scholarly journals DARE: A decentralized association rules extraction scheme for embedded data sets in distributed IoT devices

2020 ◽  
Vol 16 (10) ◽  
pp. 155014772096299
Author(s):  
Márcio Alencar ◽  
Raimundo Barreto ◽  
Horácio Fernandes ◽  
Eduardo Souto ◽  
Richard Pazzi
Keyword(s):  
Smart Home ◽  
Single Point ◽  
Data Sets ◽  
Data Memory ◽  
Usage Patterns ◽  
Extraction Scheme ◽  
Hypertext Transfer Protocol ◽  
Iot Devices ◽  
Rules Extraction ◽  
Associative Analysis

In the context of smart home, it is very important to identify usage patterns of Internet of things (IoT) devices. Finding these patterns and using them for decision-making can provide ease, comfort, practicality, and autonomy when executing daily activities. Performing knowledge extraction in a decentralized approach is a computational challenge considering the tight storage and processing constraints of IoT devices, unlike deep learning, which demands a massive amount of data, memory, and processing capability. This article describes a method for mining implicit correlations among the actions of IoT devices through embedded associative analysis. Based on support, confidence, and lift metrics, our proposed method identifies the most relevant correlations between a pair of actions of different IoT devices and suggests the integration between them through hypertext transfer protocol requests. We have compared our proposed method with a centralized method. Experimental results show that the most relevant rules for both methods are the same in 99.75% of cases. Moreover, our proposed method was able to identify relevant correlations that were not identified by the centralized one. Thus, we show that associative analysis of IoT device state change is efficient to provide an intelligent and highly integrated IoT platform while avoiding the single point of failure problem.

scholarly journals Secure Access Control to IoT Devices using Blockchain

2019 ◽  
Vol 8 (2) ◽  
pp. 3064-3070 ◽  
Keyword(s):  
Smart Home ◽  
Single Point ◽  
Qualitative Evaluation ◽  
Peer Networks ◽  
Privacy And Security ◽  
Proposed Model ◽  
Peer To Peer Networks ◽  
Iot Devices ◽  
Two Parameters

Internet of Things (IoT) is growing at an exponential rate but the area of privacy and security in IoT still remains unexplored. The existing algorithms or methods are mainly centralized and hence they are vulnerable due to their single point authentication topology. As it has been estimated that by 2020 there will be more ‘things’ than people on this earth the problem of security becomes a major concern in IoT networks, as a person having control to an IoT network will be able to control a large portion of an organization. Blockchain has recently been used to provide security to peer-to-peer networks. Blockchains are computationally expensive, heavyweight and are considered unsuitable for IoT architecture. In this paper a new lightweight and secure architecture for IoT by using Ethereum Blockchain retaining most of its security providing powers is proposed. Since Blockchain is decentralized it solves the single point authentication problem existing in IoT networks. A Smart Home System as a representative case study has been implemented for broader IoT applications. The two parameters measured are temperature and intrusion detection. The proposed model tackles some more challenges that exist in IoT networks. The Qualitative evaluation of the proposed architecture highlights how it tackles various attacks.

scholarly journals IoT Traffic: Modeling and Measurement Experiments

IoT ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 140-162
Author(s):  
Hung Nguyen-An ◽  
Thomas Silverston ◽  
Taku Yamazaki ◽  
Takumi Miyoshi
Keyword(s):  
Smart Home ◽  
Large Scale ◽  
Traffic Modeling ◽  
The Novel ◽  
Network Behavior ◽  
Performance Accuracy ◽  
Traffic Generator ◽  
Multiple Devices ◽  
Iot Devices ◽  
The Internet Of Things

We now use the Internet of things (IoT) in our everyday lives. The novel IoT devices collect cyber–physical data and provide information on the environment. Hence, IoT traffic will count for a major part of Internet traffic; however, its impact on the network is still widely unknown. IoT devices are prone to cyberattacks because of constrained resources or misconfigurations. It is essential to characterize IoT traffic and identify each device to monitor the IoT network and discriminate among legitimate and anomalous IoT traffic. In this study, we deployed a smart-home testbed comprising several IoT devices to study IoT traffic. We performed extensive measurement experiments using a novel IoT traffic generator tool called IoTTGen. This tool can generate traffic from multiple devices, emulating large-scale scenarios with different devices under different network conditions. We analyzed the IoT traffic properties by computing the entropy value of traffic parameters and visually observing the traffic on behavior shape graphs. We propose a new method for identifying traffic entropy-based devices, computing the entropy values of traffic features. The method relies on machine learning to classify the traffic. The proposed method succeeded in identifying devices with a performance accuracy up to 94% and is robust with unpredictable network behavior with traffic anomalies spreading in the network.

