The Neural Knowledge DNA Based Smart Internet of Things

Abstract

The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet of Things that enables IoT to extract knowledge from past experiences, as well as to store, evolve, share, and reuse such knowledge aiming for smart functions. By catching decision events, this approach helps IoT gather its own daily operation experiences, and it uses such experiences for knowledge discovery with the support of machine learning technologies. An initial case study is presented at the end of this paper to demonstrate how this approach can help IoT applications become smart: the proposed approach is applied to fitness wristbands to enable human action recognition.     

Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study

In this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach to our current work—SmartBike, a sensor-equipped bicycle built under the concept of Internet of Things. By using Decisional DNA and machine learning algorithms, the SmartBike is able to distinguish its user's patterns based on past riding data. The presented conceptual approach demonstrates how Decisional DNA can be applied to the Internet of Things and bring to them intelligence required by forthcoming semantic networks.     

Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA

ABSTRACT

In this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands based on learning from past valid driving behavior data on a simulator.     

Manufacturing Data Analysis in Internet of Things/Internet of Data (IoT/IoD) Scenario

ABSTRACT

Computer integrated manufacturing (CIM) has enormous benefits as it increases the rate of production, reduces errors and production waste, and streamlines manufacturing sub-systems. However, there are some new challenges related to CIM operating in the Internet of Things/Internet of Data (IoT/IoD) scenarios associated with Industry 4.0 and cyber-physical systems. The main challenge is to deal with the massive volume of data flowing between various CIM components functioning in virtual settings of IoT. This paper proposes decisional DNA-based knowledge representation framework to manage the storage, analysis, and processing of data, information, and knowledge of a typical CIM. The framework utilizes the concept of virtual engineering object and virtual engineering process for developing knowledge models of various CIM components such as automatic storage and retrieval systems, automatic guided vehicles, robots, and numerically controlled machines. The proposed model is capable of capturing in real time the manufacturing data, information and knowledge at every stage of production, that is, at the object level, the process level, and at the factory level. The significance of this study is that it will support decision-making by reusing the experience, which will not only help in effective real-time data monitoring and processing, but also make CIM system intelligent and ready to function in the virtual Industry 4.0 environment.     

Quality-enabled decentralized IoT architecture with efficient resources utilization

The Internet of Things (IoT) is a paradigm aimed at connecting everyday objects to the internet. IoT applications include smart cities, healthcare, agriculture, as well as the industry and manufacturing. The ability to monitor and control the physical world using information technology creates many opportunities. However, it also comes with some costs. The exponential growth of connected devices, the heterogeneity of IoT use cases, and the diversity of the network technologies yield a concern regarding IoT sustainability. With this work, we aim to contribute to this concern. In doing so, we introduce a novel representation model that is destined for (i) monitoring the IoT environment at runtime, (ii) expressing the overall quality of the system, and (iii) helping to utilize the available resources efficiently. We also define a feature set that describes the best the expectations of decentralized IoT platforms. Furthermore, we describe a quality-enabled decentralized IoT architecture too that incorporates the specified feature set as well as our representation model. Such solutions are necessary to improve and maintain IoT of the future and all its application domains, including the Industrial Internet of Things (IIoT). With the presented research, we aim to encourage the efficient utilization of resources and simplify the production of next-generation IoT solutions.     

语义传感器Web中传感器本体的构建及应用

语义传感器Web的出现为物联网中传感器系统间的数据互操作、信息共享和知识融合提供了实现方式,传感器本体的构建则是实现这些功能的前提.本文在参考万维网联盟提出的语义传感器网络本体的基础上,对传感器及配套的数据采集仪构建了对应的本体,为传感器系统提供了有效的知识组织模型.通过建立的传感器和数据采集仪本体,可以实现传感器的自动分类管理,设定推理规则后可以提供传感器和采集仪间的配接推荐,提高检测现场多传感器系统设计的效率和可靠性,将领域知识应用到系统设计和管理中.最后以具体的传感器实例对推理规则进行了测试,结果满足应用要求.     

