Collaboration IoT-Based RBAC with Trust Evaluation Algorithm Model for Massive IoT Integrated Application

With the recent advances in ubiquitous communications and the growing demand for low-power wireless technology, smart IoT device (SID) to access various Internet of Things (IoT) resources through Internet at any time and place alternately. There are some new requirements for integration IoT servers in which each one is individually gathering its local resources in Internet, which cooperatively supports SID to get some flexibility or temporary contract(s) and privileges in order to access their corresponding desired service(s) in a group of collaboration IoT servers. However, traditional access control schemes designed for a single server are not sufficient to handle such applications across multiple collaboration IoT servers to get rich services in IoT environments. It does not take into account both security and efficiency of IoT servers, which securely share their resources. Therefore, the collaboration IoT-based RBAC (Role-based Access Control) with trust evaluation (TE) algorithm model to reducing internal security threats in intra-server and inter server for the massive IoT integrated application is proposed in this paper. Finally, the three trust evaluation algorithms including a local trust evaluation algorithm, a virtual trust evaluation algorithm and a cooperative trust evaluation algorithm in the proposed collaboration IoT-based RBAC model, which are designed and presented for reducing internal security threats in collaborative IoT servers.

     

Decision Based Model for Real-Time IoT Analysis Using Big Data and Machine Learning

Use of internet of things (IoT) in different fields including smart cities, health care, manufacturing, and surveillance is growing rapidly, which results in massive amount of data generated by IoT devices. Real-time processing of large-scale data streams is one of the main challenges of IoT systems. Analyzing IoT data can help in providing better services, predicting trends and timely decision making for industries. The systematic structure of IoT data follows the pattern of big data. In this paper, a novel approach is proposed in which big data tools are used to perform real-time stream processing and analysis on IoT data. We have also applied Spark’s built-in support of the machine learning library in order to make real-time predictions. The efficiency of the proposed system is evaluated by conducting experiments and reporting results on the case scenario of IoT based weather station.

     

Wormhole Attack Detection System for IoT Network: A Hybrid Approach

Many errors in data communication cause security attacks in Internet of Things (IoT). Routing errors at network layer are prominent errors in IoT which degrade the quality of data communication. Many attacks like sinkhole attack, blackhole attack, selective forwarding attack and wormhole attack enter the network through the network layer of the IoT. This paper has an emphasis on the detection of a wormhole attack because it is one of the most uncompromising attacks at the network layer of IoT protocol stack. The wormhole attack is the most disruptive attack out of all the other attacks mentioned above. The wormhole attack inserts information on incorrect routes in the network; it also alters the network information by causing a failure of location-dependent protocols thus defeating the purpose of routing algorithms. This paper covers the design and implementation of an innovative intrusion detection system for the IoT that detects a wormhole attack and the attacker nodes. The presence of a wormhole attack is identified using location information of any node and its neighbor with the help of Received Signal Strength Indicator (RSSI) values and the hop-count. The proposed system is energy efficient hence it is beneficial for a resource-constrained environment of IoT. It also provides precise true-positive (TPR) and false-positive detection rate (FPR).

     

A Distributed Trust Management Mechanism for the Internet of Things Using a Multi-Service Approach

Wireless Personal Communications - In the Internet of Things (IoT) heterogeneous devices can cooperate and communicate to provide or require determined services. A multi-service IoT is vulnerable...     

A KNN-Scoring Based Core-Growing Approach to Cluster Analysis

This paper proposes a novel core-growing (CG) clustering method based on scoring k-nearest neighbors (CG-KNN). First, an initial core for each cluster is obtained, and then a tree-like structure is constructed by sequentially absorbing data points into the existing cores according to the KNN linkage score. The CG-KNN can deal with arbitrary cluster shapes via the KNN linkage strategy. On the other hand, it allows the membership of a previously assigned training pattern to be changed to a more suitable cluster. This is supposed to enhance the robustness. Experimental results on four UCI real data benchmarks and Leukemia data sets indicate that the proposed CG-KNN algorithm outperforms several popular clustering algorithms, such as Fuzzy C-means (FCM) (Xu and Wunsch IEEE Transactions on Neural Networks 16:645–678, 2005), Hierarchical Clustering (HC) (Xu and Wunsch IEEE Transactions on Neural Networks 16:645–678, 2005), Self-Organizing Maps (SOM) (Golub et al. Science 286:531–537, 1999; Tamayo et al. Proceedings of the National Academy of Science USA 96:2907, 1999), and Non-Euclidean Norm FCM (NEFCM) (Karayiannis and Randolph-Gips IEEE Transactions On Neural Networks 16, 2005).     

A Train-Once Approach for Location Estimation Using the Directional Propagation Model

Location estimation that is based on the mobile phone network has drawn considerable attention in the field of wireless communications. Among the different mobile location estimation methods, the one that estimates a mobile station location with reference to a wave propagation model is shown to be effective and is applicable to different kinds of cellular networks, including Global System for Mobile Communications (GSM), cdmaOne, CDMA2000, and the Universal Mobile Telecommunications System. We have designed a train-once approach for location estimations using the directional propagation model (DPM). The DPM is an improved model that is based on the traditional free-space wave propagation model with the directional gain and environmental factors integrated in the estimation. The train-once approach works because we observe that different types of antennas are designed for different types of environments. Thus, a parameter estimation is related to the antenna type and, in turn, related to the environment. In this paper, we report our study of the train-once approach with the DPM for location estimations. We have tested our model with 192 177 sets of real-life data that have been collected from a major mobile phone operator in Hong Kong. Experimental results show that the train-once approach with the DPM is practical and outperforms the existing location estimation algorithms in terms of accuracy, stability among different types of terrains, and success rates.     

