Capability-based IoT access control using blockchain

Internet of Things (IoT) devices facilitate intelligent service delivery in a broad range of settings, such as smart offices, homes and cities. However, the existing IoT access control solutions are mainly based on conventional identity management schemes and use centralized architectures. There are known security and privacy limitations with such schemes and architectures, such as the single-point failure or surveillance (e.g., device tracking). Hence, in this paper, we present an architecture for capability-based IoT access control utilizing the blockchain and decentralized identifiers to manage the identity and access control for IoT devices. Then, we propose a protocol to provide a systematic view of system interactions, to improve security. We also implement a proof-of-concept prototype of the proposed approach and evaluate the prototype using a real-world use case. Our evaluation results show that the proposed solution is feasible, secure, and scalable.     

基于雾计算的物联网架构研究

物联网是一种能将物体连接至互联网使其更加智能的技术.但是物联网设备产生的大数据难以处理,网络架构的可扩展性差,以及用户的安全隐私容易泄露等问题都限制了物联网的发展.为了解决这些问题,通过分析雾计算所具有的优势提出基于雾计算的物联网架构.基于该架构,同时考虑到用户的安全隐私问题,又提出分层的网络架构.最后对文章进行总结和展望.     

Reliable and secure data transfer in IoT networks

With the rapid technological improvements in mobile devices and their inclusion in Internet of Things (IoT), secure key management becomes mandatory to ensure security of information exchange. For instance, IoT applications, such as smart health-care and smart homes, provide automated services to the users with less or no user intervention. As these application use user-sensitive data, ensuring their security and privacy should be paramount, especially during the key management process. However, traditional approaches for key management will not suit well in IoT environment because of the inherent resource constraint property of IoT devices. In this paper, we propose a novel distributed key management scheme for IoT ecosystem. The proposed scheme efficiently provides security to IoT devices by delegating most of the resource consuming cryptographic processing to a local entity. This entity coordinates with other peer entities to provide a distributed key as well as an authentication mechanism to network devices. In particular, the proposed scheme exploits the advantages of mobile agents by deploying them in different subnetworks as and when required: (1) to process the cryptography work for the IoT devices, and (2) to act as an local authenticated entity to perform fast authentication process. To verify the effectiveness and correctness of our proposed scheme, we have simulated it in a large IoT scenario and evaluated against relevant metrics that includes user mobility, certification generation time, and communication overhead.

     

BDN-GWMNN: Internet of Things (IoT) Enabled Secure Smart City Applications

Nowadays, next-generation networks such as the Internet of Things (IoT) and 6G are played a vital role in providing an intelligent environment. The development of technologies helps to create smart city applications like the healthcare system, smart industry, and smart water plan, etc. Any user accesses the developed applications; at the time, security, privacy, and confidentiality arechallenging to manage. So, this paper introduces the blockchain-defined networks with a grey wolf optimized modular neural network approach for managing the smart environment security. During this process, construction, translation, and application layers are created, in which user authenticated based blocks are designed to handle the security and privacy property. Then the optimized neural network is applied to maintain the latency and computational resource utilization in IoT enabled smart applications. Then the efficiency of the system is evaluated using simulation results, in which system ensures low latency, high security (99.12%) compared to the multi-layer perceptron, and deep learning networks.

     

Smart Prediction and Monitoring of Waste Disposal System Using IoT and Cloud for IoT Based Smart Cities

