scholarly journals Enabling Processing Power Scalability with Internet of Things (IoT) Clusters

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 81
Author(s):  
Jorge Coelho ◽  
Luís Nogueira
Keyword(s):  
Internet Of Things ◽  
Programming Language ◽  
Network Traffic ◽  
Crucial Role ◽  
State Of The Art ◽  
End User ◽  
Processing Power ◽  
Increasing Demand ◽  
Iot Devices ◽  
Traditional Approaches

Internet of things (IoT) devices play a crucial role in the design of state-of-the-art infrastructures, with an increasing demand to support more complex services and applications. However, IoT devices are known for having limited computational capacities. Traditional approaches used to offload applications to the cloud to ease the burden on end-user devices, at the expense of a greater latency and increased network traffic. Our goal is to optimize the use of IoT devices, particularly those being underutilized. In this paper, we propose a pragmatic solution, built upon the Erlang programming language, that allows a group of IoT devices to collectively execute services, using their spare resources with minimal interference, and achieving a level of performance that otherwise would not be met by individual execution.

scholarly journals The Audio Auditor: User-Level Membership Inference in Internet of Things Voice Services

2021 ◽  
Vol 2021 (1) ◽  
pp. 209-228
Author(s):  
Yuantian Miao ◽  
Minhui Xue ◽  
Chao Chen ◽  
Lei Pan ◽  
Jun Zhang ◽  
...  
Keyword(s):  
Internet Of Things ◽  
State Of The Art ◽  
Rapid Development ◽  
Black Box ◽  
Problem Space ◽  
Specific Data ◽  
Learning Techniques ◽  
Audio Data ◽  
Iot Devices ◽  
Asr System

AbstractWith the rapid development of deep learning techniques, the popularity of voice services implemented on various Internet of Things (IoT) devices is ever increasing. In this paper, we examine user-level membership inference in the problem space of voice services, by designing an audio auditor to verify whether a specific user had unwillingly contributed audio used to train an automatic speech recognition (ASR) model under strict black-box access. With user representation of the input audio data and their corresponding translated text, our trained auditor is effective in user-level audit. We also observe that the auditor trained on specific data can be generalized well regardless of the ASR model architecture. We validate the auditor on ASR models trained with LSTM, RNNs, and GRU algorithms on two state-of-the-art pipelines, the hybrid ASR system and the end-to-end ASR system. Finally, we conduct a real-world trial of our auditor on iPhone Siri, achieving an overall accuracy exceeding 80%. We hope the methodology developed in this paper and findings can inform privacy advocates to overhaul IoT privacy.

scholarly journals Adjusting Group Communication in Dense Internet of Things Networks with Heterogeneous Energy Sources

2019 ◽  
Author(s):  
Renato Mota ◽  
André Riker ◽  
Denis Rosário
Keyword(s):  
Internet Of Things ◽  
Energy Efficient ◽  
Group Communication ◽  
State Of The Art ◽  
Dynamic Control ◽  
Energy Resources ◽  
Extensive Evaluation ◽  
Message Loss ◽  
Loss Event ◽  
Iot Devices

Internet-of-Things (IoT) environments will have a large number of nodes organized into groups to collect and to disseminate data. In this sense, one of the main challenges in IoT environments is to dynamically manage communication characteristics of IoT devices to decrease congestion, traffic collisions, and excessive data collection, as well as to balance the use of energy resources. In this paper, we introduce an energy-efficient and reliable Self Adjusting group communication of dense IoT Network, called SADIN. It configures the communication settings to ensure a dynamic control of IoT devices considering a comprehensive set of aspects, i.e., traffic loss, event relevance, amount of nodes with renewable batteries, and the number of observers. Specifically, SADIN changes the communication interval, the number of data producers, the reliability level of the network. Extensive evaluation results show that SADIN improves system performance in terms of message loss, energy consumption, and reliability compared to state-of-the-art protocol.

