Smart Home Network Research Articles

A Novel Smart Energy Theft System (SETS) for IoT-Based Smart Home

In the modern smart home, smart meters, and Internet of Things (IoT) have been massively deployed to replace traditional analogue meters. It digitalises the data collection and the meter readings. The data can be wirelessly transmitted that significantly reduces manual works. However, the community of smart home network is vulnerable to energy theft. Such attacks cannot be effectively detected since the existing techniques require certain devices to be installed to work. This imposes a challenge for energy theft detection systems to be implemented despite the lack of energy monitoring devices. This paper develops an energy detection system called smart energy theft system (SETS) based on machine learning and statistical models. There are three stages of decision-making modules, the first stage is the prediction model which uses multimodel forecasting system. This system integrates various machine learning models into a single forecast system for predicting the power consumption. The second stage is the primary decision making model that uses simple moving average (SMA) for filtering abnormally. The third stage is the secondary decision making model that makes the final stage of the decision on energy theft. The simulation results demonstrate that the proposed system can successfully detect 99.96% accuracy that enhances the security of the IoT-based smart home.

Anonymous mutual IoT interdevice authentication and key agreement scheme based on the ZigBee technique

Establishing end-to-end device authentication in Internet of Things (IoT) networks is challenging because of the heterogeneous nature of IoT devices. By covering different security properties, various authentication protocols have been introduced to ensure a certain level of security and privacy protection. In this paper, we propose an anonymous device-to-device mutual authentication and key exchange scheme based on the ZigBee technique, designed for a smart home network, an important domain in the IoT. The proposed protocol relies on symmetric encryption and enables IoT devices to authenticate in the network and agree on a shared secret session key when communicating with each other via a trusted intermediary (home controller). To achieve perfect forward secrecy, the session keys are changed frequently after every communication session. The proposed scheme achieves secure anonymous authentication with the unlinkability and untraceability of IoT devices’ transactions. The overhead and efficiency of the proposed scheme are analyzed and compared with other related schemes. In addition, the security of the scheme is evaluated using three different methods: informal analysis, formal analysis using the Burrows–Abadi–Needham logic (BAN), and a model check using the automated validation of internet security protocols and applications (AVISPA) toolkit.

Session-Key Establishment and Authentication in a Smart Home Network Using Public Key Cryptography

The development of the applications of Internet of Things (IoT) technology continues to grow steadily-one of the top applications being smart home environments. A smart home comprises digital devices and systems that operate inside a home to bring efficiency to home life. Devices with low computational ability and devices with high computational ability work together in a smart home network, and therefore, communication between devices needs to be secure. This article considers a lightweight and secure session-key establishment scheme for smart home networks and incorporates the Diffie-Hellman (DH) key exchange as an alternative method. A trusted service provider provides the algorithm parameters to the devices so that a public key can be established between the home gateway and a smart device. The proposed scheme is formally analyzed using Security Protocol Animator for Automated Validation of Internet Security Protocol and Applications (AVISPA).

SH-BlockCC: A secure and efficient Internet of things smart home architecture based on cloud computing and blockchain technology

The growing demand for human-independent comfortable lifestyle has emboldened the development of smart home. A typical keenly intellective home includes many Internet of things contrivances that engender processes and immensely colossal data to efficiently handle its users’ demands. This incrementing demand raises a plethora of concern cognate to a smart home system in terms of scalability, efficiency, and security. All these issues are tedious to manage, and the existing studies lack the granularity for surmounting them. Considering such a requisite of security and efficiency as a quandary at hand, this article presents a secure and efficient smart home architecture, which incorporates the blockchain and the cloud computing technologies for a cumulated solution. Because of the decentralized nature of blockchain technology, it can serve the processing services and make the transaction copy of the collected sensible user data from smart home. To ensure the security of smart home network, our proposed model utilizes the multivariate correlation analysis technique to analyze the network traffic and identify the correlation between traffic features. We have evaluated the performance of our proposed architecture using different parameters like throughput and discovered that blockchain is an efficient security solution for the future Internet of things network.

