Beyond the convenience of the internet of things: Security and privacy concerns

Moganedi, Sophia; Mtsweni, Jabu

doi:10.23919/istafrica.2017.8102372

Cited by 16 publications

(9 citation statements)

References 42 publications

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“…This is in contrast to time tested protocols, like the TCP/IP suite, that more traditional internetworking devices are built upon. Moganedi & Mtsweni [8] outlined that while IoT devices can introduce great convenience into human life, if the mass amount of personal data that can be collected are not secured or improperly protected against being leaked, any desire to adopt or use such technology will wane and the potential and the ability of what IoT devices can do will be less explored.…”

Section: Security Concerns In Iot Based Networkmentioning

confidence: 99%

IoT security vulnerabilities and predictive signal jamming attack analysis in LoRaWAN

Ingham¹,

Marchang²,

Bhowmik

2020

IET Information Security

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Internet of Things (IoT) gains popularity in recent times due to its flexibility, usability, diverse applicability and ease of deployment. However, the issues related to security is less explored. The IoT devices are light weight in nature and have low computation power, low battery life and low memory. As incorporating security features are resource expensive, IoT devices are often found to be less protected and in recent times, more IoT devices have been routinely attacked due to high profile security flaws. This paper aims to explore the security vulnerabilities of IoT devices particularly that use Low Power Wide Area Networks (LPWANs). In this work, LoRaWAN based IoT security vulnerabilities are scrutinised and loopholes are identified. An attack was designed and simulated with the use of a predictive model of the device data generation. The paper demonstrated that by predicting the data generation model, jamming attack can be carried out to block devices from sending data successfully. This research will aid in the continual development of any necessary countermeasures and mitigations for LoRaWAN and LPWAN functionality of IoT networks in general.

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Section: Security Concerns In Iot Based Networkmentioning

confidence: 99%

IoT security vulnerabilities and predictive signal jamming attack analysis in LoRaWAN

Ingham¹,

Marchang²,

Bhowmik

2020

IET Information Security

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“…The rapid proliferation of insecure IoT devices and ease by which attackers can locate them using online services, such as shodan, provides an ever expanding pool of attack resources. By comprising and leveraging multitudes of these vulnerable IoT devices, attackers can now perform large scale attacks such as spamming, phishing and Distributed Denial of Service (DDoS), against resources on the Internet [5].…”

Section: Introductionmentioning

confidence: 99%

Botnet Detection in the Internet of Things using Deep Learning Approaches

McDermott

Majdani

Petrovski

2018

2018 International Joint Conference on Neural Networks (IJCNN)

252

106

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The recent growth of the Internet of Things (IoT) has resulted in a rise in IoT based DDoS attacks. This paper presents a solution to the detection of botnet activity within consumer IoT devices and networks. A novel application of Deep Learning is used to develop a detection model based on a Bidirectional Long Short Term Memory based Recurrent Neural Network (BLSTM-RNN). Word Embedding is used for text recognition and conversion of attack packets into tokenised integer format. The developed BLSTM-RNN detection model is compared to a LSTM-RNN for detecting four attack vectors used by the mirai botnet, and evaluated for accuracy and loss. The paper demonstrates that although the bidirectional approach adds overhead to each epoch and increases processing time, it proves to be a better progressive model over time. A labelled dataset was generated as part of this research, and is available upon request.

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“…The rapid proliferation of insecure IoT devices and ease by which attackers can locate them using online services, such as shodan [5], provides an ever-expanding pool of attack resources. By comprising multitudes of these vulnerable IoT devices, attackers can now perform large-scale attacks such as spamming, phishing and Distributed Denial of Service (DDoS), against resources on the Internet [6].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Awareness and Perception of Botnet Activity within Consumer Internet-of-Things (IoT) Networks

2019

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The growth of the Internet of Things (IoT), and demand for low-cost, easy-to-deploy devices, has led to the production of swathes of insecure Internet-connected devices. Many can be exploited and leveraged to perform large-scale attacks on the Internet, such as those seen by the Mirai botnet. This paper presents a cross-sectional study of how users value and perceive security and privacy in smart devices found within the IoT. It analyzes user requirements from IoT devices, and the importance placed upon security and privacy. An experimental setup was used to assess user ability to detect threats, in the context of technical knowledge and experience. It clearly demonstrated that without any clear signs when an IoT device was infected, it was very difficult for consumers to detect and be situationally aware of threats exploiting home networks. It also demonstrated that without adequate presentation of data to users, there is no clear correlation between level of technical knowledge and ability to detect infected devices.

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Beyond the convenience of the internet of things: Security and privacy concerns

Cited by 16 publications

References 42 publications

IoT security vulnerabilities and predictive signal jamming attack analysis in LoRaWAN

IoT security vulnerabilities and predictive signal jamming attack analysis in LoRaWAN

Botnet Detection in the Internet of Things using Deep Learning Approaches

Evaluating Awareness and Perception of Botnet Activity within Consumer Internet-of-Things (IoT) Networks

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