Internet Of Things Mechanisms Research Articles

Multi-dimension-precision chaotic encryption mechanism for Internet of Things

The massive amount of information processed in the Internet of Things(IoT) environment requires effective encryption schemes to ensure secure transmission. However, traditional encryption methods such as Elliptic Curve Cryptography (ECC) or Data Encryption Standard (DES) are not suitable for IoT environments where large amounts of data need to be quickly encrypted. In this paper, a multi-precision encryption mechanism based on multi-dimensional chaotic system is proposed. Firstly, the proposed scheme uses floating-point, 32-bit, 24-bit, and 16-bit data accuracy respectively, which can effectively reduce the complexity through fixed-point calculation. Secondly, aiming at the problem that traditional chaotic dynamic analysis methods such as the Lyapunov index cannot be applied, an analysis scheme based on complexity measure is proposed. Finally, a free dimension encryption mechanism based on Logistic, Tent, and PWLCM is proposed. By adding random disturbance to a one-dimensional chaotic map, the weak randomness of the single chaotic sequence is overcome effectively. Finally, the security analysis of the encryption scheme is carried out, and the result proves that the scheme can effectively resist the common attack means. In the 3D chaotic system, the encryption effect of 24-bit data accuracy is close to floating point accuracy, which is suitable for the IoT environment with large data volume, high encryption efficiency, and vulnerability.

An Efficient and Secure Communication Mechanism for Internet of Things Based Connected Devices

An Efficient and Secure Communication Mechanism for Internet of Things Based Connected Devices

A multi‐device user authentication mechanism for Internet of Things

AbstractThe advent of the Internet of Things (IoT) enables different customized services to ease the day‐to‐day life activities of users by utilizing information attained through the internet connectivity of low‐powered sensing devices. Due to device diversity and resource constraints of participating devices, IoT is vulnerable to security attacks. Consequently, authentication is the fundamental measure for using IoT services in the context of network security. IoT devices’ resource captivity makes designing robust and secure authentication mechanisms challenging. Besides, existing user authentication mechanisms are designed assuming a user always accesses an IoT environment using a particular device. However, nowadays, most users employ multiple devices to access the internet; subsequently, it needs an authentication mechanism to handle this diversity. This paper addresses this limitation and proposes a new One‐Time Password (OTP)‐based user authentication scheme supporting user access from multiple devices in an IoT environment. We verify the proposed scheme using widely used BAN logic, AVISPA tool, and informal security analysis, guaranteeing that our scheme preserves the necessary security features. Comparative performance analysis shows that our scheme achieves comparable computation, storage, and communication costs concerning existing works. Moreover, simulation results demonstrate that the proposed method also sustains satisfactory network performance.

FogTrust: Fog-Integrated Multi-Leveled Trust Management Mechanism for Internet of Things

The Internet of Things (IoT) is widely used to reduce human dependence. It is a network of interconnected smart devices with internet connectivity that can send and receive data. However, the rapid growth of IoT devices has raised security and privacy concerns, with the identification and removal of compromised and malicious nodes being a major challenge. To overcome this, a lightweight trust management mechanism called FogTrust is proposed. It has a multi-layer architecture that includes edge nodes, a trusted agent, and a fog layer. The trust agent acts as an intermediary authority, communicating with both IoT nodes and the fog layer for computation. This reduces the burden on nodes and ensures a trustworthy environment. The trust agent calculates the trust degree and transmits it to the fog layer, which uses encryption to maintain integrity. The encrypted value is shared with the trust agent for aggregation to improve the trust degree’s accuracy. The performance of the FogTrust approach was evaluated against various potential attacks, including On-off, Good-mouthing, and Bad-mouthing. The simulation results demonstrate that it effectively assigns low trust degrees to malicious nodes in different scenarios, even with varying percentages of malicious nodes in the network.

Food Serving Robot for Contactless Experience

As the world is emerging towards new trends and technologies; there is a need to invent something that is more attractive and useful for the citizens. This research work highlights a very young area of application and provides a comprehensive overview of the application of robotics in the food industry. In this new technological age, all jobs depend on a technology called automation. New research works are developed in the market instead of human workers being the fashion and new passion today. In this context, we develop the concept of the food serving robots (FSR) in this work. It required Arduino board and the Arduino IDE to build. In this research work the board is predefined by using color sensors and the obstacle sensor to identify the tables. This Application can be used in any hotel and restaurant, regular cycles. The use of robots in the food management system is very trendy. Internet of Things mechanisms (IoTM) are widely used to avoid human manual work. It also reduces the number of employees in a workplace. Once the structure is created, it works according to the user's instructions. Here in this Application we will create this robot for food delivery in hotels. In this paper, we consider two tables to show the operation of the robo and the so-called food delivery robot. In this robo build it required components like Arduino board, gear motor, motor controller, IR obstacle sensor, battery (6 volt), and jumper wires.