One of the prominent applications of Internet of Things (IoT) in this digital era is the development of smart cities. In IoT based smart cities, the smart objects (devices) are connected with each other via internet as a backbone. The sensed data by the smart objects are transmitted to the sink for further processing using multi hop communication. The smart cities use the analyzed data to improve their infrastructure, public utilities and they enhance their services by using the IoT technology for the betterment of livelihood of the common people. For IoT based smart cities, waste collection is a prominent issue for municipalities that aim to achieve a clean environment. With a boom in population in urban areas, an increasing amount of waste is generated. A major issue of waste management system is the poor process used in waste collection and segregation. Public bins begin to overflow for a long period before the process of cleaning starts, which is resulting in an accumulation of bacteria causing bad odors and spreading of diseases. In order to overcome this issue, in this paper an IoT based smart predication and monitoring of waste disposal system is proposed which utilizes off-the-shelf components that can be mounted to a bin of any size and measure fill levels. An Arduino microcontroller is employed in the proposed model to interface the infrared (IR), ultraviolet (UV), weight sensors, and a Global Positioning System (GPS) module is used to monitor the status of bins at predetermined intervals. The proposed system transmits the data using the cluster network to the master module which is connected to the backend via Wi-Fi. As data is collected, an intelligent neural network algorithm namely Long Short-Term Memory (LSTM) is used which will intelligently learn and predict the upcoming wastage from waste generation patterns. Moreover, the proposed system uses Firebase Cloud Messaging to notify the appropriate people when the bins were full and needed to be emptied. The Firebase Cloud Messaging (FCM) JavaScript Application Programming Interface (API) is used to send notification messages in web apps in browsers that provide service work support. Hence, the proposed system is useful to the society by providing facilities to the governments for enforcing stricter regulations for waste disposal. Additional features such as automated calibration of bin height, a dynamic web data dashboard as well as collation of data into a distributed real-time firebase database are also provided in the proposed system.

     

RAD‐EI: A routing attack detection scheme for edge‐based Internet of Things environment

Internet of Things (IoT) offers various types of application services in different domains, such as “smart infrastructure, health‐care, critical infrastructure, and intelligent transportation system.” The name edge computing signifies a corner or edge in a network at which traffic enters or exits from the network. In edge computing, the data analysis task happens very close to the IoT smart sensors and devices. Edge computing can also speed up the analysis process, which allows decision makers to take action within a short duration of time. However, edge‐based IoT environment has several security and privacy issues similar to those for the cloud‐based IoT environment. Various types of attacks, such as “replay, man‐in‐the middle, impersonation, password guessing, routing attack, and other denial of service attacks” may be possible in edge‐based IoT environment. The routing attacker nodes have the capability to deviate and disrupt the normal flow of traffic. These malicious nodes do not send packets (messages) to the edge node and only send packets to its neighbor collaborator attacker nodes. Therefore, in the presence of such kind of routing attack, edge node does not get the information or sometimes it gets the partial information. This further affects the overall performance of communication of edge‐based IoT environment. In the presence of such an attack, the “throughput of the network” decreases, “end‐to‐end delay” increases, “packet delivery ratio” decreases, and other parameters also get affected. Consequently, it is important to provide solution for such kind of attack. In this paper, we design an intrusion detection scheme for the detection of routing attack in edge‐based IoT environment called as RAD‐EI. We simulate RAD‐EI using the widely used “NS2 simulator” to measure different network parameters. Furthermore, we provide the security analysis of RAD‐EI to prove its resilience against routing attacks. RAD‐EI accomplishes around 95.0% “detection rate” and 1.23% “false positive rate” that are notably better than other related existing schemes. In addition, RAD‐EI is efficient in terms of computation and communication costs. As a result, RAD‐EI is a good match for some critical and sensitive applications, such as smart security and surveillance system.     

A Review on the Security of the Internet of Things: Challenges and Solutions

The Internet of Things (IoT) has emerged as a modern wave of Internet technologies that promises great transformation of life in areas such as smart health, smart cities, smart homes, intelligent transport, amongst others. However, security often serves as a critical reason for the widespread adoption of any innovation. While the IoT has increased business productivity and enriched diverse areas of life over the years, the world is yet to see a methodical revolution of its humongous application and transformation given its ubiquity and highly interconnected global network structure. The main culprit for such lapses is principally attributed to security and privacy issues which have been widely discussed in research articles and reviews but remain largely unaddressed in the literature. Hence, this paper provides a state-of-the-art review of IoT security and its challenges. It overviews technical and legal solutions that are useful to private, organizational, and governmental enterprises. The study encompasses the review and security analysis of IoT’s evolution and revolution, IoT security assessments, requirements, current research challenges in security and much more. Consequently, it offers potential solutions to address the security challenges discussed and further present open research issues, research gaps, opportunities, future development, and recommendations. This overview is intended to serve as a knowledgebase that will proffer novel foresight to guide users and administrators in positioning themselves and their organizations in a manner that is consistent with their overall objectives, mission, and vision for remarkable outcomes. Likewise, interested scholars and researchers can explore topics and directions from the study in providing better solutions to the numerous problems in IoT security.