Software Defined Security Architecture for a Smart Home Networks Using Token Sharing Mechanism

Since the end of 2000, there are lot of revolutions occurs in the field of Internet of Things (IoT), that affect tremendously on the world internet infrastructure. Smart Home is a dwelling which incorporates the key electrical appliances of a home connected to each other in a network, so that it can be easily accessed through remote device. The complexity of a smart home lies in the fact that it comprises of many heterogeneous networks which works simultaneously in order to achieve common task. Since each and every network has some sort of vulnerability associated with it, the same lies with Smart home network. Each of the layers of a smart home architecture is associated with some vulnerability. These Vulnerability could be dangerous and can exploit the network if not properly handled. This Paper discussed a secure framework based on Token Sharing mechanism using Squid Authentication for Access Control in a Smart Home Networks.

ForChaos: Real Time Application DDoS Detection Using Forecasting and Chaos Theory in Smart Home IoT Network

Recently, D/DoS attacks have been launched by zombie IoT devices in smart home networks. They pose a great threat to network systems with Application Layer DDoS attacks being especially hard to detect due to their stealth and seemingly legitimacy. In this paper, we propose ForChaos, a lightweight detection algorithm for IoT devices, which is based on forecasting and chaos theory to identify flooding and DDoS attacks. For every time-series behaviour collected, a forecasting-technique prediction is generated, based on a number of features, and the error between the two values is calculated. In order to assess the error of the forecasting from the actual value, the Lyapunov exponent is used to detect potential malicious behaviour. In NS-3 we evaluate our detection algorithm through a series of experiments in flooding and slow-rate DDoS attacks. The results are presented and discussed in detail and compared with related studies, demonstrating its effectiveness and robustness.

A Security Protocol for Route Optimization in DMM-Based Smart Home IoT Networks

Smart home networks have been recognized as one of its representative important applications in the forthcoming 5G era. It is also expected that in 5G networks, future smart home services will be much powered by mobility management, which enables users to remotely access and control their in-home Internet of Things (IoT) sensors and appliances anywhere anytime any device. As a major solution, Distributed IP Mobility Management (DMM) can be considered because it addresses the limitation of the centralized approaches as well as its flat architecture is suit for 5G networks. Obviously, without being protected, mobility management can cause smart home systems to be vulnerable to various security threats. Especially, it is of paramount important to protect data traffic transmitted between user mobile devices and their in-home IoT appliances because they include users' sensitive and critical privacy information. Taking this into consideration, it is necessary to support secure route optimization, which allows the involved devices to directly communicate each other in secure way while minimizing possibility of information leakage during data transmission. According to our best knowledge, there is no study on securing route optimization for DMM networks. Motivated by this, we propose a secure route optimization protocol for DMM-based smart home systems. The proposed security protocol, composed of the route optimization initialization and handover phases, is designed to provide mutual authentication, key exchange, perfect forward secrecy, and privacy protection. Its security is thoroughly verified through the two formal security analysis tools, BAN-logic and Automated Validation of Internet Security Protocols and Applications (AVISPA). From the comparison analysis, it is shown that the proposed protocol is better than other standard protocols.

Supporting Asymmetric Transmission for Full-Duplex Smart-Home Networks

In smart home networks, the traffic is often asymmetric (i.e., the uplink traffic load of a node is not equal to its downlink traffic load). This paper is concerned with how to achieve asymmetric transmission for a full-duplex (FD) IoT network (where the AP and nodes are FD-enabled). Most existing related schemes considered a partial FD network consisting of an FD AP and half-duplex (HD) nodes and achieved asymmetric transmission via PHY-layer mechanisms such as power control. However, for an FD network, the MAC-layer scheduling mechanism might be better to achieve asymmetric transmission than the PHY-layer power-control mechanism which will introduce complex interference management. To this end, we propose a simple and novel MAC scheduling scheme called AT-MAC to support asymmetric transmission in an FD IoT network. In our design, we differentiate uplink-dominant (UD) and downlink-dominant (DD) nodes. Upon receiving a packet, a receiver determines whether to execute a reverse transmission to the peer or to initiate a new transmission to a third node according to the type of UD and DD nodes. Next, we develop a theoretical framework to evaluate the throughput of AT-MAC. The extensive simulations verify that our design is very effective (namely, it can achieve the asymmetric transmission, while fully utilizing the FD gain to maximize the system throughput and lower the packet delay) and our theoretical model is very accurate. This paper is very helpful for designing quality-of-service-oriented FD MAC protocols.