An efficient steganographic approach for protecting communication in the Internet of Things (IoT) critical infrastructures

ABSTRACT

With the manifestation of the Internet of Things (IoT) and fog computing, the quantity of edge devices is escalating exponentially all over the world, providing better services to the end user with the help of existing and upcoming communication infrastructures. All of these devices are producing and communicating a huge amount of data and control information around this open IoT environment. A large amount of this information contains personal and important information for the user as well as for the organization. The number of attack vectors for malicious users is high due to the openness, distributed nature, and lack of control over the whole IoT environment. For building the IoT as an effective service platform, end users need to trust the system. For this reason, security and privacy of information in the IoT is a great concern in critical infrastructures such as the smart home, smart city, smart healthcare, smart industry, etc. In this article, we propose three information hiding techniques for protecting communication in critical IoT infrastructure with the help of steganography, where RGB images are used as carriers for the information. We hide the information in the deeper layer of the image channels with minimum distortion in the least significant bit (lsb) to be used as indication of data. We analyze our technique both mathematically and experimentally. Mathematically, we show that the adversary cannot predict the actual information by analysis. The proposed approach achieved better imperceptibility and capacity than the various existing techniques along with better resistance to steganalysis attacks such as histogram analysis and RS analysis, as proven experimentally.     

An ontological model of the domain of applications for the Internet of Things in analyzing information security

In this paper, we have proposed an ontological model for the application domain of the Internet of Things (IoT) that provides a detailed representation of the relationships and interrelations between system elements at different levels of abstraction with different degrees of detail. The ontological model allows one to understand the technical aspects of developing security information and event management (SIEM) systems for the detection and analysis of security incidents in the IoT.     

Logistic Regression Trust–A Trust Model for Internet-of-Things Using Regression Analysis

Internet of Things (IoT) is a popular social network in which devices are virtually connected for communicating and sharing information. This is applied greatly in business enterprises and government sectors for delivering the services to their customers, clients and citizens. But, the interaction is successful only based on the trust that each device has on another. Thus trust is very much essential for a social network. As Internet of Things have access over sensitive information, it urges to many threats that lead data management to risk. This issue is addressed by trust management that help to take decision about trustworthiness of requestor and provider before communication and sharing. Several trust-based systems are existing for different domain using Dynamic weight method, Fuzzy classification, Bayes inference and very few Regression analysis for IoT. The proposed algorithm is based on Logistic Regression, which provide strong statistical background to trust prediction. To make our stand strong on regression support to trust, we have compared the performance with equivalent sound Bayes analysis using Beta distribution. The performance is studied in simulated IoT setup with Quality of Service (QoS) and Social parameters for the nodes. The proposed model performs better in terms of various metrics. An IoT connects heterogeneous devices such as tags and sensor devices for sharing of information and avail different application services. The most salient features of IoT system is to design it with scalability, extendibility, compatibility and resiliency against attack. The existing works finds a way to integrate direct and indirect trust to converge quickly and estimate the bias due to attacks in addition to the above features.     

MANAGING IOT SYSTEMS

ABSTRACT

The Internet of Things Systems, or IoT Systems, can have the potential to add substantial value to institutions, such as university campuses, cities, and corporate campuses. However, if these systems are not thoughtfully selected, implemented, subsequently managed, they can instead bring substantial risk to the same. This erosion of value manifests itself in negative ROI on the systems as well degraded cyber risk/cybersecurity posture for the institution, city, or corporate campus. Amongst all of the excitement of what added value IoT Systems can potentially bring – all of the ‘bling’, it is easy to miss the nuanced, but substantial systemic costs that acquisition, implementation and operation/management of these systems bring. The aggregation of this systemic loss can bring the whole value proposition to its knees, both in terms of lost financial and resource investment as well as appreciably degraded cybersecurity posture. IoT Systems are sociotechnical systems that encounter systems loss, as do all systems. As such, they need to be reviewed in that context to serve the needs of the institution, city, or corporation. This article will review differences between IoT Systems and traditional IT systems, what IoT Systems implementation success looks like, systems of systems, boundaries and seams between systems, the importance of manageability of IoT Systems, IoT vendor relationships and vendor management, planning considerations, and strategy.     