     

A reputation-based RPL protocol to detect selective forwarding attack in Internet of Things

Internet of Things (IoT) is an internet of smart objects where smart objects communicate with each other. IoT objects are deployed in open medium with dynamic topology. Due lack of infrastructure and centralized management, IoT present serious vulnerabilities to security attacks. Therefore, security is an essential prerequisite for the real-world deployment of IoT. In this work, we propose reputation-based RPL protocol where reputation-based mechanism is embedded into RPL protocol to enhance its capabilities against selective forwarding attack. Reputation is calculated by evaluating data forwarding behavior of IoT node. Data forwarding behavior of IoT node is evaluated by the difference between monitored actual packet loss and estimated normal loss. Calculated reputation value is considered in parent selection. Simulation results show that the proposed approach can accurately detect and isolate selective forwarding attack with improving data delivery ratio of the IoT network.     

Real Time Scheduling in TSCH for IoT Using Neurogenetic Algorithm

Internet of Things (IoT) is a widely adoptable technology in industrial, smart home, smart grid, smart city and smart healthcare applications. The real world objects are remotely connected through internet and it provides services with the help of friendly devices. Currently IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) standard is gaining a part of consideration among the IoT research community because of its effectiveness to improvise the reliability of communication which is orchestrated by the scheduling. As TSCH is an emerging Medium Access Control (MAC) protocol, it is used in the proposed work to enhance the network scheduling by throughput maximization and delay minimization. The paper focuses on proper utilization of the channel through node scheduling. NeuroGenetic Algorithm (NGA) has been proposed for TSCH scheduling and its performance is evaluated with respect to time delay and throughput. The system is implemented in real time IoT devices and results are perceived and analyzed. The proposed algorithm is compared with existing TSCH scheduling algorithms.

     

A lightweight IoT‐based security framework for inventory automation using wireless sensor network

Internet of things (IoT) has evolved as an innovation of next generation in this world of smart devices. IoT tends to provide services for data collection, data management, and data and device security required for application development. Things or devices in IoT communicate and compute to make our lives comfortable and safe. In inventory automation, real‐time check on items, their information management, and status management, monitoring can be carried out using IoT. The huge amount of data that flows among the devices in the network demands for a security framework that ensures authentication, authorization, integrity, and confidentiality of data. The existing security solutions like SIMON or SPECK offer lightweight security solutions but are vulnerable to differential attack because of their simplicity. Moreover, existing solutions do not offer inbuilt authentication. Therefore, this research work contributes a secure and lightweight IoT‐based framework using wireless sensor network (WSN) as a technology. The existing security solutions SPECK and SIMON are compared with the proposed security approach using COOJA simulator. The results show that proposed approach outstands others by 2% reduction in number of CPU cycles, 10% less execution time, 4% less memory requirements of security approach, and with minimum 10% more security impact.     

Smart integrated IoT healthcare system for cancer care

The emergence of the internet of things (IoT) has drastically influenced and shaped the world of technology in the contexts of connectivity, interconnectivity, and interoperability with smart connected sensors, objects, devices, data, and applications. In fact, IoT has brought notable impacts on the global economy and human experience that span from industry to industry in a variety of application domains, including healthcare. With IoT, it is expected to facilitate a seamless interaction and communication of objects (devices) with humans in the environment. Therefore, it is imperative to embrace the potentials and benefits of IoT technology in healthcare delivery to ensure saving lives and to improve the quality of life using smart connected devices. In this paper, we focus on the IoT based healthcare system for cancer care services and business analytics/cloud services and also propose the adoption and implementation of IoT/WSN technology to augment the existing treatment options to deliver healthcare solution. Here, the business analytics/cloud services constitute the enablers for actionable insights, decision making, data transmission and reporting for enhancing cancer treatments. Furthermore, we propose a variety of frameworks and architectures to illustrate and support the functional IoT-based solution that is being considered or utilized in our proposed smart healthcare solution for cancer care services. Finally, it will be important to understand and discuss some security issues and operational challenges that have characterized the IoT-enabled healthcare system.