Remotely Access “My” Smart Home in Private: An Anti-Tracking Authentication and Key Agreement Scheme

Smart home is one of the key applications of the Internet of Things (IoT), which allows users to control the smart devices in their houses through the Internet. However, a smart home system also faces severe challenges in terms of privacy and confidentiality when users are allowed to remotely access it. Despite the recent research efforts on authentication schemes to improve the security aspects of a smart home, there are still unsolved problems. On the one hand, most of the existing schemes focus on secure authentication and communication via a trusted third party without taking its privacy leakage into consideration. On the other hand, many protocols enable the users to directly authenticate themselves to a large number of smart devices in the smart home network, which is often inefficient and inconvenient. To cope with these issues, we propose a smart home system model based on Internet services, like if this then that (IFTTT), and design an anti-tracking mutual authentication scheme with a key agreement element in it. Specifically, our scheme introduces an IFTTT home gateway as the control commands' executor and the security guard to allow a user to remotely access a smart home system privately. The proposed scheme employs the elliptic curves' cryptography (ECC) algorithm, nonces, XOR, and cryptographical hash functions to achieve mutual authentication with security features, such as anonymity and perfect forward security. The security analysis and performance comparison results demonstrate that the proposed scheme achieves secure and private authentication.

A New Layered Architecture for Future Big Data-Driven Smart Homes

In this paper, a new layered architecture is proposed for big data-driven processing and management of future smart homes. The proposed Representational State Transfer (REST)-based architecture includes seven layers: physical, fog-computing, network, cloud-computing, service, session, and application for efficient data exchange and processing tasks of future smart homes. The smart home physical layer includes all the sensing technologies and smart devices within the smart home, which monitors the home environment and its residents. The data of these sensors will be sent to the smart home fog-computing layer that can do limited data storage and processing. Then, all the required data will be sent to the cloud-computing layer using smart home network layer. The cloud-computing layer provides the scalable solution for data processing and storage. The processed data in the cloud-computing layer will be provided as the data-driven services to different smart home and third-party (e.g., smart city) applications via smart home service layer. Based on the proposed architecture, the applications will utilize the session layer and RESTFUL APIs to use the data-driven services of the smart home. The proposed smart home architecture can provide a ubiquitous and shared data environment as the key aspect of Internet-of-Things systems.

Modeling and Graph Analysis for Enhancing Resilience in Smart Homes

A number of network technologies applicable to home networking have emerged for various purposes in recent decades. Ethernet and IEEE 802.11 WLAN provide the home network backbone, along with a range of competing technologies for sensors and home automation such as IEEE 802.15.4/ZigBee, Z-Wave, and Bluetooth LE. Technologies in the home vary with respect to their importance. In this paper, we provide a model smart home network and analyze its graph-theoretic properties with an emphasis on the resilience of critical services and connections to the Global Internet. We consider both the network connectivity graph of nodes and links, and our novel technology interdependence graph.We explore the resilience of the network technologies in the smart home in light of complex technological interdependency. We analyze these graphs and discuss properties such as diameter, closeness, centrality, and k-connectedness. We explain why this analysis is a necessary pre-condition for understanding IoT-based smart-city resilience.

“Network Sentiment” Framework to Improve Security and Privacy for Smart Home

A Smart Home is characterized by the presence of a huge number of small, low power devices, along with more classical devices. According to the Internet of Things (IoT) paradigm, all of them are expected to be always connected to the Internet in order to provide enhanced services. In this scenario, an attacker can undermine both the network security and the user’s security/privacy. Traditional security measures are not sufficient, because they are too difficult to setup and are either too weak to effectively protect the user or too limiting for the new services effectiveness. The paper suggests to dynamically adapt the security level of the smart home network according to the user perceived risk level what we have called network sentiment analysis. The security level is not fixed, established by a central system (usually by the Internet Service Provider) but can be changed with the users cooperation. The security of the smart home network is improved by a distributed firewalls and Intrusion Detection Systems both to the smart home side as to the Internet Service Provider side. These two parts must cooperate and integrate their actions for reacting dynamically to new and on going threats. Moreover, the level of network sentiment detected can be propagate to nearby home networks (e.g., the smart home networks of the apartments inside a building) to increase/decrease their level of security, thus creating a true in-line Intrusion Prevention System (IPS). The paper also presents a test bed for Smart Home to detect and counteract to different attacks against the IoT sensors, Wi-Fi and Ethernet connections.

