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 Grid-PPPS: A Skyline Method for Efficiently Handling Top-kQueries in Internet of Things

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Sun-Young Ihm ◽  
Aziz Nasridinov ◽  
Young-Ho Park
Keyword(s):  
Internet Of Things ◽  
State Of The Art ◽  
Rapid Development ◽  
The Internet ◽  
Space Partitioning ◽  
Data Space ◽  
Index Building ◽  
Representative Skyline ◽  
The Internet Of Things ◽  
Grid Based

A rapid development in wireless communication and radio frequency technology has enabled the Internet of Things (IoT) to enter every aspect of our life. However, as more and more sensors get connected to the Internet, they generate huge amounts of data. Thus, widespread deployment of IoT requires development of solutions for analyzing the potentially huge amounts of data they generate. A top-kquery processing can be applied to facilitate this task. The top-kqueries retrievektuples with the lowest or the highest scores among all of the tuples in the database. There are many methods to answer top-kqueries, where skyline methods are efficient when considering all attribute values of tuples. The representative skyline methods are soft-filter-skyline (SFS) algorithm, angle-based space partitioning (ABSP), and plane-project-parallel-skyline (PPPS). Among them, PPPS improves ABSP by partitioning data space into a number of spaces using hyperplane projection. However, PPPS has a high index building time in high-dimensional databases. In this paper, we propose a new skyline method (called Grid-PPPS) for efficiently handling top-kqueries in IoT applications. The proposed method first performs grid-based partitioning on data space and then partitions it once again using hyperplane projection. Experimental results show that our method improves the index building time compared to the existing state-of-the-art methods.

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.

scholarly journals A Novel Approach towards the Design and Implementation of Virtual Network Based on Controller in Future IoT Applications

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 604
Author(s):  
Faisal Mehmood ◽  
Israr Ullah ◽  
Shabir Ahmad ◽  
Do-Hyeun Kim
Keyword(s):  
Internet Of Things ◽  
Traffic Congestion ◽  
Rapid Development ◽  
Remote Access ◽  
Virtual Network ◽  
The Internet ◽  
Minimal Network ◽  
Virtual Objects ◽  
Design And Implementation ◽  
Iot Devices

The Internet of Things refers (IoT) to the billions of physical devices around the globe that are connected to the Internet, collecting and sharing data. The overall Internet of Things market is projected to be worth more than 50.6 billion U.S. dollars in 2020. IoT devices possess low processing capabilities, limited memory, limited storage, and minimal network protocol support. With the help of cloud computing technology, we can overcome the limited resources of IoT devices. A lot of research has been conducted on IoT device virtualization to facilitate remote access and control. The concept of virtualization in IoT is to provide a virtual representation of physical devices in the form of virtual objects. IoT devices are more likely to be accessed and communicate through virtual objects in the near future. In this paper, we present the design and implementation of building a virtual IoT network for a smart home. The virtual network is based on virtual objects and IoT controller. We derived the concept from Software Defined Network (SDN) and separated the control plane and data plane in the virtual IoT network. This enhanced the rapid development of diverse applications on top of the virtualization layer by establishing a dynamic end-to-end connection between IoT devices. This article briefly explains the design and development of the virtual network. Results achieved during experiments and performance analysis show that IoT controller enhances the capabilities of a virtual network by dynamically controlling the traffic congestion, handling mapping requests, and routing mechanisms.

scholarly journals Automated diagnosis of attacks in internet of things using machine learning and frequency distribution techniques

2021 ◽  
Vol 10 (2) ◽  
pp. 950-961
Author(s):  
Toufik Ghrib ◽  
Mohamed Benmohammed ◽  
Purnendu.Shekhar Pandey
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Ensemble Methods ◽  
Machine Learning Techniques ◽  
Sensitive Data ◽  
Learning Techniques ◽  
Image Set ◽  
Iot Devices ◽  
Table Data ◽  
Multi Class Classification

