scholarly journals Towards a New Model to Secure IoT-based Smart Home Mobile Agents using Blockchain Technology

2020 ◽  
Vol 10 (2) ◽  
pp. 5441-5447
Author(s):  
B. E. Sabir ◽  
M. Youssfi ◽  
O. Bouattane ◽  
H. Allali
Keyword(s):  
Mobile Agents ◽  
Smart Home ◽  
Daily Lives ◽  
Security Issues ◽  
Blockchain Technology ◽  
Network Load ◽  
Proposed Model ◽  
Agent Migration ◽  
The Internet Of Things ◽  
Selection Of

The Internet of Things (IoT) is becoming an indispensable part of the actual Internet and continues to extend deeper into the daily lives of people, offering distributed and critical services. Mobile agents are widely used in the context of IoT and due to the possibility of transmitting their execution status from one device to another in an IoT network, they offer many advantages such as reducing network load, encapsulating protocols, exceeding network latency, etc. Also, Blockchain Technology is growing rapidly allowing for the addition of an approved security layer in many areas. Security issues related to mobile agent migration can be resolved with the use of Blockchain. This paper aims to demonstrate how Blockchain Technology can be used to secure mobile agents in the context of the IoT using Ethereum and a Smart Contract. The transactions within the Blockchain are used to detect the malevolent mobile agents that could infiltrate the IoT systems. The proposed model aims to provide a secure migration of mobile agents to ensure security and protect the IoT applications against malevolent agents. The case of a smart home with multiple applications is applied to verify the proposed solution. The model presented in this paper could be extended to a wider selection of IoT systems outside of the smart home.

scholarly journals A Proposed Heuristic Optimization Algorithm for Detecting Network Attacks

2019 ◽  
Vol 2 (4) ◽  
pp. 530
Author(s):  
Amr Hassan Yassin ◽  
Hany Hamdy Hussien
Keyword(s):  
Neural Network ◽  
Heuristic Algorithms ◽  
Feed Forward Neural Network ◽  
Data Set ◽  
Network Attacks ◽  
Security Issues ◽  
Proposed Model ◽  
Network Intrusions ◽  
Attack Patterns ◽  
Selection Of

Due to the exponential growth of E-Business and computing capabilities over the web for a pay-for-use groundwork, the risk factors regarding security issues also increase rapidly. As the usage increases, it becomes very difficult to identify malicious attacks since the attack patterns change. Therefore, host machines in the network must continually be monitored for intrusions since they are the final endpoint of any network. The purpose of this work is to introduce a generalized neural network model that has the ability to detect network intrusions. Two recent heuristic algorithms inspired by the behavior of natural phenomena, namely, the particle swarm optimization (PSO) and gravitational search (GSA) algorithms are introduced. These algorithms are combined together to train a feed forward neural network (FNN) for the purpose of utilizing the effectiveness of these algorithms to reduce the problems of getting stuck in local minima and the time-consuming convergence rate. Dimension reduction focuses on using information obtained from NSL-KDD Cup 99 data set for the selection of some features to discover the type of attacks. Detecting the network attacks and the performance of the proposed model are evaluated under different patterns of network data.

scholarly journals QUANTUM FOG CLOUD MODEL IN INTERNET OF THINGS WITH ANALYSIS OF GREEN COMPUTING

2017 ◽  
Vol 5 (1) ◽  
pp. 230-238
Author(s):  
Sayantan Gupta
Keyword(s):  
Internet Of Things ◽  
Cloud Model ◽  
Modern Society ◽  
Green Computing ◽  
Modern World ◽  
Security Issues ◽  
Proposed Model ◽  
Implementation Techniques ◽  
The Many ◽  
The Internet Of Things

The technology of Quantum Green Computing has been discussed in this paper. It also discusses the need of the many implementation techniques and approaches in relation with Fog-Cloud Computing. Moreover, we would like to introduce the latest algorithms like Stack Algorithm, Address Algorithm and many others which will help in the analysis of Green-Quantum Computing Technology in the modern society and would create a technological revolution. With the Internet of Things rising in the modern world time, new security issues have also been developed. So, our proposed Model the Fog-Things Model will help us to determine the security issues and indeed secure the entire IoT network.