Machine learning based privacy-preserving fair data trading in big data market

In the era of big data, the produced and collected data explode due to the emerging technologies and applications that pervade everywhere in our daily lives, including internet of things applications such as smart home, smart city, smart grid, e-commerce applications and social network. Big data market can carry out efficient data trading, which provides a way to share data and further enhances the utility of data. However, to realize effective data trading in big data market, several challenges need to be resolved. The first one is to verify the data availability for a data consumer. The second is privacy of a data provider who is unwilling to reveal his real identity to the data consumer. The third is the payment fairness between a data provider and a data consumer with atomic exchange. In this paper, we address these challenges by proposing a new blockchain-based fair data trading protocol in big data market. The proposed protocol integrates ring signature, double-authentication-preventing signature and similarity learning to guarantee the availability of trading data, privacy of data providers and fairness between data providers and data consumers. We show the proposed protocol achieves the desirable security properties that a secure data trading protocol should have. The implementation results with Solidity smart contract demonstrate the validity of the proposed blockchain-based fair data trading protocol.

A certificateless signcryption scheme for smart home networks

SummarySmart home networks (SHNets) are based on the Internet of Things (IoT) and provide users with a highly intelligent home life. In recent years, SHNets have become more and more popular. In SHNets, a large amount of data interactions are needed. These data related to the privacy of users may be subject to attacks such as eavesdropping attacks, replay attacks, and mobile phone stolen attacks. Privacy protection and communication security in smart home networks have been widely studied by many scholars. However, most of the existing user authentication in current researches focus on identity‐based authentication, where the encryption protocols are divided into two steps: the signing step and the encryption step. In this paper, a certificateless signcryption scheme for SHNets is proposed which can provide biometric‐based user identity authentication. The security and performance analyses show that our scheme is efficient and secure.

Hybrid Secure Authentication and Key Exchange Scheme for M2M Home Networks

In this paper, we analyzed Sun et al.’s scheme which proposes an M2M (Machine-to-Machine) secure communication scheme by using existing TD SCMA (Time Division-Synchronous Code Division Multiple Access) networks. They offer a password-based authentication and key establishment protocol for mutual authentication. Moreover, their proposed secure channel establishment protocol uses symmetric cryptography and one-way hash algorithms and they considered using their protected channel model for mobile users and smart home networks. In this paper, we propose to complete the missing part of Sun et al.’s scheme. This can occur by addressing privacy-preserving and message modification protection. Moreover, improvements can be made to MITM (Man-In-The-Middle) attack resistance, anomaly detection and DoS (Denial-of-Service) attacks with timing. ECDH (Elliptic Curve Diffie Hellman) cryptography based protected cipher-key exchange operation used on initial setup and key-injection operations to provide secure user registration, user password change and home gateway network join phases. We simulated both the proposed and Sun et al.’s schemes. We analyzed Sun et al.’s scheme for performance, network congestion and resource usage. Missing privacy-preserving was analyzed and compared with the GLARM scheme, and the storage cost of each phase was analyzed according to Ferrag et al.’s survey proposal. In Sun et al.’s scheme, future work for the security architecture of the home network is related to Li et al.’s protocol being implemented in our proposed design.

SHSec: SDN based Secure Smart Home Network Architecture for Internet of Things

To address the challenges of flexible device utilization, heterogeneous device interoperability, and security enhancement in smart homes, this paper proposes a new architecture for the software defined network to realize secure smart home environment (SHSec). SHSec concentrates on the capabilities required to deliver a flexible generic platform and the modularity of open-source service creation components for a user-friendly smart home by adopting the traditional software-defined network concept. It offers an infrastructure that is agile, modular and, most importantly, secure. To avoid many manual reviews and recommendations by administrators, security should automatically adapt to any threat in the immediate environment. We simulated the proposed model to test network performance and feasibility during link failures and switching in a normal environment. We also evaluated the performance of our proposed model based on various metric parameters. The results of the simulation show that SHSec management is able to detect and mitigate attacks, and can also be used to secure the system, ensure user security, and improve the heterogeneous local network. The proposed model achieves an accuracy of 89.9% and a sensitivity of 91.1% while predicting malicious events.

