An enhanced security framework for home appliances in smart home

The dramatic advancement of Internet of Things technology and smart services has encouraged the integration of smart home and healthcare service. Despite various research studies on the technology of smart home healthcare services, it is essential to approach those services from the service experience perspective. Moreover, it would be significant to consider the context and environment of smart services, namely, “smart servicescapes,” as they can influence users’ perceptions and experiences. With this background, the aim of this study was to examine the smart servicescape framework that was developed based on the smart home services in the prior study from the domain of smart home healthcare services and to ameliorate the framework to better reflect the characteristics of smart services.During the qualitative analysis of 21 user‐scenario movie clips on smart home healthcare services, the smart servicescape elements were recategorized and relabeled, and the structure of smart servicescape framework was modified. The values of the improved smart servicescape framework can be identified in two aspects. First, the framework can demonstrate the characteristics of smart services, namely, the omnipresence of Datascape and Connection infra and the mediating role of artificial intelligence. Second, this framework can be used to establish design requirements about service elements, relationships, and interactions when the smart service experiences, including smart home healthcare, are designed.

Internet of Thing (IoT) is going to make such a world where physical things (smart home appliances, and smart watches etc.) revolutionized the information networks and services providing systems which provide innovative and smart services to human. With smart home technology, our living area is becoming more comfortable and convenient. Smart home technology provides automated, intelligent, smart, innovative and ubiquitous services to residential users through Information Communication Technology (ICT). Due to internet-connected, dynamic and heterogeneous nature of smart home environment creates new security, authentication and privacy challenges. In this paper, we investigate security attacks in smart home and evaluate their impact on the overall system security. We identified security requirements and solutions in the smart home environment. Based on several scenarios, we suggest to set security goals for the smart home environment. Based on historical data, we forecast security attacks (like malware, virus etc.) and estimated that how many attacks are expected to be launched in coming years.

The recent advancement in home automation technologies and inter-connectivity of smart appliances has contributed immensely in developing intelligent home environment. The complex smart home environment consists of smart devices from different vendors having different configuration and communication standards that introduce the problem of a heterogeneous subsystem in a smart home. A need is emerging for a central management system to control all these various devices. In this paper, we propose an action-based framework that acts as a middleware between the user and smart appliances which allow the user to control these heterogeneous devices in a federated manner. The proposed framework is based on a controller, for accepting user input and sending instructions to the intended smart devices. Framework maintains the integrity of an instruction send to the device and employs the mechanism so that only authentic user can access them. We also incorporate Human System Interaction (HSI) in our framework, by developing an Android application which receives input in the form of motion gestures, to fulfill the human-centric interaction requirements of the user to communicate with the smart home appliances. We evaluate the performance of our framework by implementing the controller in a local home network and the cloud.

The proliferation of smart devices in recent years has led to novel smart home applications that upgrade traditional home appliances to intelligent units and automatically adapt their services without human assistance. In a smart home system, a central gateway is required to coordinate the functions of various smart home devices and allow bidirectional communications. However, the gateway may cause leakage of sensitive information unless proper privacy protections are applied. In this work, we first introduce a smart home model based on fog computing and secured by differential privacy. Then, we apply a personalized differential privacy scheme to provide privacy protection. Furthermore, we consider a collusion attack and propose our differential privacy model called APDP based on a modified Laplace mechanism and a Markov process to strengthen privacy protection, thus resisting the attack. Lastly, we perform extensive experiments based on the real-world datasets to evaluate the proposed APDP model.

This chapter presents the concept of Smart Home, describes the Smart Home networking technologies and discusses the main issues for ensuring security in a Smart Home environment. Nowadays, the integration of current communication and information technologies within the dwelling has led to the emergence of Smart Homes. These technologies facilitate the building of Smart Home environments in which devices and systems can communicate with each other and can be controlled automatically in order to interact with the household members and improve the quality of their life. However, the nature of Smart Home environment, the fact that it is always connected to the outside world via Internet and the open security back doors derived from the household members raise many security concerns. Finally, by reviewing the existing literature regarding Smart Homes and security issues that exist in Smart Home environments, the authors envisage to provide a base to broaden the research in Smart Home security.