scholarly journals A Secure and Scalable Smart Home Gateway to Bridge Technology Fragmentation

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3587
Author(s):  
Ezequiel Simeoni ◽  
Eugenio Gaeta ◽  
Rebeca I. García-Betances ◽  
Dave Raggett ◽  
Alejandro M. Medrano-Gil ◽  
...  
Keyword(s):  
Smart Home ◽  
Home Automation ◽  
Dynamic Configuration ◽  
Home Gateway ◽  
Security Authentication ◽  
Living Lab ◽  
Automation Systems ◽  
Authentication And Authorization ◽  
Iot Devices ◽  
Bridge Technology

Internet of Things (IoT) technologies are already playing an important role in our daily activities as we use them and rely on them to increase our abilities, connectivity, productivity and quality of life. However, there are still obstacles to achieving a unique interface able to transfer full control to users given the diversity of protocols, properties and specifications in the varied IoT ecosystem. Particularly for the case of home automation systems, there is a high degree of fragmentation that limits interoperability, increasing the complexity and costs of developments and holding back their real potential of positively impacting users. In this article, we propose implementing W3C’s Web of Things Standard supported by home automation ontologies, such as SAREF and UniversAAL, to deploy the Living Lab Gateway that allows users to consume all IoT devices from a smart home, including those physically wired and using KNX® technology. This work, developed under the framework of the EC funded Plan4Act project, includes relevant features such as security, authentication and authorization provision, dynamic configuration and injection of devices, and devices abstraction and mapping into ontologies. Its deployment is explained in two scenarios to show the achieved technology’s degree of integration, the code simplicity for developers and the system’s scalability: one consisted of external hardware interfacing with the smart home, and the other of the injection of a new sensing device. A test was executed providing metrics that indicate that the Living Lab Gateway is competitive in terms of response performance.

HomeTec Software for Security Aspects of Smart Home Devices Based on IoT

2021 ◽  
pp. 5-16
Author(s):  
Parth Rustagi ◽  
◽  
◽  
◽  
◽  
...  
Keyword(s):  
Smart Home ◽  
Denial Of Service ◽  
Security Protocols ◽  
The Internet ◽  
Security Threats ◽  
Deep Dive ◽  
Cost Cutting ◽  
Full Control ◽  
Iot Devices ◽  
Service Data

As useful as it gets to connect devices to the internet to make life easier and more comfortable, it also opens the gates to various cyber threats. The connection of Smart Home devices to the internet makes them vulnerable to malicious hackers that infiltrate the system. Hackers can penetrate these systems and have full control over devices. This can lead to denial of service, data leakage, invasion of privacy, etc. Thus security is a major aspect of Smart home devices. However, many companies manufacturing these Smart Home devices have little to no security protocols in their devices. In the process of making the IoT devices cheaper, various cost-cutting is done on the security protocols in IoT devices. In some way, many manufactures of the devices don’t even consider this as a factor to build upon. This leaves the devices vulnerable to attacks. Various authorities have worked upon to standardize the security aspects for the IoT and listed out guidelines for manufactures to follow, but many fail to abide by them. This paper introduces and talks about the various threats, various Security threats to Smart Home devices. It takes a deep dive into the solutions for the discussed threats. It also discusses their prevention. Lastly, it discusses various preventive measures and good practices to be incorporated to protect devices from any future attacks.

scholarly journals Device-Based Security to Improve User Privacy in the Internet of Things †

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2664 ◽  
Author(s):  
Luis Belem Pacheco ◽  
Eduardo Pelinson Alchieri ◽  
Priscila Mendez Barreto
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Single Point ◽  
Data Access ◽  
Cloud Services ◽  
Sensitive Information ◽  
User Privacy ◽  
Privacy And Security ◽  
Iot Devices ◽  
And Control

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.