A Machine Learning-Based Exploration of Relationship Between Security Vulnerabilities of IoT Devices and Manufacturers

2020 ◽  
Vol 1 (2) ◽  
pp. 1-12
Author(s):  
Ritu Chauhan ◽  
Gatha Tanwar
Keyword(s):  
Cyber Security ◽  
Automated System ◽  
Smart Devices ◽  
Protocol Stack ◽  
Security Vulnerabilities ◽  
Local Networks ◽  
Daily Lives ◽  
Security Issues ◽  
Iot Devices ◽  
The Internet Of Things

The internet of things has brought in innovations in the daily lives of users. The enthusiasm and openness of consumers have fuelled the manufacturers to dish out new devices with more features and better aesthetics. In an attempt to keep up with the competition, the manufacturers are not paying enough attention to cyber security of these smart devices. The gravity of security vulnerabilities is further aggravated due to their connected nature. As a result, a compromised device would not only stop providing the intended service but could also act as a host for malware introduced by an attacker. This study has focused on 10 manufacturers, namely Fitbit, D-Link, Edimax, Ednet, Homematic, Smarter, Osram, Belkin Wemo, Philips Hue, and Withings. The authors studied the security issues which have been raised in the past and the communication protocols used by devices made by these brands. It was found that while security vulnerabilities could be introduced due to lack of attention to details while designing an IoT device, they could also get introduced by the protocol stack and inadequate system configuration. Researchers have iterated that protocols like TCP, UDP, and mDNS have inherent security shortcomings and manufacturers need to be mindful of the fact. Furthermore, if protocols like EAPOL or Zigbee have been used, then the device developers need to be aware of safeguarding the keys and other authentication mechanisms. The authors also analysed the packets captured during setup of 23 devices by the above-mentioned manufacturers. The analysis gave insight into the underlying protocol stack preferred by the manufacturers. In addition, they also used count vectorizer to tokenize the protocols used during device setup and use them to model a multinomial classifier to identify the manufacturers. The intent of this experiment was to determine if a manufacturer could be identified based on the tokenized protocols. The modelled classifier could then be used to drive an algorithm to checklist against possible security vulnerabilities, which are characteristic of the protocols and the manufacturer history. Such an automated system will be instrumental in regular diagnostics of a smart system. The authors then wrapped up this report by suggesting some measures a user can take to protect their local networks and connected devices.

PROTECTED INTELLIGENT HOUSE SYSTEM USING INTERNET OF THINGS

2020 ◽  
pp. 218-228
Author(s):  
Volodymyr Bazylevych ◽  
◽  
Marina Maltseva ◽  
Taras Petrenko ◽  
Lesia Chernysh ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Smart Home ◽  
The Internet ◽  
Local Data ◽  
Web Interfaces ◽  
Security Issues ◽  
Advantages And Disadvantages ◽  
Software Interfaces ◽  
Smart House ◽  
The Internet Of Things

Urgency of the research. Today, the Internet of Things (IoT) is firmly entrenched in the lives of billions of people around the world. IoT is used in many areas of human activity - industry, everyday life, medicine, education, urban management and others. However, the increase in the number of connected devices leads to an increase in safety risks - from causing physical harm to humans with these devices to damage to complex technological equipment. That is why the issues of ensuring the protection of IoT systems are relevant. Target setting. Comprehensive protection of IoT systems is possible only with reliable network, software and technical protection of devices, equipment and communications of which these systems consist. Given that the above objects and methods of their protection can be combined into a separate secure system of a smart home, its development is an important theoretical and practical task of cybersecurity. Actual scientific researches and issues analysis. Today, there are many publications that analyze IoT security issues and suggest ways to solve them, but there is no work that would develop a separate model of IoT protection on the example of a smart home. Uninvestigated parts of general matters defining. Analyzing the multilevel architecture of IoT systems and features of cloud platforms of the Internet of Things, highlighting potentially vulnerable components of these complex solutions (access control system to IoT device and cloud platform; clouds, mobile applications and web interfaces of devices; software updates; device memory ; local data warehouses; hardware and software interfaces of devices; network services of devices; ecosystem of communications, including network traffic) it can be argued that building a secure system of a smart home using IoT will increase the level of security of these systems. . The research objective of this article is to build a secure system using IoT on the example of a smart home. The statement of basic materials. The basic concepts of IoT are defined, the main spheres of IoT use are investigated, the secure system of smart house with use of IoT in which the basic ways of protection of the information which is expedient to implement in networks of smart house - VPN, firewall, ACL and passwords for reliable protection is developed. The main IoT vulnerabilities and ways to eliminate them are analyzed. Different architectures of IoT systems are considered. An algorithm for setting up a secure smart home system using IoT is proposed Conclusions. The work developed a secure system using the Internet of Things on the example of a smart home. The advantages and disadvantages of using the Internet of Things are identified. It has been studied that the popularity of the Internet of Things is growing every second, so it is necessary to pay more attention to their protection. The main vulnerabilities of IoT can be considered the lack of standardization, traffic encryption, default passwords. The scheme of a secure system of a smart home using the Internet of Things built in Cisco Packet Tracer and a step-by-step algorithm for debugging its protection system using the ASA5505 firewall to filter incoming traffic were proposed. Strong passwords have been created for IoT device accounts. WPA2 / 3-PSK wireless protocols using the AES algorithm ensure the security of wireless data transmission. The home controller has a unique SSID. The created system can be implemented and safely used in homes and offices.