Collaborative Flow-Identification Mechanism for Software-Defined Internet of Things

Collaborative Flow-Identification Mechanism for Software-Defined Internet of Things

Matching Learning-Based Relay Selection for Substation Power Internet of Things

Wireless sensor network (WSN) can effectively solve the problems of weak coverage, blind coverage, and low survivability of smart substation communication networks by deploying multiple relay nodes and adopting multihop transmission. However, there are still some challenges in the traditional relay selection strategy of WSN in substation, including incomplete information and the selection conflicts among multisource nodes. In this paper, we propose a matching learning-based relay selection mechanism for WSN-based substation power Internet of things (SPIoT). Firstly, considering the electromagnetic interference caused by the operation of high-voltage equipment, a multihop transmission model of SPIoT is built. Furthermore, based on the upper confidence bound (UCB) algorithm and matching theory, a matching learning-based relay selection (MLRS) algorithm is proposed to minimize the energy consumption of SPIoT devices. Simulation results demonstrate that MLRS outperforms existing algorithms in terms of energy consumption and optimal selection probability.

Fault Tolerance Mechanism for Internet of Things (IoT) by Solving Nature Inspired Computing Algorithm (NIC)

In clustering approach the sensor nodes are grouped to form a cluster. The nodes of a clustering network have low powered battery capability and limited processing capabilities. These nodes continuously exchange the data to cluster head which is in turn transforming the data to its base station. Few of these nodes in network may be faulty or may not support life time processing data due to its low power battery. All these sensor nodes measure the temperature, humidity, sound and pollution from environment and collected data is send to cloud for further processing. The fault tolerance mechanism of these nodes is solved by applying genetic algorithm by implementing chromosome technique to identify and avoid fault nodes in the network. This proposed research work increases detection of fault nodes in a network, increase network efficiency, lifetime and reach energy optimization results in Internet of Things (IoT) concept. The performance evaluation shows that the data accuracy in Genetic Algorithm (GA) is higher when compared with Direct Diffusion (DD) Algorithm and Ad-hoc on demand Distance Vector (AODV) Algorithm.

A Cooperative Block-variant Monitoring Mechanism Based on Spectral Clustering for Internet of Things

There exist two main defects in traditional monitoring systems: rigid monitoring intensities and fixed task roles, which induce low monitoring efficiencies and large power consumptions. To alleviate these two problems, this paper proposes a cooperative block-variant monitoring mechanism for Internet of Things. This mechanism divides the whole monitoring area into several blocks with different monitoring intensities according to the spatial distribution of monitoring terminals based on spectral clustering. The monitoring intensities, including monitoring densities and frequencies, are decided by the status of monitoring objects in different blocks and the values of pre-setting thresholds. By adjusting the monitoring densities and frequencies in real time, this method makes the monitoring focus on the most critical blocks, which improves the monitoring efficiencies and reduces the overall consumption of system. In addition, adequate switching of the task roles of nodes balances their workloads, and therefore extends the overall life of the monitoring systems. A large number of experiments have been carried out, and the results show that this collaborative monitoring mechanism achieves good performance.

Smart-Cluster-Based Distributed Caching for Fog-IoT Networks

The idea of co-operative caching in a cache-enabled wireless network has gained much interest due to its services in terms of short service delay and improved transmission rate at the user end. In this article, we consider a co-operative caching mechanism for a fog-enabled Internet of Things (IoT) network. We propose a delay-minimizing policy for fog nodes (FNs), where the goal is to reduce the service delay for the IoT nodes, also known as terminal nodes (TNs). To this end, a novel smart clustering mechanism is proposed, aiming to efficiently assign FNs to the TNs while improving the network benefit by finding a tradeoff between the delay and the network’s energy consumption. We perform mathematical analysis and extensive simulations to highlight the potential gain and the proposed policy.

Provenance‐based data flow control mechanism for Internet of things

AbstractIn the Internet of things (IoT), the flow and sharing of data between different devices has become a trend. However, determining how to ensure the controlled flow and sharing of data is an urgent problem to address to ensure data security and privacy in the IoT environment. To address the above problem, we propose a provenance‐based data flow control mechanism (PDFC) that includes flow control and further control to realize data flow control and further control after flow. The mechanism implements both direct and indirect control of data flow based on provenance data, which reduces the risk of indirect leakage. As data flow and are shared between different devices, the provenance data become increasingly large, consequently, indirect control on the provenance data takes increasing amounts of time, seriously affecting control efficiency. To improve the control efficiency of data flow, the provenance data are simplified according to the type of operation generating the data and the association degree of data and their provenance data. To reduce the storage space occupied by the provenance data and improve the efficiency of querying the provenance data, we propose a provenance tree that records the relationship between data and their provenance data. A theoretical analysis demonstrates the security and effectiveness of PDFC, which can solve the fine‐grained controlled sharing problem in IoT. Using the data flow in a smart healthcare system as an example, we demonstrate the implementation and optimization method of PDFC, and the result shows PDFC has obvious flexibility and performance advantages.