scholarly journals Physical Unclonable Functions in the Internet of Things: State of the Art and Open Challenges

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3208 ◽  
Author(s):  
Armin Babaei ◽  
Gregor Schiele
Keyword(s):  
Internet Of Things ◽  
State Of The Art ◽  
The Internet ◽  
Physical Unclonable Functions ◽  
Iot Devices ◽  
Computational Resources ◽  
The Internet Of Things

Attacks on Internet of Things (IoT) devices are on the rise. Physical Unclonable Functions (PUFs) are proposed as a robust and lightweight solution to secure IoT devices. The main advantage of a PUF compared to the current classical cryptographic solutions is its compatibility with IoT devices with limited computational resources. In this paper, we investigate the maturity of this technology and the challenges toward PUF utilization in IoT that still need to be addressed.

A Novel Insider Attack and Machine Learning Based Detection for the Internet of Things

2021 ◽  
Vol 2 (4) ◽  
pp. 1-23
Author(s):  
Morshed Chowdhury ◽  
Biplob Ray ◽  
Sujan Chowdhury ◽  
Sutharshan Rajasegarar
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Network Traffic ◽  
The Internet ◽  
Traffic Data ◽  
Lossy Networks ◽  
Insider Attack ◽  
Iot Devices ◽  
The Impact ◽  
The Internet Of Things

Due to the widespread functional benefits, such as supporting internet connectivity, having high visibility and enabling easy connectivity between sensors, the Internet of Things (IoT) has become popular and used in many applications, such as for smart city, smart health, smart home, and smart vehicle realizations. These IoT-based systems contribute to both daily life and business, including sensitive and emergency situations. In general, the devices or sensors used in the IoT have very limited computational power, storage capacity, and communication capabilities, but they help to collect a large amount of data as well as maintain communication with the other devices in the network. Since most of the IoT devices have no physical security, and often are open to everyone via radio communication and via the internet, they are highly vulnerable to existing and emerging novel security attacks. Further, the IoT devices are usually integrated with the corporate networks; in this case, the impact of attacks will be much more significant than operating in isolation. Due to the constraints of the IoT devices, and the nature of their operation, existing security mechanisms are less effective for countering the attacks that are specific to the IoT-based systems. This article presents a new insider attack, named loophole attack , that exploits the vulnerabilities present in a widely used IPv6 routing protocol in IoT-based systems, called RPL (Routing over Low Power and Lossy Networks). To protect the IoT system from this insider attack, a machine learning based security mechanism is presented. The proposed attack has been implemented using a Contiki IoT operating system that runs on the Cooja simulator, and the impacts of the attack are analyzed. Evaluation on the collected network traffic data demonstrates that the machine learning based approaches, along with the proposed features, help to accurately detect the insider attack from the network traffic data.

scholarly journals Hyperledger Fabric Blockchain for Securing the Edge Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 359
Author(s):  
Houshyar Honar Pajooh ◽  
Mohammad Rashid ◽  
Fakhrul Alam ◽  
Serge Demidenko
Keyword(s):  
Internet Of Things ◽  
Performance Metrics ◽  
Security And Privacy ◽  
Practical Implementation ◽  
Blockchain Technology ◽  
Performance Requirements ◽  
Processing Power ◽  
Proposed Model ◽  
Iot Devices ◽  
Research Challenge

Providing security and privacy to the Internet of Things (IoT) networks while achieving it with minimum performance requirements is an open research challenge. Blockchain technology, as a distributed and decentralized ledger, is a potential solution to tackle the limitations of the current peer-to-peer IoT networks. This paper presents the development of an integrated IoT system implementing the permissioned blockchain Hyperledger Fabric (HLF) to secure the edge computing devices by employing a local authentication process. In addition, the proposed model provides traceability for the data generated by the IoT devices. The presented solution also addresses the IoT systems’ scalability challenges, the processing power and storage issues of the IoT edge devices in the blockchain network. A set of built-in queries is leveraged by smart-contracts technology to define the rules and conditions. The paper validates the performance of the proposed model with practical implementation by measuring performance metrics such as transaction throughput and latency, resource consumption, and network use. The results show that the proposed platform with the HLF implementation is promising for the security of resource-constrained IoT devices and is scalable for deployment in various IoT scenarios.