Is the Time Ripe? How the Value of Waiting and Incentives Affect Users’ Switching Behaviors for Smart Home Devices

Product-related and market-related uncertainties often cause users to defer from switching to new IT devices. There is a value of waiting (VoW) for users because waiting allows them to collect more information. At the same time, many IT switching decisions are increasingly complex due to increased connectivity and the resulting interdependencies between jointly used devices. Therefore, switching decisions for connected devices not only need to consider the new device in isolation, but must also account for the potential benefits from internally or externally connecting the device with other devices. Although crucial for users and providers alike, existing models cannot explain whether and when users switch in such connected environments. We focus on connected Smart Home Devices (SHDs) and simulate users’ actual switching timing based on a real options model which combines switching and deferral concepts in a context-specific setting. We examine how Smart Home Network (SHN) density influences switching and how providers can use incentives to accelerate switching to foster product diffusion. The findings show an accelerating effect of connectivity and a deferring effect of uncertainty on actual switching timing. We also learn that SHD providers should focus more on immediate than on delayed incentives to promote product diffusion, since the latter can also have undesired effects. Interestingly, external connectivity has almost no influence on decision timing in scenarios with highly dense SHNs, leading to further key implications for SHD providers.

A Smart Home Gateway Platform for Data Collection and Awareness

Smart homes have attracted much attention due to the expanding of IoT and smart devices. In this article, we propose a smart gateway platform for data collection and awareness in smart home networks. A smart gateway will replace the traditional network gateway to connect the home network and the Internet. A smart home network supports different types of smart devices, including in-home IoT devices, smartphones, smart electric appliances, and so on. A traditional network gateway is not capable of providing quality of service measurement, user behavioral analytics, or network optimization. Such tasks are traditionally performed with measurement agents such as optical splitters or network probes deployed in the core network. Our proposed platform is a lightweight plug-in for the smart gateway to accomplish data collection, awareness, and reporting. While the smart gateway is able to adjust the control policy for data collection and awareness locally, a cloud-based controller is also included for more refined control policy updates. Furthermore, we propose a multi-dimensional awareness plug-in framework to achieve accurate data awareness at the smart gateway. The efficiency of data collection and accuracy of data awareness of the proposed platform is demonstrated based on tests using actual data traffic from a large number of smart home users.

Secure Remote User Authenticated Key Establishment Protocol for Smart Home Environment

The Information and Communication Technology (ICT) has been used in wide range of applications, such as smart living, smart health and smart transportation. Among all these applications, smart home is most popular, in which the users/residents can control the operations of the various smart sensor devices from remote sites also. However, the smart devices and users communicate over an insecure communication channel, i.e., the Internet. There may be the possibility of various types of attacks, such as smart device capture attack, user, gateway node and smart device impersonation attacks and privileged-insider attack on a smart home network. An illegal user, in this case, can gain access over data sent by the smart devices. Most of the existing schemes reported in the literature for the remote user authentication in smart home environment are not secure with respect to the above specified attacks. Thus, there is need to design a secure remote user authentication scheme for a smart home network so that only authorized users can gain access to the smart devices. To mitigate the aforementioned isses, in this paper, we propose a new secure remote user authentication scheme for a smart home environment. The proposed scheme is efficient for resource-constrained smart devices with limited resources as it uses only one-way hash functions, bitwise XOR operations and symmetric encryptions/decryptions. The security of the scheme is proved using the rigorous formal security analysis under the widely-accepted Real-Or-Random (ROR) model. Moreover, the rigorous informal security analysis and formal security verification using the broadly-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool is also done. Finally, the practical demonstration of the proposed scheme is also performed using the widely-accepted NS-2 simulation.

A Hypergraph-Based Blockchain Model and Application in Internet of Things-Enabled Smart Homes

With the fast development and expansion of the Internet of Things (IoT), billions of smart devices are being continuously connected, and smart homes, as a typical IoT application, are providing people with various convenient applications, but face security and privacy issues. The idea of Blockchain (BC) theory has brought about a potential solution to the IoT security problem. The emergence of blockchain technology has brought about a change of decentralized management, providing an effective solution for the protection of network security and privacy. On the other hand, the smart devices in IoT are always lightweight and have less energy and memory. This makes the application of blockchain difficult. Against this background, this paper proposes a blockchain model based on hypergraphs. The aims of this model are to reduce the storage consumption and to solve the additional security issues. In the model, we use the hyperedge as the organization of storage nodes and convert the entire networked data storage into part network storage. We discuss the design of the model and security strategy in detail, introducing some use cases in a smart home network and evaluating the storage performance of the model through simulation experiments and an evaluation of the network.