     

Research of authentication techniques for the Internet of things

Identity authentication technology is a key technology in the Internet of things (IoT)security field which ensures the authenticity of the identity information of users and device nodes connected to the IoT.Due to the low cost,low power consumption,small storage of IoT devices and heterogeneity of IoT network,the identity authentication mechanisms in traditional computer networks are often not applicable.Firstly,the development process of IoT was introduced,the security risks of IoT and the challenges faced by the authentication work were analyzed.Then the emphasis was put on comparison of the advantages and disadvantages among five typical authentication protocols.Moreover,the authentication technologies in several practical scenarios of RFID,smart grid,Internet of vehicles,and smart home were summarized and analyzed.Finally,the future research direction was discussed.     

The Digital Fingerprinting Analysis of Generic Twitter Sessions from Internet of Things Security Aspect

Nowadays, the unparalleled growth of Internet of Things (IoT) is a new digital disruption which intelligent devices are connected and working together. IoT connects personal computers, tablets, and smart phones in our daily communications from leisure purposes to business tasks. However, the security concern of IoT can’t be overemphasized due to the connectivity among communication gadgets. Sustainably, Twitter is one of the most popular Instant Message (IM) toolkits today. When Twitter is being utilized, there will be some negligible and imperceptible digital remnants left in the computing devices, which could be probative digital evidences in a court of law when IoT application is involved. Hence, the digital forensics of IM has been a relatively rigorous, competitive, and novel research field by the law enforcement agency officers and the information security staffs with respect to some cybercrimes concerning IoT. Consequently, this research is targeting on the utilization of Twitter on the desktop PC under Windows 7 operating system via the acquisition of volatile digital bread crumbs inside physical memory of the computing device for the purpose of presenting supportive digital evidences for some information security concerns. The proposed various scenarios in the design of the experiment could be the paradigms for digital forensics specialists or law enforcement agencies to follow in order to reconstruct the previous operations in the Twitter sessions of a certain user under the IoT ecosystems.

     

A review on smart home present state and challenges: linked to context-awareness internet of things (IoT)

The smart home is considered as an essential domain in Internet of Things (IoT) applications, it is an interconnected home where all types of things interact with each other via the Internet. This helps to automate the home by making it smart and interconnected. However, at the same time, it raises a great concern of the privacy and security for the users due to its capability to be controlled remotely. Hence, the rapid technologically growth of IoT raises abundant challenges such as how to provide the home users with safe and secure services keeping privacy in the account and how to manage the smart home successfully under the controlled condition to avoid any further secrecy or theft of personal data. A number of the research papers are available to address these critical issues, researchers presented different approaches to overcome these stated issues. This research review will analyze smart home approaches, challenges and will suggest possible solutions for them and illustrate open issues that still need to be addressed.

     

Fog-Sec: Secure end-to-end communication in fog-enabled IoT network using permissioned blockchain system

The technological integration of the Internet of Things (IoT)-Cloud paradigm has enabled intelligent linkages of things, data, processes, and people for efficient decision making without human intervention. However, it poses various challenges for IoT networks that cannot handle large amounts of operation technology (OT) data due to physical storage shortages, excessive latency, higher transfer costs, a lack of context awareness, impractical resiliency, and so on. As a result, the fog network emerged as a new computing model for providing computing capacity closer to IoT edge devices. The IoT-Fog-Cloud network, on the other hand, is more vulnerable to multiple security flaws, such as missing key management problems, inappropriate access control, inadequate software update mechanism, insecure configuration files and default passwords, missing communication security, and secure key exchange algorithms over unsecured channels. Therefore, these networks cannot make good security decisions, which are significantly easier to hack than to defend the fog-enabled IoT environment. This paper proposes the cooperative flow for securing edge devices in fog-enabled IoT networks using a permissioned blockchain system (pBCS). The proposed fog-enabled IoT network provides efficient security solutions for key management issues, communication security, and secure key exchange mechanism using a blockchain system. To secure the fog-based IoT network, we proposed a mechanism for identification and authentication among fog, gateway, and edge nodes that should register with the blockchain network. The fog nodes maintain the blockchain system and hold a shared smart contract for validating edge devices. The participating fog nodes serve as validators and maintain a distributed ledger/blockchain to authenticate and validate the request of the edge nodes. The network services can only be accessed by nodes that have been authenticated against the blockchain system. We implemented the proposed pBCS network using the private Ethereum 2.0 that enables secure device-to-device communication and demonstrated performance metrics such as throughput, transaction delay, block creation response time, communication, and computation overhead using state-of-the-art techniques. Finally, we conducted a security analysis of the communication network to protect the IoT edge devices from unauthorized malicious nodes without data loss.     