scholarly journals Efficient distributed network covert channels for Internet of things environments†

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Krzysztof Cabaj ◽  
Piotr Żórawski ◽  
Piotr Nowakowski ◽  
Maciej Purski ◽  
Wojciech Mazurczyk
Keyword(s):  
Internet Of Things ◽  
Communication Networks ◽  
Data Hiding ◽  
Network Traffic ◽  
Data Transfer ◽  
Research Area ◽  
Distributed Network ◽  
Covert Channels ◽  
Secret Communication ◽  
Iot Devices

Abstract Each day more and more Internet of Things (IoT) devices are being connected to the Internet. In general, their applications are diverse but from the security perspective, it is evident that they are increasingly targeted by cybercriminals and used for nefarious purposes. Network covert channels form a subgroup of the information-hiding research area where secrets are sent over communication networks embedded within the network traffic. Such techniques can be used, among others, by malware developers to enable confidential data exfiltration or stealth communications. Recently, distributed network covert channels have raised the attention of security professionals as they allow the cloaking of secret transmission by spreading the covert bits among many different types of data-hiding techniques. However, although there are many works dealing with IoT security, little effort so far has been devoted in determining how effective the covert channels threat can be in the IoT henvironments. That is why, in this article, we present an extensive analysis on how distributed network covert channels that utilize network traffic from IoT devices can be used to perform efficient secret communication. More importantly, we do not focus on developing novel data-hiding techniques but, instead, considering the nature of IoT traffic, we investigate how to combine existing covert channels so the resulting data transfer is less visible. Moreover, as another contribution of our work, we prepare and share with the community the network traffic dataset that can be used to develop effective countermeasures against such threats.

scholarly journals Firmware Over-the-air Programming Techniques for IoT Networks - A Survey

2022 ◽  
Vol 54 (9) ◽  
pp. 1-36
Author(s):  
Konstantinos Arakadakis ◽  
Pavlos Charalampidis ◽  
Antonis Makrogiannakis ◽  
Alexandros Fragkiadakis
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
State Of The Art ◽  
Security Vulnerabilities ◽  
Software Bugs ◽  
Programming Techniques ◽  
Iot Devices ◽  
Physical Access ◽  
Update Process ◽  
Access Resource

The devices forming Internet of Things (IoT) networks need to be re-programmed over the air, so that new features are added, software bugs or security vulnerabilities are resolved, and their applications can be re-purposed. The limitations of IoT devices, such as installation in locations with limited physical access, resource-constrained nature, large scale, and high heterogeneity, should be taken into consideration for designing an efficient and reliable pipeline for over-the-air programming (OTAP). In this work, we present a survey of OTAP techniques, which can be applied to IoT networks. We highlight the main challenges and limitations of OTAP for IoT devices and analyze the essential steps of the firmware update process, along with different approaches and techniques that implement them. In addition, we discuss schemes that focus on securing the OTAP process. Finally, we present a collection of state-of-the-art open-source and commercial platforms that integrate secure and reliable OTAP.

scholarly journals Blocking Without Breaking: Identification and Mitigation of Non-Essential IoT Traffic

2021 ◽  
Vol 2021 (4) ◽  
pp. 369-388
Author(s):  
Anna Maria Mandalari ◽  
Daniel J. Dubois ◽  
Roman Kolcun ◽  
Muhammad Talha Paracha ◽  
Hamed Haddadi ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Network Traffic ◽  
Internet Traffic ◽  
Third Parties ◽  
The Internet ◽  
Prototype System ◽  
Network Connections ◽  
Iot Devices ◽  
Internet Connections ◽  
Open Question

