Cache Freshness in Named Data Networking for the Internet of Things

A Lightweight Forwarding Strategy for Named Data Networking in Low-end IoT

The project is about to implement Internet of Things (IoT) technology in Railways. Goal is to constitute a secure IoT system by using Information Centric Networking (ICN) architecture to comprehend the key requirements of IoT system. The proposed system is based on ICN architecture. ICN is the architecture which supports multicast, mobility and security. Mobility is the necessity here in the proposed IoT system in railways. System contains passenger information which should remain secure. Hence, ICN architecture is used as a base for IoT system in railways. The Internet of Things (IoT) based system is for catering passengers' services and requests in long journey railways. The system is to collect requests from passengers from each coach, track the location of crew members within train and allocate them requests from passengers. This allocation of the requests to the crew members takes place depending on the service arrival time, location information and workload factor of crew member. As proposed project is based on ICN architecture, it will use secure device discovery concept to make system more secure.

As devices for the Internet of Things (IoT) are typically battery-powered, energy efficiency is a major challenge for IoT networks. In this paper, we leverage the in-network caching of Information-Centric Networking (ICN) to propose a novel cooperative caching scheme, based on the IoT data lifetime and user request rate, to improve the energy efficiency of IoT networks. By caching IoT data at different nodes (such as content routers, base stations, etc.), IoT devices can stay in sleep mode for a larger portion of time and therefore reduce the overall energy consumption. With the help of an auto- configuration mechanism, the proposed IoT data Lifetime-based Cooperative Caching (LCC) scheme can dynamically adapt to the change of request rate. Extensive evaluations were performed and the simulation results show that LCC outperforms existing schemes in terms of total energy consumption reduction (up to 40%) and the reduction in the average number of hops traversed along the path (up to 20%), which is also directly related to the response time. Keywords- Internet of Things (IoT), Cooperative Caching, Information-Centric Network (ICN).

The Internet of Things (IoT) is a diverse technology that primarily utilizes TCP/IP protocols in IoT environments. However, it is often argued that the existing IP protocol stack is insufficient to support data sharing and storage capabilities for mobile IoT applications. Named Data Networking (NDN) has gained significant attention over time as a solution to the limitations of host-centric services in traditional IP networks. The key advantages of NDN include name-based routing and network caching, along with mobility support in wireless networks. The integration of NDN and IoT can address issues related to frequent node mobility, name-based routing, and storage constraints on resource-limited devices. IoT devices are frequently in mobility, creating routing challenges when transitioning from one domain to another. Interest packets remain unsatisfied until the producer reconnects to a new Point of Attachment (PoA) and updates its location. Despite these reconnections, challenges such as interest and data packet losses, increased latency, and suboptimal routing paths persist during communication. Consequently, managing producer mobility remains difficult during the frequent movement of nodes across different IoT domains. This paper proposes a novel Zone-Based Producer Mobility Management (ZBP-MM) protocol for NDN-based IoT environments. The proposed technique is evaluated and compared against the OPMSS scheme using the ndnSIM simulator. Results demonstrated that the proposed scheme achieves better hop count and cache hit ratio, with minimized interest satisfaction delay and handover delay, compared to the OPMSS technique during producer mobility scenarios in intra- and inter-zones.

The Internet of Things (IoT) devices is able to communicate with another IoT devices in heterogeneous environments. They are also able to create a network by their own using wireless capabilities without a centralized approach. This network is called wireless mobile ad hoc network (MANET). The MANET facilitate IoT devices to communicate with each other in an infrastructure less network of the Internet of Things environment. The IoT devices can dynamically join, create connection and exchange information among them. The role of cloud in this framework is to store and process the data by IoT devices. The communication Security has been raised as one of the most critical issues of cloud computing where resolving such an issue would result in a constant growth in the use and popularity of cloud. Our purpose of this study is to create a framework for providing the communication in an integrated framework of Cloud and MANET among IoT devices. Our main contribution links a new study that integrates cloud computing to the MANET and provides communication to the internet of things. This study can be used in the framework of the Internet of Things in future.

Privacy preserving Internet of Things: From privacy techniques to a blueprint architecture and efficient implementation

The Internet of Things (IoT) is overrunning different domains and applications, where the use of wireless sensors and mobile devices is indispensable in such a mobile environment. These heterogeneous devices may generate a tremendous amount of content. Information-Centric Network (ICN) paradigm has been proposed to meet today’s users and application requirements. The in-network caching is a fundamental feature supported by design in ICN that improves network performance by providing ubiquitous caching in the network layer. Since most IoT devices are resource-constrained with limitations in communication, processing, energy, and memory; the energy-efficiency is a prime concern in IoT deployment. Different factors may affect energy efficiency in ICN-based wireless IoT networks such as transport (communication), caching, and energy limitation. This research paper attempts to focus on the in-network caching in wireless IoT to maximize the energy-efficiency. We propose an Energy-aware caching placement scheme (EaCP) that aims to maximize the energy-saving by trading-off between content transmission energy and content caching energy. Compared to other strategies, the simulation results show significant improvements while ensuring low data replication and a high cache hit ratio.

