scholarly journals Recognition of the Cybersecurity State of IoT devices

TEM Journal ◽  
2021 ◽  
pp. 1912-1918
Author(s):  
M.E. Sukhoparov ◽  
I.S. Lebedev
Keyword(s):  
Time Series ◽  
Internet Of Things ◽  
Processing Time ◽  
External Information ◽  
Classification Methods ◽  
Internal Resources ◽  
Software And Hardware ◽  
Mass Development ◽  
Process Execution ◽  
Iot Devices

The identification of the cybersecurity (CS) state of Internet of things (IoT) devices determines the necessity to search for and improve approaches to detecting various threat types. The unification used in the mass development of IoT devices facilitates software and hardware modification to block certain built-in protective functions from the side of a potential intruder. A need arises to develop universal methods for identifying the cybersecurity state of devices using comprehensive approaches to analyzing data from internal and external information channels. The article presents an approach to identifying the cybersecurity of IoT devices based on processing time series recorded from sensors during various processes, and internal and external (thirdparty) sources. The approach is based on classification methods. The presented solution uses template sequences containing synchronized time series showing numerical values obtained from various probes and sensors during process execution. The proposed approach makes it possible to identify IoT device cybersecurity states without increasing the volume of information stored and processed in internal resources.

scholarly journals STATE ANALYSIS INTERNET OF THINGS DEVICES BASED ON BAGGING

T-Comm ◽  
2020 ◽  
Vol 14 (12) ◽  
pp. 45-50
Author(s):  
Mikhail E. Sukhoparov ◽  
◽  
Ilya S. Lebedev ◽  
Keyword(s):  
Time Series ◽  
Internet Of Things ◽  
The State ◽  
Point Of View ◽  
Operating Conditions ◽  
Process Time ◽  
K Nearest Neighbors ◽  
Computational Point ◽  
Iot Devices ◽  
The Internet Of Things

The development of IoT concept makes it necessary to search and improve models and methods for analyzing the state of remote autonomous devices. Due to the fact that some devices are located outside the controlled area, it becomes necessary to develop universal models and methods for identifying the state of low-power devices from a computational point of view, using complex approaches to analyzing data coming from various information channels. The article discusses an approach to identifying IoT devices state, based on parallel functioning classifiers that process time series received from elements in various states and modes of operation. The aim of the work is to develop an approach for identifying the state of IoT devices based on time series recorded during the execution of various processes. The proposed solution is based on methods of parallel classification and statistical analysis, requires an initial labeled sample. The use of several classifiers that give an answer "independently" from each other makes it possible to average the error by "collective" voting. The developed approach is tested on a sequence of classifying algorithms, to the input of which the time series obtained experimentally under various operating conditions were fed. Results are presented for a naive Bayesian classifier, decision trees, discriminant analysis, and the k nearest neighbors method. The use of a sequence of classification algorithms operating in parallel allows scaling by adding new classifiers without losing processing speed. The method makes it possible to identify the state of the Internet of Things device with relatively small requirements for computing resources, ease of implementation, and scalability by adding new classifying algorithms.

scholarly journals Virtualization Based Efficient Service Matching and Discovery in Internet of Things

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1007
Author(s):  
Zulfiqar Ali Khan ◽  
Israr Ullah ◽  
Muhammad Ibrahim ◽  
Muhammad Fayaz ◽  
Ayman Aljarbouh ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Service Discovery ◽  
Processing Time ◽  
Service Selection ◽  
Geographic Area ◽  
Residual Energy ◽  
Service Matching ◽  
Domain Specific ◽  
Proposed Model ◽  
Iot Devices

Internet of Things (IoT) is getting more popular day by day, which triggers its adoption for solving domain specific problems. Cities are becoming smart by gathering the context knowledge through sensors and controlling specific parameters through actuators. Dynamically discovering and integrating different data streams from different sensors is a major challenge these days. In this paper, a service matchmaking algorithm is presented for service discovery utilizing IoT devices and services in a particular geographic area. It helps us to identify services based on a variety of parameters (location, query size and processing time, etc.). Customization of service selection and discovery are also explored. The conceptual framework is provided for the proposed model along with a matchmaking algorithm based on IoT devices virtualization. The simulation results elaborate the increased complexity of processing time with respect to the increasing pool of available services. The average processing time varies as the number of conditions are multiplied. Query size and complexity increases with additional number of filters and conditions which results in the reduction of the number of matching services. Moreover, upon decreasing the radius of geographic search area, the number of candidate services decreases for service matching algorithm. This is based on the assumption that IoT devices and services are evenly distributed in a given geographic area. Similarly, the remaining energy of IoT devices is also assumed to be uniformly distributed and, therefore, if we are interested in IoT devices or services with more residual energy, then a limited number of IoT devices or services will fulfill this criterion.