Typical Internet of Things (IoT) and smart home environments are composed of smart devices that are controlled and orchestrated by applications developed and run in the cloud. Correctness is important for these applications, since they control the home’s physical security (i.e. door locks) and systems (i.e. HVAC). Unfortunately, many smart home applications and systems exhibit poor security characteristics and insufficient system support. Instead they force application developers to reason about a combination of complicated scenarios—asynchronous events and distributed devices. This paper demonstrates that existing cloud-based smart home platforms provide insufficient support for applications to correctly deal with concurrency and data consistency issues. These weaknesses expose platform vulnerabilities that affect system correctness and security (e.g. a smart lock erroneously unlocked). To address this, we present OKAPI, an application-level API that provides strict atomicity and event ordering. We evaluate our work using the Samsung SmartThings smart home devices, hub, and cloud infrastructure. In addition to identifying shortfalls of cloud-based smart home platforms, we propose design guidelines to make application developers oblivious of smart home platforms’ consistency and concurrency intricacies.

The popularity of smart home systems has greatly increased over the past several years, which provide convenience, automation, and control over various areas of daily life at home. However, these technologies still have issues with scalable user experience, mainly because there aren’t any engaging and intuitive user interfaces. Incorporating pervasive virtual reality (VR) interfaces into smart home systems is the unique strategy proposed in this study to improve scalable user experience. The study’s goal is to use VR technology to develop engaging and simple user interfaces that seamlessly integrate with the actual surroundings of a smart home. Users can engage with their smart home appliances and services through a mixed-reality experience in which virtual items and information are seamlessly incorporated into their environment by donning portable VR headsets. This application considers various difficulties related to developing Ambient Assisted Living (AAL) solutions, including unique characteristics of each end user, appliance, technology, deployment, and data-sharing problems. The Smart Home Systems take advantage of Semantic Web technologies integration abilities and their capacity facing represent significant information into legal models. A virtual reality application called Smart Home Systems allows for residential settings’ setup and customization in AAL systems. Additionally, it effectively uses VR technology to streamline the creation of specialized AAL settings. The application and underlying framework were evaluated for each through two scenarios: designing a home setting specifically for specific scalable user categories.

Different kinds of system components including hardware elements, software components, network connections, and sensors are required to cooperate with each other to provide various services in smart home. In recent years, we must consider how to reduce the environmental burden by energy management and to support human's life allow for a comfortable lifestyle in an aging society. This paper proposes a concept of an agent-based middleware for smart home that consists of various home electric appliances and various sensors. The agents acquire variety of information, data, etc. from the smart home environment and store/manage them in a methodical manner. In this paper, we describe the concept, design, and initial implementation based on our agent-based middleware. We implemented initial applications related to multimedia and energy management to apply for smart home.

Automatic indoor human tracking has attracted noticeable research concern recently due to the increasing demands for enhancing the majority of the offered services within smart home environment. Many human tracking approaches have been suggested and discussed. However, the problem of reliable human tracking remains untackled. The aim of this paper is to develop and implement an advanced tracking approach using smart floor that is capable of detecting and tracking people accurately and reliably. The proposed approach can be used as infrastructure for various smart home services. A proof-of-concept testbed has been designed, implemented, and validated via several case studies.

The Internet of things is a new technological revolution following the computer and Internet. It aims to connect all physical objects existing in the world and forms a network with everything. In recent years, smart home gradually enters into our life. Smart home uses the Internet of things technology to connect all kinds of devices in the home, to achieve a smart home environment. Although the development of smart home has brought a qualitative leap to people’s life, there are many problems in security. Privacy security is one of the challenges to the smart home environment. Attackers can intrude various smart devices in the smart home environment, to achieve the purpose of stealing users’ personal information and privacy. Among these devices, smart cameras are the most intruded frequently. Since many cameras are installed in users’ homes to achieve real-time monitoring of the environment, but the existence of these cameras provides a channel to get information for attackers. In recent years, the leak of video privacy is emerging in an endless stream. According to the researches about privacy protection, this paper proposes a new scheme to selectively encrypt the video captured by the cameras through machine learning technology, so as to protect the personal privacy of users and improve the security of the smart home environment.

Smart homes are increasingly becoming popular because they make living comfortable, enjoyable, and secure. People can remotely control various aspects of their smart home environments. However, smart home appliances can pose threats to privacy. The reason is that smart appliances collect and store sensitive information, and if hackers gain access to this information, user privacy may be breached. It is difficult for users to constantly monitor and determine which data is sensitive to them and which one is not. Also, a user’s identity can be leaked during sharing of information with different service providers such as health care providers and utility companies. In this paper we address one important privacy issue in smart homes, which is lack of users’ control over their desired privacy. We propose a privacy decision framework which considers this problem. In this framework, active learning (machine learning) technique is used to help users detect sensitive information according to their privacy preferences.