Scalable Asymmetric Security Mechanism for Internet of Things

The Internet of things stances rigorous demands on excellence of quality and the vitality of security. It becomes vital to provide an extremely reliable encryption algorithm with less complexity and computational expense in IoT paradigm. Most of the protocols designed in past for communication between sender and the receiver based on asymmetric cryptography algorithms poses high computational cost. Therefore, this paper presents a less complex and more secure and fast encryption algorithm for communication between devices i.e. Asymmetric Scalable Security between sender and the receiver of the information. We present a reliable, secure, scalable and efficient communication protocol that used asymmetric algorithm for securing the exchange of information between sender and the receiver. The proposed communication protocol is lightweight encryption method that does not require complex resources to perform the computations involved for using the asymmetric cryptography. The simulation results also show that the proposed method is efficient in terms of time and space and ensures confidentiality. Therefore, the proposed scheme is beneficial for providing the secure communication for the power and resource constrained IoT devices.

An Optimized Probabilistic Delay Tolerant Network (DTN) Routing Protocol Based on Scheduling Mechanism for Internet of Things (IoT).

Many applications of Internet of Things (IoT) have been implemented based on unreliable wireless or mobile networks like the delay tolerant network (DTN). Therefore, it is an important issue for IoT applications to achieve efficient data transmission in DTN. In order to improve delivery rate and optimize delivery delay with low overhead in DTN for IoT applications, we propose a new routing protocol, called Scheduling-Probabilistic Routing Protocol using History of Encounters and Transitivity (PROPHET). In this protocol, we calculate the delivery predictability according to the encountering frequency among nodes. Two scheduling mechanisms are proposed to extend the traditional PROPHET protocol and improve performance in both storage and transmission in DTN. In order to evaluate the proposed routing protocol, we perform simulations and compare it with other routing protocols in an Opportunistic Network Environment (ONE) simulator. The results demonstrate that the proposed Scheduling-PROPHET can achieve better performances in several key aspects compared with the existing protocols.

Trust management mechanism for Internet of Things

Trust management has been proven to be a useful technology for providing security service and as a consequence has been used in many applications such as P2P, Grid, ad hoc network and so on. However, few researches about trust mechanism for Internet of Things (IoT) could be found in the literature, though we argue that considerable necessity is held for applying trust mechanism to IoT. In this paper, we establish a formal trust management control mechanism based on architecture modeling of IoT. We decompose the IoT into three layers, which are sensor layer, core layer and application layer, from aspects of network composition of IoT. Each layer is controlled by trust management for special purpose: self-organized, affective routing and multi-service respectively. And the final decision-making is performed by service requester according to the collected trust information as well as requester' policy. Finally, we use a formal semantics-based and fuzzy set theory to realize all above trust mechanism, the result of which provides a general framework for the development of trust models of IoT.

A Novel Multi-x Cooperative Decision-making Mechanism for Cognitive Internet of Things

Cognitive Internet of Things (CIoT) mainly consists of a group of autonomous nodes (ANs) which are commonly combined into domains and should have the intelligence to perceive, analyze, decide and act. Cooperation has shown to be a good technique for collective behavior of ANs that locally interact with each other in distributed environments. In this paper, we study the cooperative decision-making mechanism of multi-ANs and multi-domains and present the corresponding cooperative decision-making process in CIoT. Multi-ANs cooperation deals with the cases that one AN cannot meet the QoS and network performance object (NPO) and multi-domains cooperation addresses the cases that the ANs of only one domain cannot meet the QoS and NPO. Based on the cooperative decision-making mechanism, the simulative experiments are done and show that the NPO can be satisfied perfectly.

An Anonymity and Authentication Mechanism for Internet of Things

Authentication has received increasing attention in the literatures of Internet of Things. At the same time, numerous concerns have been raised about the issue of anonymity due to users’ awareness of their privacy nowadays. How to achieve trade-off between anonymity and certification simultaneously? In this paper, we propose a security architecture to ensure anonymity and certification for Internet of Things. We use pseudonym and threshold secret sharing approach to resolve conflict between anonymity and certification. Moreover, the implementation of Bloom filter offers security authentication for remote command. Security analysis shows that the proposed mechanism can perfectly achieve tradeoff between anonymity, certification, and also resist impersonation, tamper as well as compromise attacks.