Goal-Based Semantic Queries for Dynamic Processes in the Internet of Things

2016 ◽  
Vol 10 (02) ◽  
pp. 269-293 ◽  
Author(s):  
Steffen Huber ◽  
Ronny Seiger ◽  
André Kühnert ◽  
Vasileios Theodorou ◽  
Thomas Schlegel
Keyword(s):  
Internet Of Things ◽  
Domain Knowledge ◽  
Service Discovery ◽  
Modeling Languages ◽  
Goal Modeling ◽  
Modeling Methodology ◽  
Novel Approach ◽  
Process Execution ◽  
Process Engine ◽  
Iot Devices

Internet of Things-aware process execution imposes new requirements on process modeling that are outside the scope of current modeling languages. Internet of Things (IoT) devices may vanish, appear or stay unknown during process execution, which renders process resource allocation at design time infeasible. Devices’ capabilities are often only available in a particular real-world context at runtime. This is not considered by current approaches that use services for encapsulating device functionality. We propose a novel approach to enable both service discovery and invocation for IoT-aware processes based on users’ goals that are defined as part of a process. We apply the Tropos goal modeling methodology to represent the dependencies between these goals and IoT device capabilities. Furthermore, we present a Semantic Access Layer (SAL) to transform these goals into service invocations using generated SPARQL queries. The SAL executes the queries on a knowledge base representing runtime domain knowledge about IoT services, their capabilities, and context. As a result, it invokes the identified IoT services and transfers the responses back to the process engine. The evaluation of our approach within several Smart Home scenarios shows an increase of flexibility and separation of concerns for scalable, IoT-aware process execution.

scholarly journals Internet of Things (IoT)-Enabled Elderly Fall Verification, Exploiting Temporal Inference Models in Smart Homes

2020 ◽  
Vol 17 (2) ◽  
pp. 408 ◽  
Author(s):  
Grigorios Kyriakopoulos ◽  
Stamatios Ntanos ◽  
Theodoros Anagnostopoulos ◽  
Nikolaos Tsotsolas ◽  
Ioannis Salmon ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Synthetic Data ◽  
Smart Homes ◽  
The Elderly ◽  
Classification Methods ◽  
Inference Models ◽  
Fall Incident ◽  
Temporal Inference ◽  
Iot Devices ◽  
Serious Injuries

Everyday life of the elderly and impaired population living in smart homes is challenging because of possible accidents that may occur due to daily activities. In such activities, persons often lean over (to reach something) and, if they not cautious, are prone to falling. To identify fall incidents, which could stochastically cause serious injuries or even death, we propose specific temporal inference models; namely, CM-I and CM-II. These models can infer a fall incident based on classification methods by exploiting wearable Internet of Things (IoT) altimeter sensors adopted by seniors. We analyzed real and synthetic data of fall and lean over incidents to test the proposed models. The results are promising for incorporating such inference models to assist healthcare for fall verification of seniors in smart homes. Specifically, the CM-II model achieved a prediction accuracy of 0.98, which is the highest accuracy when compared to other models in the literature under the McNemar’s test criterion. These models could be incorporated in wearable IoT devices to provide early warning and prediction of fall incidents to clinical doctors.

scholarly journals A Comprehensive Addressing and Erudition on Blockchain in IOT Fortification

2021 ◽  
pp. 233-237
Author(s):  
R. Priyadharsini
Keyword(s):  
Internet Of Things ◽  
Key Management ◽  
Iot Security ◽  
Blockchain Technology ◽  
Software And Hardware ◽  
Iot Devices ◽  
Security Of Iot

Blockchain is the technology that provides security through its cryptography. IOT (Internet of Things) enhances the usage of software and hardware power in efficient way. The IOT Devices can be configured and controlled by blockchain. In this, the analysis of blockchain in IOT Security presented. The Key management is one of the biggest features for blockchain to be successful in the technology. As security is essential for any technology to be successful, the importance is considered and revealed about the security of IOT through blockchain technology. The features and considerations made would be useful for further research on blockchain in IOT Security.

scholarly journals Suitability Of Influxdb Database For Iot Applications

2019 ◽  
Vol 8 (10) ◽  
pp. 1850-1857 ◽  
Keyword(s):  
Time Series ◽  
Internet Of Things ◽  
Relational Databases ◽  
User Experiences ◽  
Business Decisions ◽  
Nosql Databases ◽  
Iot Applications ◽  
The Creation ◽  
Iot Devices