The electric mobility dissemination is forcing the adoption of new technologies and operation paradigms, not only focusing on smart grids, but also on smart homes. In fact, the emerging technologies for smart homes are also altering the conventional grids toward smart grids. By combining the key pillars of electric mobility and smart homes, this paper characterizes the paradigms of the electric vehicle (EV) in smart homes, presenting a review about the state-of-the-art and establishing a relation with future perspectives. Since the smart home must be prepared to deal with the necessities of the EV, the analysis of both on-board and off-board battery charging systems are considered in the paper. Moreover, the inclusion of renewable energy sources, energy storage systems, and dc electrical appliances in smart homes towards sustainability is also considered in this paper, but framed in the perspective of an EV off-board battery charging system. As a pertinent contribution, this paper offers future perspectives for the EV in smart homes, including the possibility of ac, dc, and hybrid smart homes. Covering all of these aspects, exemplificative and key results are presented based on numerical simulations and experimental results obtained with a proof-of-concept prototype.

Method A literature study was conducted to examine cyber security in Smart Homes, focusing on vulnerability assessment, privacy, threat mitigation, and policy regulations. Not only smartphones have advanced technology, but smarthomes or smart homes are a technological development that allows users to control functions such as security access, temperature, lighting and home theater remotely. This is the basis for the need for user-friendly cybersecurity measures, considering the rapid adoption of IoT devices in smart homes. This literature review highlights challenges related to inconsistent regulations and varying technology standards. Significant gaps exist in user awareness, device interoperability, data privacy, and security protocols. A multidisciplinary approach that brings together technology, policy, and social science stakeholders is recommended to build a secure, efficient, and privacy-preserving smart home ecosystem

The fourth industrial revolution put new processes on the rails of automation in industry, healthcare, home and other areas of human life through the mass integration of the concept of the Internet of Things into these areas. At the same time, these processes are not bypassed by home automation systems or smart homes. A smart home is defined as a system of interconnected sensors, actuators, and other devices that are networked together with computer systems and controlled by appropriate software. This connection allows to collect, share and analyze data, which helps to increase comfort, automation and control over the parameters of the house. However, along with the obvious advantages and conveniences of rooting home automation systems, this concept leaves a number of potential security bottlenecks for attackers. Data collected by smart devices is always point of interest to hackers and hijackers of confidential information.Third-party access to data collected by smart devices can lead to a variety of emergencies, the degree of danger of which will depend solely on the wish of the owner of the intercepted data. The paper proposes an intelligent system for detecting anomalies and identifying smart home devices based on the collective communication of smart homes. The concept of the system is based on the benefits of combining smart homes into a social network in terms of improving the security of both a single smart home and the entire social network of combined smart homes. Detection of anomalies and identification of devices in each of the smart homes is based on monitoring network traffic and forming profiles of smart devices that are present in the network. Profiles consist of a set of features that describe the behavior of smart devices on the network, including the period of activity of the device and the period of its sleep. Based on this, a whitelist of allowed profiles of devices operation in the cluster is formed. To verify the presence of a profile in the whitelist the Random Forest algorithm was used. A key feature of the system is the communication of smart home clusters with each other to exchange information about the available smart device profiles in the whitelists of each cluster.

Smart home devices are vulnerable to attacks that put their users’ security at risk. Vulnerabilities are discovered very frequently and can expose these devices through unsecured services. Meanwhile, the lack of standardisation in upgrade methods makes smart homes a potentially vulnerable environment. Furthermore, many manufacturers release their products and then abandon them, refusing to support security updates. As a result, security updates are needed to deal with the emergence of new attacks. There are several proposals to promote security in smart homes. However, there are rare solutions where changes for security purposes occur with little or no human intervention. This paper presents UP-Home, a self-adaptive solution that manages the security of smart homes. UP-Home aims to ensure that smart home devices meet the security requirements set by industry standards. The solution can continually identify and mitigate smart home security vulnerabilities. With autonomous computing techniques, UP-Home seeks to ensure the self-protection of devices and, consequently, the entire smart home. With the UP-Home evalu-ation, it was possible to notice significant improvements in the security of the smart home without any human intervention.