TOWARDS THE CONSTRUCTION OF DECISIONAL DNA: A SET OF EXPERIENCE KNOWLEDGE STRUCTURE JAVA CLASS WITHIN AN ONTOLOGY SYSTEM

In this article, we present a Java class and an ontology system implementation for the exploitation of embedded experiential knowledge that can be used in several domains. We support this approach on three concepts: Set of Experience Knowledge Structure (SOEKS), a tool able to collect and manage explicit decisional knowledge; Decisional DNA, a structure for decisional knowledge akin to human DNA; and a group of ontologies for ubiquitous applications called SOUPA (Standard Ontology for Ubiquitous and Pervasive Applications).

The SOUPA is extended with the Set of Experience Knowledge Structure (SOEKS), enhancing the decisional experience used to assemble Decisional DNA with ontology characteristics for ubiquitous and pervasive applications. Additionally, we propose a SOEKS Java class created for the support and easy implementation of applications using the extended SOUPA which will allows the construction of a Decisional DNA repository useful within many different intelligent systems and platforms.     

A secure and scalable storage system for aggregate data in IoT

In recent years, with the impressive rapid development of integrated circuit and networking technologies, computers, devices and networking have become highly pervasive, incurring the introduction, development and deployment of the Internet of Things (IoT). The tiny identifying devices and wearables in IoT have transformed daily life in human society, as they generate, process and store the amount of data increasing at exponential rate all over the world. Due to high demand on data mining and analytics activities in IoT, secure and scalable mass storage systems are highly demanded for aggregate data in efficient processing. In this paper, we propose such a secure and scalable IoT storage system based on revised secret sharing scheme with support of scalability, flexibility and reliability at both data and system levels. Shamir’s secret sharing scheme is applied to achieve data security without complex key management associated with traditional cryptographic algorithms. The original secret sharing scheme is revised to utilize all coefficients in polynomials for larger data capacity at data level. Flexible data insert and delete operations are supported. Moreover, a distributed IoT storage infrastructure is deployed to provide scalability and reliability at system level. Multiple IoT storage servers are aggregated for large storage capacity whereas individual servers can join and leave freely for flexibility at system level. Experimental results have demonstrated the feasibility and benefits of the proposed system as well as tangible performance gains.     

物联网信息服务系统研究综述

信息服务系统作为物联网的重要基石,是实验物联网信息化、智能化的手段。从系统架构、关键技术两个方面阐述物联网信息服务系统的研究现状,在关键技术中着重分析数据质量控制、海量数据存储以及异构数据共享三个方面;最后进行总结,并展望未来工作。     

基于实体-数据的物联网服务建模

物联网服务作为信息世界软件服务通过物联网向现实世界的延伸,其在物联网系统具有重要的作用.然而,不同于传统Web服务,物联网服务具有现实感知、数据驱动、异构分布、时空相关等新特点,使得现有的服务模型不足以对物联网服务有效刻画,进而也不能满足物联网应用中的后续服务发现、服务卸载、服务组合等需求.在凝练分析物联网服务建模需求和已有物联网服务模型的基础上,提出了一种基于实体-数据的物联网服务建模框架,该框架提出了服务、实体、数据三元信息融合的物联网服务模型概念及概念关系,重点定义了服务、实体、数据的时空属性及时空依赖关系,以支持基于时空相关性的物联网服务关联表示与分析,并通过扩展OWL-S(ontology Web language for services)给出了基于实体-数据的物联网服务描述方式.最后,结合一个高速公路物联网应用案例对模型的使用方式和效果进行了讨论.     