An IoT Assisted System for Generating Emergency Alerts Using Routine Analysis

Wireless Personal Communications - This paper proposes a system to generate intimations in emergencies using the internet of things and machine learning to work as a virtual agent. The idea is to...     

Highly Secured Cluster Based WSN Using Novel FCM and Enhanced ECC-ElGamal Encryption in IoT

Wireless Personal Communications - The wireless sensor networks WSN is the most substantial network utilized in the IoT based applications. The WSN consists of various sensor nodes used for the...     

一种传感器网络的分布式信任模型

传感器网络面临的攻击很多,尤其是内部节点进行的攻击带来的危险最大。同时,传感器网络特别是军用传感器网络不能采用建立信任中心的信任模型,导致其内部节点的恶意行为更难以控制。通过引入基于CPK认证的源地址认证模块,使用第三方推荐信任,并结合多种相关的网络行为属性,能够为用户提供更准确可信的信任度计算能力作为参考依据,使用户可以根据信任度对权限进行控制,以达到控制恶意行为的目的。     

Quantitative Survivability Analysis Using Probability Model Checking: A Study of Cluster-Based Vehicle Networks with Dual Cluster Heads

As an important part of future 5G wireless networks,a vehicular network demands safety,reliability and connectivity.In this context,networking survivability is usually considered an important metric to evaluate network performance.In this paper,we propose a survivability model for vehicle communication networking based on dual cluster heads,wherein a backup cluster head(CH)will be activated if the primary CH fails,thereby effectively enhancing the network lifetime.Additionally,we introduce a software rejuvenation strategy for the prime CH to further improve the survivability of the entire network.Using the Probabilistic Symbolic Model Checker(PRISM),we verify and discuss the proposed survivability model via numerical simulations.The results show that network survivability can be effectively improved by introducing an additional CH and further enhanced by adopting the software rejuvenation technique.     

A Model for Low Power,High Speed and Energy Efficient Early Landslide Detection System Using IoT

A landslide, also called as landslip appear to be the most threatening disaster of all time especially in the hillside regions. It involves enormous surface movements including debris flows, slopes failure, rock fall etc. It mainly occurs when the land slopes become unstable. Other measures that also lead to landslides are Ground water changes, Earthquakes, Floods, Volcano eruptions and Heavy rainfalls. People among these hill areas doesn’t know about the disaster that’s about to happen massively. The perfect way to avoid such hazards is by predicting it at initial phase with maximum accuracy. There are many wired and wireless supervising systems available to detect landslides which require higher cost and maintenance. But we have a suitable solution for this with Internet of Things (IoT) based approach. It improves objects control and detection remotely between various networks thereby creating possibilities for direct communication between physical and computer-based world. By this approach Landslides can be predicted at the initial phase. If there is a higher chance of Landslide then an alert will be sent to disaster management sector immediately to take necessary precautions so that enormous precious lives can be protected. This paper proposes a model for IoT based Landslide detection mechanisms in detail.

     

A Systematic Survey on Fog steered IoT: Architecture,Prevalent Threats and Trust Models

International Journal of Wireless Information Networks - Internet of Things (IoT) is considered as a scheme that consists of smart objects furnished with sensors, processing and networking...     

一种基于邻居合作监测的移动Ad hoc网络信任模型

针对自私节点的恶意丢包行为,将节点和其邻居节点所监测的结果结合起来,计算出节点间的信任度,并以此作为路由选择的依据来促进节点间的相互合作,提出一种基于邻居合作监测的移动Adhoc网络信任模型.将信任模型应用于DSR路由协议并在NS2中进行仿真实验,结果表明该信任模型可以有效地缓解自私节点造成的影响,提高了网络的分组投递率.     

SEPAR: A New Lightweight Hybrid Encryption Algorithm with a Novel Design Approach for IoT

Wireless Personal Communications - This paper presents a new hybrid encryption algorithm with 16-bit block size and a 128-bit initialization vector, referred to as SEPAR, and it is suitable for IoT...     

Using SMS for Communication with IoT Devices

Mobile Networks and Applications - This paper is in the context of Smart Cities and Internet of Things (IoT). We proposed a novel approach in communication of IoT devices via SMS messages. This can...     

Scheduling Correlated IoT Application Requests Within IoT Eco-System: An Incremental Cloud Oriented Approach

Wireless Personal Communications - In the era of adopting Internet everywhere, the recent modernization through incredible Internet of Things (IoT) makes the world more shrewd and automated....     

A Smart Parking System: An IoT Based Computer Vision Approach for Free Parking Spot Detection Using Faster R-CNN with YOLOv3 Method

Wireless Personal Communications - Internet-of-things has altered pervasive figuring with many applications created around different kinds of sensors/devices. As for these applications lower...     

Ad Hoc网络中一种基于救赎机制的信任模型

在Ad Hoc网络中,节点由于自私等恶意原因以及链路错误导致拒绝转发数据,需要采用适当的机制来提高网络的转发性能。提出一种Ad Hoc网络中的信任模型来激励节点间的协作,在此信任模型中,每个节点通过直接监控和其它节点的推荐监控信息共同完成对邻居节点的信任评价,并维护所有邻居节点的信任值,同时在信任值更新和重建中引入信任值衰退和信任救赎机制来体现模型的健壮性。实验表明该信任模型中的信任救赎机制能提高网络可用性,且该模型有效抑制了恶意节点的行为。