A survey of Internet of Things communication using ICN: A use case perspective

Recently, with the increasing application of the Internet of Things (IoT), various IoT environments such as smart factories, smart homes, and smart grids are being generated. In the IoT environment, a lot of data are generated in real time, and the generated IoT data can be used as source data for various services such as artificial intelligence, remote medical care, and finance, and can also be used for purposes such as electricity bill generation. Therefore, data access control is required to grant access rights to various data users in the IoT environment who need such IoT data. In addition, IoT data contain sensitive information such as personal information, so privacy protection is also essential. Ciphertext-policy attribute-based encryption (CP-ABE) technology has been utilized to address these requirements. Furthermore, system structures applying blockchains with CP-ABE are being studied to prevent bottlenecks and single failures of cloud servers, as well as to support data auditing. However, these systems do not stipulate authentication and key agreement to ensure the security of the data transmission process and data outsourcing. Accordingly, we propose a data access control and key agreement scheme using CP-ABE to ensure data security in a blockchain-based system. In addition, we propose a system that can provide data nonrepudiation, data accountability, and data verification functions by utilizing blockchains. Both formal and informal security verifications are performed to demonstrate the security of the proposed system. We also compare the security, functional aspects, and computational and communication costs of previous systems. Furthermore, we perform cryptographic calculations to analyze the system in practical terms. As a result, our proposed protocol is safer against attacks such as guessing attacks and tracing attacks than other protocols, and can provide mutual authentication and key agreement functions. In addition, the proposed protocol is more efficient than other protocols, so it can be applied to practical IoT environments.

The explosive proliferation of Internet of Things (IoT) devices is generating an incomprehensible amount of data. Machine learning plays an imperative role in aggregating this data and extracting valuable information for improving operational and decision-making processes. In particular, emerging machine intelligence platforms that host pre-trained machine learning models are opening up new opportunities for IoT industries. While those platforms facilitate customers to analyze IoT data and deliver faster and accurate insights, end users and machine learning service providers (MLSPs) have raised concerns regarding security and privacy of IoT data as well as the pre-trained machine learning models for certain applications such as healthcare, smart energy, etc. In this paper, we propose a cloud-assisted, privacypreserving machine learning classification scheme over encrypted data for IoT devices. Our scheme is based on a three-party model coupled with a two-stage decryption Paillier-based cryptosystem, which allows a cloud server to interact with MLSPs on behalf of the resource-constrained IoT devices in a privacy-preserving manner, and shift load of computation-intensive classification operations from them. The detailed security analysis and the extensive simulations with different key lengths and number of features and classes demonstrate that our scheme can effectively reduce the overhead for IoT devices in machine learning classification applications.

Information Centric Networking (ICN) has been proposed as an encouraging remedy for solving complications of traditional IP based architecture. In this work, we present the design and implementation of an ICN framework in Contiki NG OS, a prominent operating system (OS) for constrained IoT devices that have limited computing and communication capabilities. Elementary end-to-end communication paradigms of Named Data Networking (NDN), inspired from ICN concepts and proposed as one of Future Internet Architectures (FIA), is integrated to Contiki NG OS developed for low-power and constrained Internet of Things (IoT) devices. Our results demonstrate the expediency of using the NDN concept for constrained IoT devices in Contiki NG OS.

Information Centric Networking (ICN) is an emerging research topic aiming at shifting the Internet from its current host-centric paradigm towards an approach centred around content, which enables the direct retrieval of information objects in a secure, reliable, scalable, and efficient way. The exposure of ICN to scenarios other than static content distribution is a growing research topic, promising to extend the impact of ICN to a broader scale. In this context, particular attention has been given to the application of ICN in Internet of Things (IoT) environments. The current paper, by focusing on local domain IoT scenarios, such as multi-sensory Machine to Machine environments, discusses the challenges that ICN, particularly Interest-based solutions, impose to service discovery. This work proposes a service discovery mechanism for such scenarios, relying on an alternative forwarding pipeline for supporting its core operations. The proposed mechanism is validated through a proof-of-concept prototype, developed on top of the Named Data Networking ICN architecture, with results showcasing the benefits of our solution for discovering services within a collision domain.