The Internet of Things (IoT) is the interconnection of things around us to make our daily process more efficient by providing more comfort and productivity. However, these connections also reveal a lot of sensitive data. Therefore, thinking about the methods of information security and coding are important as the security approaches that rely heavily on coding are not a strong match for these restricted devices. Consequently, this research aims to contribute to filling this gap, which adopts machine learning techniques to enhance network-level security in the low-power devices that use the lightweight MQTT protocol for their work. This study used a set of tools tools and, through various techniques, trained the proposed system ranging from Ensemble methods to deep learning models. The system has come to know what type of attack has occurred, which helps protect IoT devices. The log loss of the Ensemble methods is 0.44, and the accuracy of multi-class classification is 98.72% after converting the table data into an image set. The work also uses a Convolution Neural Network, which has a log loss of 0.019 and an accuracy of 99.3%. It also aims to implement these functions in IDS.

scholarly journals Fine-Grained Attribute-Based Multikeyword Search for Shared Multiowner in Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yunhong Zhou ◽  
Jiehui Nan ◽  
Licheng Wang
Keyword(s):  
Internet Of Things ◽  
Keyword Search ◽  
Security Analysis ◽  
Security And Privacy ◽  
Management Service ◽  
Specific Data ◽  
Fine Grained ◽  
Secure Search ◽  
Data Owner ◽  
Iot Devices

At present, with the popularity of Internet of things (IoT), a huge number of datasets generated by IoT devices are being uploaded to the cloud storage in remote data management service, but a series of security and privacy defects also arises, where one of the best ways for preventing data disclosure is encryption. Among them, searchable encryption (SE) is considered to be a very attractive cryptographic technology, since it allows users to search records in an encrypted form and to protect user’s data on an untrusted server. For the sake of enhancing search permission, attribute-based keyword search (ABKS) is an efficient method to provide secure search queries and fine-grained access authentications over ciphertexts. However, most existing ABKS schemes concentrate on single keyword search, which usually returns redundant and irrelevant results, so it would cost some unnecessary computation and communication resources. Furthermore, existing work in the literature mostly only supports unshared multiowner where a specific data owner owns each file, which is not able to satisfy more desired expressive search. In this work, we propose a novel attribute-based multikeyword search for shared multiowner (ABMKS-SM) primitive in IoT to achieve enhanced access control for users; meanwhile, it can support multikeyword search over ciphertexts and give a formal security analysis in the adaptive against chosen keyword attack (IND-CKA) model. Finally, we have also implemented this prototype to show efficiency when compared with some previous schemes.

scholarly journals Firmware code instrumentation technology for internet of things-based services

2020 ◽  
Author(s):  
Chen Chen ◽  
Jinxin Ma ◽  
Tao Qi ◽  
Baojiang Cui ◽  
Weikong Qi ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Rapid Development ◽  
Security Analysis ◽  
Analysis Tool ◽  
Software Analysis ◽  
Dynamic Instrumentation ◽  
System Calls ◽  
Runtime Detection ◽  
Iot Devices ◽  
Runtime Information

Abstract With the rapid development of electronic and information technology, Internet of Things (IoT) devices have become extensively utilised in various fields. Increasing attention has been paid to the performance and security analysis of IoT-based services. Dynamic instrumentation is a common process in software analysis for acquiring runtime information. However, due to the limited software and hardware resources in IoT devices, most dynamic instrumentation tools do not support IoT-based services. In this paper, we provide an analysis tool, IoTDIT, to solve the current problem of runtime detection in IoT-based services. IoTDIT employs static analysis and ptrace system calls to obtain dynamic firmware information, which can aid in firmware performance analysis and security detection. We perform experiments to verify the performance and effectiveness of the proposed instrumentation tool.

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 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 A Clustering K-Anonymity Privacy-Preserving Method for Wearable IoT Devices

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Fang Liu ◽  
Tong Li
Keyword(s):  
Internet Of Things ◽  
Wearable Devices ◽  
Third Party ◽  
The Internet ◽  
Specific Data ◽  
Privacy Concerns ◽  
The Third ◽  
Massive Scale ◽  
Iot Devices ◽  
The Internet Of Things

Wearable technology is one of the greatest applications of the Internet of Things. The popularity of wearable devices has led to a massive scale of personal (user-specific) data. Generally, data holders (manufacturers) of wearable devices are willing to share these data with others to get benefits. However, significant privacy concerns would arise when sharing the data with the third party in an improper manner. In this paper, we first propose a specific threat model about the data sharing process of wearable devices’ data. Then we propose a K-anonymity method based on clustering to preserve privacy of wearable IoT devices’ data and guarantee the usability of the collected data. Experiment results demonstrate the effectiveness of the proposed method.

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