scholarly journals Enhancement of Security and Handling the Inconspicuousness in IoT Using a Simple Size Extensible Blockchain

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1795 ◽  
Author(s):  
B. Saravana Balaji ◽  
P. Vishnu Raja ◽  
Anand Nayyar ◽  
P. Sanjeevikumar ◽  
Sanjeevi Pandiyan
Keyword(s):  
Smart Home ◽  
Feasible Solution ◽  
Optimal Solution ◽  
The Other ◽  
Extraction Operation ◽  
Distributed Environment ◽  
Blockchain Technology ◽  
Shared Time ◽  
Novel Algorithms ◽  
The Internet Of Things

Blockchain technology is increasingly used worldwide to enhance the performance and profit of any environment through its defining characteristics, such as security, auditability, immutability, and inconspicuousness. Owing to these characteristics, the blockchain can be used in various non-financial operations of some domains, such as the Internet of Things (IoT) and distributed computing. However, implementing blockchain technology in IoT is not always a feasible solution because blockchain deployment is costly, it has limited extensibility and provides irregular bandwidth and latency. In this regard, a simple size extensible (SSE) blockchain has been proposed to provide an optimal solution for IoT environments by satisfying the needs of the IoT environment as well as ensuring end-to-end security. The implementation of the proposed blockchain develops an overlay network to obtain a distributed environment where the blockchain is handled by the resources present therein. Two novel algorithms were introduced into the proposed system to minimize the irregularity and latency on one hand, and to maximize the throughput of the system on the other. The shared-time depending agreement algorithm (STD) minimizes the irregularity in the extraction operation and latency. The other, the shared throughput administration algorithm (STA) justifies the overall collection of the transmission load in the network and maintains the performance of the blockchain. The proposed system was applied to smart home IoT appliances to test the performance of the proposed system. The experimental results show that the proposed blockchain system minimizes nearly 70% of the data irregularity, latency, and furthermore, 30% of the blockchain extensibility is maximized as compared to the existing systems.

A Security Strategy of Mobile Agent System

2013 ◽  
Vol 336-338 ◽  
pp. 2401-2405
Author(s):  
Ying Li ◽  
Bao Fang Hu ◽  
Chen Lin Wei
Keyword(s):  
Mobile Agent ◽  
Mobile Agents ◽  
Third Party ◽  
Digital Certificate ◽  
Security Strategy ◽  
Agent System ◽  
Security Issues ◽  
The Third ◽  
The Third Party ◽  
Agent Migration

The paper aims at the security issues of the mobile agent system to propose a mobile agent system based on tracking mechanism which has a third-party certification center similar to an authority sector, whose hosts and mobile agents in mobile agent system are required to be registered in the third-party certification center so as to obtain a digital certificate issued by the third-party certification center. Each server launching mobile agent has a static communication agent Tracker, responsible for maintaining the context information launched by the mobile agent and agent migration thereby solving problems in the labyrinth and authentication of mobile agent in traditional mobile agent system so that the existing mobile agent system can become more secure and reliable.

scholarly journals A conceptual model to support security analysis in the internet of things

2017 ◽  
Vol 14 (2) ◽  
pp. 557-578 ◽  
Author(s):  
Orestis Mavropoulos ◽  
Haralambos Mouratidis ◽  
Andrew Fish ◽  
Emmanouil Panaousis ◽  
Christos Kalloniatis
Keyword(s):  
Internet Of Things ◽  
Conceptual Model ◽  
Smart Home ◽  
Security Analysis ◽  
Decision Makers ◽  
Small Scale ◽  
Security Issues ◽  
The World ◽  
Main Driver ◽  
The Internet Of Things

This paper proposes a conceptual model to support decision makers during security analysis of Internet of Things (IoT) systems. The world is entering an era of ubiquitous computing with IoT being the main driver. Taking into account the scale of IoT, the number of security issues that are arising are unprecedented. Both academia and industry require methodologies that will enable reasoning about security in IoT system in a concise and holistic manner. The proposed conceptual model addresses a number of challenges in modeling IoT to support security analysis. The model is based on an architecture-oriented approach that incorporates sociotechnical concepts into the security analysis of an IoT system. To demonstrate the usage of the proposed conceptual model, we perform a security analysis on a small scale smart home example.