Simulation of art design of indoor furnishings based on FPGA and internet of things system

The Internet of Things (IoT) is fast becoming a business opportunity and home indoor design technology, and standards, mainly in wireless communication between everyday human life equipment and tools, in general, is known as the Internet of Things (IoT). The art design of products is behind the home indoor decor furnishing, and there is also service to appliances that connect to the entire home control system internet. This service allows users to decorate their home's indoor design while building an IoT and Field Programmable Gate Array (FPGA) environment. The smart home system has achieved great popularity in the past few decades because they improve the comfort and quality of life. Smartphones and microcontrollers using wireless communication technology, control, and integration of the characteristics of the control room furniture and Internet of Things (IOT) Internet Control smartphone applications intelligent home system, the sensor is triggered and intelligent Internet support. Cloud computing technology is embedded in the content of the smart home. A smart home is a platform that includes to build smart homes, automate, and provide an efficient, comfortable, safe, and convenient home environment. IoT, the detection information, a Radio Frequency Identification System (RFID), sensors, a global positioning system (GPS), the laser scanner, and other knowledge, such as infrared rays, is connected to the Internet.     

A framework based on sparse representation model for time series prediction in smart city

Smart city driven by Big Data and Internet of Things(loT)has become a most promising trend of the future.As one important function of smart city,event alert based on time series prediction is faced with the challenge of how to extract and represent discriminative features of sensing knowledge from the massive sequential data generated by IoT devices.In this paper,a framework based on sparse representa-tion model(SRM)for time series prediction is proposed as an efficient approach to tackle this challenge.After dividing the over-complete dictionary into upper and lower parts,the main idea of SRM is to obtain the sparse representation of time series based on the upper part firstly,and then realize the prediction of future values based on the lower part.The choice of different dictionaries has a significant impact on the performance of SRM.This paper focuses on the study of dictionary construction strategy and summarizes eight variants of SRM.Experimental results demonstrate that SRM can deal with different types of time series prediction flexibly and effectively.     

An extensible and active semantic model of information organizing for the Internet of Things

Data management and information processing play the key roles in developing the Internet of Things (IoT). The requirements of a well-defined data model for IoT involve in six aspects: semantic supporting, active data extracting and explaining, flexibility and extensibility, enabling to manage massive and heterogeneous data, supporting formal organization, and solid mathematic-based theory. This paper aims to exploring an extensible and active semantic information organization model for IoT to meet the above requirements, and the primary idea is “Object-cored organizing data, event-based explaining data, and knowledge-based using data.” The proposed model involves two layers: the object layer and the event layer, and both of them are discussed in detail including conceptions, schema definitions, and the rule-based knowledge representation. Semantic reasoning can be supported by the knowledge base which involves in a set of reasoning rules on semantic relations among objects or among events correspondingly.     

云信任驱动的物联网信息资源分层共享仿真

针对传统的物联网信息资源分层共享方法存在开销大等问题,提出云信任驱动的物联网信息资源分层共享方法。根据物联网中心资源模型,将物联网信息资源分为时间模型、Web负载模型以及信息资源中心传输模型。全面分析物联网信息中心资源对外提供的服务以及各个资源基本模型之间的交互关系,组建物联网信息中心资源分层共享模型,采用自适应粒子群算法优化分层模型的早熟收敛问题,实现云信任驱动的物联网信息资源分层共享。经仿真证明,所提方法具有开销小、检索快速以及资源利用率高的问题。     

A design and implementation of a framework for games in IoT

Interconnection of the sensing and actuating devices providing the ability to share information across platform through a unified framework for enabling innovative applications. This is achieved by seamless ubiquitous sensing, data analytics and information representation as the unifying framework. Extending the current internet with interconnected objects and devices and their virtual representation has been a growing trend in recent years. Internet of Things (IoT) services are becoming a popular services. This will be supported challenges in a large of aspects such as smart health, green energy, smart home and personalized applications. So, the IoT plays more and more important issue in lifestyle through entertainment such as Games. As of yet, there has not been much research done on IoT environment games as a service. In this paper, we propose schemes of the design and implantation of IT convergence framework for games as a service of IoT. First of all, we discussed what to consider when design and implementation of IT convergence framework for games through contents using user’s mobile devices and various sensors in IoT environment and suggest related techniques. Then, we showed the possibility of games in the IoT environment by creating games and measuring the interactions of users in the IoT environment.