Large amounts of data are generated every moment by connected objects creating Internet of Things (IoT). IoT isn’t about things; it’s about the data those things create and collect. Organizations rely on this data to provide better user experiences, to make smarter business decisions, and ultimately fuel their growth. However, none of this is possible without a reliable database that is able to handle the massive amounts of data generated by IoT devices. Relational databases are known for being flexible, easy to work with, and mature but they aren’t particularly known for is scale, which prompted the creation of NoSQL databases. Another thing to note is that IoT data is time-series in nature. In this paper we are discussed and compare about top five time-series database like InfluxDB, Kdb+, Graphite, Prometheus and RRDtool.

scholarly journals STATE ANALYSIS INTERNET OF THINGS DEVICES BASED ON BAGGING

T-Comm ◽  
2021 ◽  
Vol 15 (4) ◽  
pp. 21-27
Author(s):  
Mikhail E. Sukhoparov ◽  
◽  
Ilya S. Lebedev ◽  
Keyword(s):  
Time Series ◽  
Internet Of Things ◽  
The State ◽  
Point Of View ◽  
Operating Conditions ◽  
Process Time ◽  
K Nearest Neighbors ◽  
Computational Point ◽  
Iot Devices ◽  
The Internet Of Things

The development of IoT concept makes it necessary to search and improve models and methods for analyzing the state of remote autonomous devices. Due to the fact that some devices are located outside the controlled area, it becomes necessary to develop universal models and methods for identifying the state of low-power devices from a computational point of view, using complex approaches to analyzing data coming from various information channels. The article discusses an approach to identifying IoT devices state, based on parallel functioning classifiers that process time series received from elements in various states and modes of operation. The aim of the work is to develop an approach for identifying the state of IoT devices based on time series recorded during the execution of various processes. The proposed solution is based on methods of parallel classification and statistical analysis, requires an initial labeled sample. The use of several classifiers that give an answer “independently” from each other makes it possible to average the error by “collective” voting. The developed approach is tested on a sequence of classifying algorithms, to the input of which the time series obtained experimentally under various operating conditions were fed. Results are presented for a naive Bayesian classifier, decision trees, discriminant analysis, and the k nearest neighbors method. The use of a sequence of classification algorithms operating in parallel allows scaling by adding new classifiers without losing processing speed. The method makes it possible to identify the state of the Internet of Things device with relatively small requirements for computing resources, ease of implementation, and scalability by adding new classifying algorithms.

Bringing Security to The Smallest Embedded Systems

2017 ◽  
Author(s):  
JOSEPH YIU
Keyword(s):  
Internet Of Things ◽  
Embedded Systems ◽  
Low Cost ◽  
Security Requirements ◽  
The Internet ◽  
Security Measures ◽  
Significant Challenge ◽  
Iot Devices

The increasing need for security in microcontrollers Security has long been a significant challenge in microcontroller applications(MCUs). Traditionally, many microcontroller systems did not have strong security measures against remote attacks as most of them are not connected to the Internet, and many microcontrollers are deemed to be cheap and simple. With the growth of IoT (Internet of Things), security in low cost microcontrollers moved toward the spotlight and the security requirements of these IoT devices are now just as critical as high-end systems due to:

Agricultural Application of Web of Things Architecture

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 61-63 ◽  
Author(s):  
Akihiro Fujii
Keyword(s):  
Internet Of Things ◽  
Agricultural Sector ◽  
Electronic Device ◽  
Specific Work ◽  
Science And Engineering ◽  
Unique Identifier ◽  
Agricultural Application ◽  
Iot Devices ◽  
The Internet Of Things ◽  
Type Pressure

The Internet of Things (IoT) is a term that describes a system of computing devices, digital machines, objects, animals or people that are interrelated. Each of the interrelated 'things' are given a unique identifier and the ability to transfer data over a network that does not require human-to-human or human-to-computer interaction. Examples of IoT in practice include a human with a heart monitor implant, an animal with a biochip transponder (an electronic device inserted under the skin that gives the animal a unique identification number) and a car that has built-in sensors which can alert the driver about any problems, such as when the type pressure is low. The concept of a network of devices was established as early as 1982, although the term 'Internet of Things' was almost certainly first coined by Kevin Ashton in 1999. Since then, IoT devices have become ubiquitous, certainly in some parts of the world. Although there have been significant developments in the technology associated with IoT, the concept is far from being fully realised. Indeed, the potential for the reach of IoT extends to areas which some would find surprising. Researchers at the Faculty of Science and Engineering, Hosei University in Japan, are exploring using IoT in the agricultural sector, with some specific work on the production of melons. For the advancement of IoT in agriculture, difficult and important issues are implementation of subtle activities into computers procedure. The researchers challenges are going on.

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