IoT-Fog-Cloud Centric Earthquake Monitoring and Prediction

2021 ◽  
Vol 20 (6) ◽  
pp. 1-26
Author(s):  
Kanika Saini ◽  
Sheetal Kalra ◽  
Sandeep K. Sood
Keyword(s):  
Real Time ◽  
Seismic Signal ◽  
Sensor Layer ◽  
Natural Catastrophes ◽  
Specificity And Sensitivity ◽  
Proposed Model ◽  
Earthquake Monitoring ◽  
Artificial Neural Network Ann ◽  
The Internet Of Things ◽  
Selection Of

Earthquakes are among the most inevitable natural catastrophes. The uncertainty about the severity of the earthquake has a profound effect on the burden of disaster and causes massive economic and societal losses. Although unpredictable, it can be expected to ameliorate damage and fatalities, such as monitoring and predicting earthquakes using the Internet of Things (IoT). With the resurgence of the IoT, an emerging innovative approach is to integrate IoT technology with Fog and Cloud Computing to augment the effectiveness and accuracy of earthquake monitoring and prediction. In this study, the integrated IoT-Fog-Cloud layered framework is proposed to predict earthquakes using seismic signal information. The proposed model is composed of three layers: (i) at sensor layer, seismic data are acquired, (ii) fog layer incorporates pre-processing, feature extraction using fast Walsh–Hadamard transform (FWHT), selection of relevant features by applying High Order Spectral Analysis (HOSA) to FWHT coefficients, and seismic event classification by K-means accompanied by real-time alert generation, (iii) at cloud layer, an artificial neural network (ANN) is employed to forecast the magnitude of an earthquake. For performance evaluation, K-means classification algorithm is collated with other well-known classification algorithms from the perspective of accuracy and execution duration. Implementation statistics indicate that with chosen HOS features, we have been able to attain high accuracy, precision, specificity, and sensitivity values of 93.30%, 96.65%, 90.54%, and 92.75%, respectively. In addition, the ANN provides an average correct magnitude prediction of 75%. The findings ensured that the proposed framework has the potency to classify seismic signals and predict earthquakes and could therefore further enhance the detection of seismic activities. Moreover, the generation of real-time alerts further amplifies the effectiveness of the proposed model and makes it more real-time compatible.

Concept of Blockchain Technology and Its Emergence

2021 ◽  
pp. 1-20
Author(s):  
Padmavathi U. ◽  
Narendran Rajagopalan
Keyword(s):  
Internet Of Things ◽  
Educational Institutions ◽  
The Internet ◽  
Disruptive Technology ◽  
Smart Contracts ◽  
Security Issues ◽  
Blockchain Technology ◽  
Distributed Ledger ◽  
Authentication And Authorization ◽  
The Internet Of Things

Blockchain refers to a distributed ledger technology that helps people to regulate and manage their information without any intermediaries. This technology emerges as a promising panacea for authentication and authorization with potential for use in every possible domain including financial, manufacturing, educational institutions, etc. Blockchain has its birth through the concept of Bitcoin, a digital cryptocurrency by Satoshi Nakamoto, called as Blockchain 1.0. Blockchain 2.0 came into existence in 2014 with Ethereum and smart contracts. The challenges such as scalability, interoperability, sustainability, and governance led to the next generation of Blockchain also called as IOTA, a blockchainless cryptocurrency for the internet of things runs on the top of their own ledger called Tangle, which is immune towards quantum computers. This disruptive technology evolved to provide cross chain support and more security through Blockchain 4.0. Finally, the chapter concludes by discussing the various applications of this technology and its advantages and security issues.

scholarly journals A Cross-Chain Solution to Integrating Multiple Blockchains for IoT Data Management

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2042 ◽  
Author(s):  
Yiming Jiang ◽  
Chenxu Wang ◽  
Yawei Wang ◽  
Lang Gao
Keyword(s):  
Data Management ◽  
Rapid Development ◽  
The Internet ◽  
Privacy And Security ◽  
Security Issues ◽  
High Resource ◽  
Proposed Model ◽  
Effectiveness And Efficiency ◽  
Iot Devices ◽  
The Internet Of Things

With the rapid development of the internet of things (IoT), traditional industries are setting off a massive wave of digitization. In the era of the Internet of Everything, millions of devices and links in IoT pose more significant challenges to data management. Most existing solutions employ centralized systems to control IoT devices, which brings about the privacy and security issues in IoT data management. Recently, blockchain has attracted much attention in the field of IoT due to its decentralization, traceability, and non-tamperability. However, it is non-trivial to apply the current blockchain techniques to IoT due to the lack of scalability and high resource costs. Different blockchain platforms have their particular advantages in the scenario of IoT data management. In this paper, we propose a cross-chain framework to integrate multiple blockchains for efficient and secure IoT data management. Our solution builds an interactive decentralized access model which employs a consortium blockchain as the control station. Other blockchain platforms customized for specific IoT scenarios run as the backbone of all IoT devices. It is equivalent to opening the off-chain channels on the consortium blockchain. Our model merges transactions in these channels for confirmation based on the notary mechanism. Finally, we implement a prototype of the proposed model based on hyperledge Fabric and IOTA Tangle. We evaluate the performance of our method through extensive experiments. The results demonstrate the effectiveness and efficiency of our framework.

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