Towards Combining Digitization Techniques in the Generation of Reverse Engineering Data Sets

1999 ◽  
Author(s):  
C. J. Rolls ◽  
W. ElMaraghy ◽  
H. ElMaraghy
Keyword(s):  
Reverse Engineering ◽  
Computer Aided Design ◽  
Laser Scanning ◽  
Single Point ◽  
Laser Scanner ◽  
Coordinate Measuring Machine ◽  
Industrial Applications ◽  
Data Sets ◽  
Error Characterization ◽  
Measuring Machine

Abstract Reverse engineering (RE), may be defined as the process of generating computer aided design models (CAD) from existing or prototype parts. The process has been used for many years in industry. It has markedly increased in implementation in the past few years, primarily due to the introduction of rapid part digitization technologies. Current industrial applications include CAD model construction from artisan geometry, such as in automotive body styling, the generation of custom fits to human surfaces, and quality control. This paper summarizes the principles of operation behind many commercially available part digitization technologies, and discusses techniques involved in part digitization using a coordinate measuring machine (CMM) and laser scanner. An overall error characterization of the laser scanning digitization process is presented for a particular scanner. This is followed by a discussion of the merits and considerations involved in generating combined data sets with characteristics indicative of the design intent of specific part features. Issues in facilitating the assembly, or registration, of the different types of data into a single point set are discussed.

scholarly journals Towards Secure and Privacy-Preserving IoT Enabled Smart Home: Architecture and Experimental Study

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6131
Author(s):  
Mamun Abu-Tair ◽  
Soufiene Djahel ◽  
Philip Perry ◽  
Bryan Scotney ◽  
Unsub Zia ◽  
...  
Keyword(s):  
Experimental Study ◽  
Smart Home ◽  
Privacy Preservation ◽  
Smart Cities ◽  
Security And Privacy ◽  
Test Cases ◽  
Security Threats ◽  
Hardware Implementations ◽  
Cryptographic Algorithms ◽  
Iot Devices

Internet of Things (IoT) technology is increasingly pervasive in all aspects of our life and its usage is anticipated to significantly increase in future Smart Cities to support their myriad of revolutionary applications. This paper introduces a new architecture that can support several IoT-enabled smart home use cases, with a specified level of security and privacy preservation. The security threats that may target such an architecture are highlighted along with the cryptographic algorithms that can prevent them. An experimental study is performed to provide more insights about the suitability of several lightweight cryptographic algorithms for use in securing the constrained IoT devices used in the proposed architecture. The obtained results showed that many modern lightweight symmetric cryptography algorithms, as CLEFIA and TRIVIUM, are optimized for hardware implementations and can consume up to 10 times more energy than the legacy techniques when they are implemented in software. Moreover, the experiments results highlight that CLEFIA significantly outperforms TRIVIUM under all of the investigated test cases, and the latter performs 100 times worse than the legacy cryptographic algorithms tested.

scholarly journals A Node Embedding-Based Influential Spreaders Identification Approach

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1554
Author(s):  
Dongming Chen ◽  
Panpan Du ◽  
Bo Fang ◽  
Dongqi Wang ◽  
Xinyu Huang
Keyword(s):  
Social Influence ◽  
Vector Space ◽  
Single Point ◽  
Point Contact ◽  
Representation Learning ◽  
Influence Maximization ◽  
Maximization Problem ◽  
Data Sets ◽  
Full Contact ◽  
The Social

Node embedding is a representation learning technique that maps network nodes into lower-dimensional vector space. Embedding nodes into vector space can benefit network analysis tasks, such as community detection, link prediction, and influential node identification, in both calculation and richer application scope. In this paper, we propose a two-step node embedding-based solution for the social influence maximization problem (IMP). The solution employs a revised network-embedding algorithm to map input nodes into vector space in the first step. In the second step, the solution clusters the vector space nodes into subgroups and chooses the subgroups’ centers to be the influential spreaders. The proposed approach is a simple but effective IMP solution because it takes both the social reinforcement and homophily characteristics of the social network into consideration in node embedding and seed spreaders selection operation separately. The information propagation simulation experiment of single-point contact susceptible-infected-recovered (SIR) and full-contact SIR models on six different types of real network data sets proved that the proposed social influence maximization (SIM) solution exhibits significant propagation capability.

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