of Things (IoT) concept involves a scattered collection of different multipurpose sensor networks that capture information, which is further processed and used in applications such as smart cities. These networks can send large amounts of information in a fairly efficient but insecure wireless environment. Energy consumption is a key aspect of sensor networks since most of the time, they are battery powered and placed in not easily accessible locations. Therefore, and regardless of the final application, wireless sensor networks require a careful energy consumption analysis that allows selection of the best operating protocol and energy optimization scheme. In this paper, a set of performance metrics is defined to objectively compare different kinds of protocols. Four of the most popular IoT protocols are selected: Zigbee, LoRa, Bluethooth, and WiFi. To test and compare their performance, multiple sensors are placed at different points of a university campus to create a network that can accurately simulate a smart city. Finally, the network is analyzed in detail using two different schemes: collaborative and cooperative.

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Wireless Technologies in IoT: Research Challenges

Cited by 10 publications

References 31 publications

Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack

Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack

Comparative Assessment of the LoRaWAN Medium Access Control Protocols for IoT: Does Listen before Talk Perform Better than ALOHA?

Smart Campus: An Experimental Performance Comparison of Collaborative and Cooperative Schemes for Wireless Sensor Network

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