In the recent days, wide-ranging cellular devices and purchaser gadgets in the Internet of Things (IoT) have created immense multimedia information in different types of media (for example, content, pictures, video, and sound). Due to this, there is a great increase in the research challenges for creating strategies and tools in addressing Multimedia Big Data (MMBD) for future IoT. As the worldwide framework for the ongoing data society, IoT empowers progressed benefits by interconnecting (virtual as well as physical) things dependent on existing and advancing interoperable data and correspondence advancements. An immense measure of connected objects will be installed universally in a couple of years. In the meantime, the utilization of MMBD has been developing colossally since recent years, while organizations are rapidly getting on what they remain to pick up. Actually, these two advances are affecting and molding one another. In spite of the fact that they emerge from various application situations, MMBD can be together utilized with machine learning, AI, factual, and other progressed procedures, models, and techniques to investigate or locate the profound incentive behind the immense information originated from IoT. Actually, the registering knowledge, including transformative calculation, neural systems, and the fuzzy hypothesis, is relied upon to assume a vital job for these issues. It is as yet one of the most scorching and most challenging fields to create novel processing knowledge for the reasonable situations concerned with the MMBD for future IoT. In this paper, we focus on one of the most important research domains in MMBD IoT, Energy Conservation. IoT devices communicate through the wireless communication medium and are expected to transmit information whenever needed. The battery life of IoT devices is an important concern for researchers and device manufacturers. Many exhaustive efforts have been put by researchers in this area. Since most IoT devices are usually deployed in remote and hostile environments out of reach for human users, it may not be possible to charge and recharge batteries frequently. Moreover, in MMBD IoT applications, a large volume of multimedia traffic needs to be processed, which consumes precious network resources such as bandwidth and energy. Thus, devising protocols for conserving energy of IoT devices in such environments has become a very interesting topic of research. There are various ways to achieve energy conservation in the MMBD IoT environment. Some of the popular research inclinations are designing energy-efficient communication protocols, developing of mechanisms that enable IoT devices to self-generate, recycle, store and harvest energy, and modifying underlying protocol stack of communication technologies to support energy efficiency. Our paper mainly focuses on the investigation of existing technologies and mechanisms in the above domains. We first present the need for energy conservation briefly and then discuss the key points of existing solutions for saving energy in IoT communications. At the end of the paper, we summarize our findings to describe the advantages and limitations of existing mechanisms and provide insights into possible research directions.

A paradigm that combines cloud computing and the Internet of Things (IoT) allows for more impressive services to be provided to users while addressing storage and computational resource issues in the IoT environments. This cloud-based IoT environment has been used in various industries, including public services, for quite some time, and has been researched in academia. However, various security issues can arise during the communication between IoT devices and cloud servers, because communication between devices occurs in open channels. Moreover, issues such as theft of a user's IoT device or extraction of key parameters from the user's device in a remote location can arise. Researchers interested in these issues have proposed lightweight mutual authentication key agreement protocols that are safe and suitable for IoT environments. Recently, a lightweight authentication scheme between IoT devices and cloud servers has been presented. However, we found out their scheme had various security vulnerabilities, vulnerable to insider, impersonation, verification table leakage, and privileged insider attacks, and did not provide users with untraceability. To address these flaws, we propose a provably secure lightweight authentication scheme. The proposed scheme uses the user's biometric information and the cloud server's secret key to prevent the exposure of key parameters. Additionally, it ensures low computational costs for providing users with real-time and fast services using only exclusive OR operations and hash functions in the IoT environments. To analyze the safety of the proposed scheme, we use informal security analysis, Burrows-Abadi-Needham (BAN) logic and a Real-or-Random (RoR) model. The analysis results confirm that our scheme is secure against insider attacks, impersonation attacks, stolen verifier attacks, and so on; furthermore, it provides additional security elements. Simultaneously, it has been verified to possess enhanced communication costs, and total bit size has been shortened to 3776 bits, which is improved by almost 6% compared to Wu et al.'s scheme. Therefore, we demonstrate that the proposed scheme is suitable for cloud-based IoT environments.

Information-centric networking (ICN) is a content-oriented network that uses content instead of traditional IP addresses, it facilitates the content retrieval and calculates downstream paths without the need of an optimal topology. ICN inherits mobility support features in its baseline design. Since the Internet of Things (IoT) faces major problems in supporting mobility management over IP, we believe that ICN would represent a major element in scalable IoT networks. This article discusses the use of ICN as a communication model in IoT environments, focusing on solving the mobility issue. Thus, we survey the relevant work that studies the merger between ICN and IoT, and describe the emergence, evolution, and state-of-the-art mobility approach. This article also presents discussions on major scalability challenges when using ICN as a communication enabler for mobile IoT and highlights key designs and guidelines.