Abstract Despite the prevalence of Internet of Things (IoT) devices, there is little information about the purpose and risks of the Internet traffic these devices generate, and consumers have limited options for controlling those risks. A key open question is whether one can mitigate these risks by automatically blocking some of the Internet connections from IoT devices, without rendering the devices inoperable. In this paper, we address this question by developing a rigorous methodology that relies on automated IoT-device experimentation to reveal which network connections (and the information they expose) are essential, and which are not. We further develop strategies to automatically classify network traffic destinations as either required (i.e., their traffic is essential for devices to work properly) or not, hence allowing firewall rules to block traffic sent to non-required destinations without breaking the functionality of the device. We find that indeed 16 among the 31 devices we tested have at least one blockable non-required destination, with the maximum number of blockable destinations for a device being 11. We further analyze the destination of network traffic and find that all third parties observed in our experiments are blockable, while first and support parties are neither uniformly required or non-required. Finally, we demonstrate the limitations of existing blocklists on IoT traffic, propose a set of guidelines for automatically limiting non-essential IoT traffic, and we develop a prototype system that implements these guidelines.

scholarly journals IoT DoS and DDoS Attack Detection using ResNet

2020 ◽  
Author(s):  
Faisal Hussain ◽  
Syed Ghazanfar Abbas ◽  
Muhammad Husnain ◽  
Ubaid U. Fayyaz ◽  
Farrukh Shahzad ◽  
...  
Keyword(s):  
Network Traffic ◽  
State Of The Art ◽  
Binary Classification ◽  
Denial Of Service ◽  
Attack Detection ◽  
Ddos Attacks ◽  
Detection Systems ◽  
Ddos Attack ◽  
Attack Patterns ◽  
Iot Devices

Abstract The network attacks are increasing both in frequency and intensity with the rapid growth of internet of things (IoT) devices. Recently, denial of service (DoS) and distributed denial of service (DDoS) attacks are reported as the most frequent attacks in IoT networks. The traditional security solutions like firewalls, intrusion detection systems, etc., are unable to detect the complex DoS and DDoS attacks since most of them filter the normal and attack traffic based upon the static predefined rules. However, these solutions can become reliable and effective when integrated with artificial intelligence (AI) based techniques. During the last few years, deep learning models especially convolutional neural networks achieved high significance due to their outstanding performance in the image processing field. The potential of these convolutional neural network (CNN) models can be used to efficiently detect the complex DoS and DDoS by converting the network traffic dataset into images. Therefore, in this work, we proposed a methodology to convert the network traffic data into image form and trained a state-of-the-art CNN model, i.e., ResNet over the converted data. The proposed methodology accomplished 99.99\% accuracy for detecting the DoS and DDoS in case of binary classification. Furthermore, the proposed methodology achieved 87\% average precision for recognizing eleven types of DoS and DDoS attack patterns which is 9\% higher as compared to the state-of-the-art.

scholarly journals An exploration of the Wearable Internet of Things (WIoT) Users‟ Privacy Concerns in healthcare domain

2020 ◽  
Vol 9 (2) ◽  
pp. 742-749
Keyword(s):  
Health Care ◽  
Internet Of Things ◽  
End User ◽  
Privacy And Security ◽  
Privacy Issue ◽  
Privacy Concerns ◽  
Iot Devices ◽  
Privacy Risks ◽  
Privacy Issues ◽  
Health Process

Internet of things (IoT) is earning a significant role in the health care domain. Though the growing benefits to improve the health process and services and the large use of the Wearable Internet of Things (WIoT) devices, the patient’s privacy issue remains a big concern. While IoT devices and its applications are more exposed to privacy risks, there is a need for a stick and strict guidelines and solutions to assist and solve this issue and minimize these risks. The aim of this paper is to survey the end-user concerns of the privacy issues related to WIoT then we review conducted on current solutions that are worked toward preserving privacy in the healthcare domain, and finally, we state our solution. This paper aims to survey end users’ privacy and security concerns and issues related to WIoT.

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