物联网的问题和挑战

如今,随着物联网应用范围的不断扩大,其发展已经体现出了多面性。这是从基于计算机的网络模式向智能对象的完全分布式网络的重大转变,这种变化带来了体系结构和安全等问题。文章从物联网的概念、结构、挑战和安全隐私方面对其进行了介绍。     

物联网的安全威胁及需求分析

物联网分布范围的广泛性、节点的移动性以及业务应用的复杂性给物联网的安全带来严峻挑战。根据物联网的架构和特点,划分物联网的安全体系,并分析了不同层面所面临的多种安全问题。分别从物联网末端节点、感知层、网络层、应用层、管理控制五个层面全面分析了物联网可能面临的多种安全威胁,并在此基础上提出了物联网面临的安全需求。     

A review on evolving domains of Internet of Things: Architecture,applications, and technical challenges

The Internet of Things (IoT) is a system that includes smart items with different sensors, advanced technologies, analytics, cloud servers, and other wireless devices that integrate and work together to create an intelligent environment that benefits end users. With its wide spectrum of applications, IoT is revolutionizing both the current and future generations of the Internet. IoT systems can be employed for broad-ranging real applications, such as agriculture, the environment, cities, healthcare, and the industrial sector. In this paper, we briefly discuss the three-tier architectural view of IoT, its different communication technologies, and the smart sensors. Moreover, we study various application areas of IoT such as the environmental domain, healthcare, agriculture, smart cities, and industrial, commercial, and general aspects. A critical analysis is shown for the existing schemes and techniques related to this work. Further, this paper addresses the basic context, tools and evaluation approaches, future scope, and the advantages and disadvantages of the aforestated IoT applications. A comprehensive analysis is provided for each domain along with its fundamental parameters like the quality of service (QoS), network longevity, scalability, energy efficiency, accuracy, and cost. Finally, this study highlights the technical challenges and open research problems existing in different IoT applications.     

A systematic literature review of machine learning applications in IoT

The Internet of Things (IoT) is a network of interconnected smart objects having capabilities that collectively form an ecosystem and enable the delivery of smart services to users. The IoT is providing several benefits into people's lives through the environment. The various applications that are run in the IoT environment offer facilities and services. The most crucial services provided by IoT applications are quick decision for efficient management. Recently, machine learning (ML) techniques have been successfully used to maximize the potential of IoT systems. This paper presents a systematic review of the literature on the integration of ML methods in the IoT. The challenges of IoT systems are split into two categories: fundamental operation and performance. We also look at how ML is assisting in the resolution of fundamental system operation challenges such as security, big data, clustering, routing, and data aggregation.     

An Efficient and Secure Data Forwarding Mechanism for Opportunistic IoT

Internet of Things (IoT) is a heterogeneous network of interconnected things where users, smart devices and wireless technologies, collude for providing services. It is expected that a great deal of devices will get connected to the Internet in the near future. Opportunistic networks(OppNet) are a class of disruption tolerant networks characterized by uncertain topology and intermittent connectivity between the nodes. Opportunistic Internet of Things(OppIoT) is an amalgamation of the OppNet and IoT exploiting the communication between the IoT devices and the communities formed by humans. The data is exposed to a wide unfamiliar audience and the message delivery is dependent on the residual battery of the node, as most of the energy is spent on node discovery and message transmission. In such a scenario where a huge number of devices are accommodated, a scalable, adaptable, inter-operable, energy-efficient and secure network architecture is required. This paper proposes a novel defense mechanism against black hole and packet fabrication attacks for OppIoT, GFRSA, A Green Forwarding ratio and RSA (Rivest, Shamir and Adleman) based secure routing protocol. The selection of the next hop is based on node’s forwarding behavior, current energy level and its predicted message delivery probability. For further enhancing the security provided by the protocol, the messages are encrypted using asymmetric cryptography before transmission. Simulations performed using opportunistic network environment (ONE) simulator convey that GFRSA provides message security, saves energy and outperforms the existing protocols, LPRF-MC (Location Prediction-based Forwarding for Routing using Markov Chain) and RSASec (Asymmetric RSA-based security approach) in terms of correct packet delivery by 27.37%, message delivery probability is higher by 34.51%, number of messages dropped are reduced by 15.17% and the residual node energy is higher by 14.08%.