Centralized framework for controlling heterogeneous appliances in a smart home environment

Since the end of 2000, smartphones have explosively spread and have made people’s lives plentiful. With the start of smartphones, new smart devices, including tablet PCs, smart TVs, smart refrigerators, and smart air conditioners, have emerged, expanding their areas from individuals to business and home. These days, smart home service has drawn a lot of attention as a human-centric service. It is the environment where home appliances and other smart devices are connected to internet in order for user service and experience. The current smart home service is simply based on wireless home network to execute the function of connected home. The service has no smart home security so that it is possible for users to suffer a financial loss caused by information leakage or home appliance hacking. Therefore, to apply smart home service to surroundings, it is necessary to take into account security of smart devices. In this paper, we propose an enhanced security framework for smart devices in a smart home environment. The security framework provides the integrity system using the self-signing and access control techniques for preventing the security threats such as data modification, leakage and code fabrication.

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.

Session Initiation Protocol (SIP) has been proposed for multimedia services and wide-area connectivity in smart home environments (SHEs). An important issue for SIP deployment in SHEs is network address translator (NAT) traversing. SIP and Real-time Transport Protocol (RTP) packets are delivered between an SHE (i.e., private IP network) and Internet (i.e., a public IP network) through an NAT function of a home gateway, and the NAT translates the IP/transport layer address and port number but leaves the application layer content unchanged. This results in inconsistency between the IP addresses/port numbers in the IP/transport layers and those in the SIP layer. To resolve this issue, we describe six solutions including static route, UPnP, STUN, ICE, ALG, and SBC. Then we compare these solutions in terms of smart home appliance (SHA) modification, scope of NATs supported, multilayer NAT traversal, ease of configuration, security issue, and time complexities.

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.

A smart home is a home environment enriched with sensing, actuation, communication and computation capabilities which permits to adapt it to inhabitants preferences and requirements. Establishing a proper strategy of actuation on the home environment can require complex computational tasks on the sensed data. This is the case of activity recognition, which consists in retrieving high-level knowledge about what occurs in the home environment and about the behaviour of the inhabitants. The inherent complexity of this application domain asks for tools able to properly support the design and implementation phases. This paper proposes a framework for the design and implementation of smart home applications focused on activity recognition in home environments. The framework mainly relies on the Cloud-assisted Agent-based Smart home Environment (CASE) architecture offering basic abstraction entities which easily allow to design and implement Smart Home applications. CASE is a three layered architecture which exploits the distributed multi-agent paradigm and the cloud technology for offering analytics services. Details about how to implement activity recognition onto the CASE architecture are supplied focusing on the low-level technological issues as well as the algorithms and the methodologies useful for the activity recognition. The effectiveness of the framework is shown through a case study consisting of a daily activity recognition of a person in a 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.

Smart homes are an emerging paradigm of Internet of Things (IoT) in which users can remotely control various home devices via the internet anytime and anywhere. However, smart home environments are vulnerable to security attacks because an attacker can inject, insert, intercept, delete, and modify transmitted messages over an insecure channel. Thus, secure and lightweight authentication protocols are essential to ensure useful services in smart home environments. In 2021, Kaur and Kumar presented a two-factor based user authentication protocol for smart homes using elliptic curve cryptosystems (ECC). Unfortunately, we demonstrate that their scheme cannot resist security attacks such as impersonation and session key disclosure attacks, and also ensure secure user authentication. Moreover, their scheme is not suitable in smart home environments because it utilizes public-key cryptosystems such as ECC. Hence, we design a secure and lightweight three-factor based privacy-preserving authentication scheme for IoT-enabled smart home environments to overcome the security problems of Kaur and Kumar’s protocol. We prove the security of the proposed scheme by using informal and formal security analyses such as the ROR model and AVISPA simulation. In addition, we compare the performance and security features between the proposed scheme and related schemes. The proposed scheme better provides security and efficiency compared with the previous schemes and is more suitable than previous schemes for IoT-enabled smart home environments.

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.

In the future, homes will have numerous intelligent communicating devices, and such smart home needs to exhibit highly adaptive behaviors to meet the inhabitants changing personal requirements and operational context of environment. To achieve this, smart home application should focus on the inhabitant¿s goal or task in diverse situations, but not the various complex devices and services. This paper proposes a context-dependent task approach to meet the challenge, and introduces case based reasoning as the reasoning method which solves the problem to discover a task in smart home environment.

Time-varying multi-objective smart home appliances scheduling using fuzzy adaptive dynamic SPEA2 algorithm

A review of smart home applications based on Internet of Things

As smart building becomes increasingly popular, it enables many interesting applications, such as smart lock, elderly monitoring and remote healthcare.This paper will introduce one sub-system in the smart building: smart power system.This smart power system consists of an Android application, a cloud server and a smart socket.In addition, human-device interaction methods in this system are studied.

In recent years, many internet of things (IoT) platforms based on cloud computing have been proposed for general purpose applications. Though many similar platforms or schemes particular for smart home applications have been proposed, many issues such as multiple connectivity due to diversity of smart home applications and supporting for real-time operations have not been solved properly. We propose a smart home foundation scheme adopting open source hardware devices and cloud computing technology to explore these issues. In this scheme, Arduino Yun-based smart hardware devices can connect to the cloud server through multiple network connectivity. By utilising Spacebrew technology, a bidirectional real-time communication can be implemented which provides a solid foundation for real-time operations of smart home. The core functions of the scheme are exposed through RESTful web services in a SaaS (short for software as a service) manner and can be called by various clients and other applications. Demonstrative applications show that the proposed smart home foundation scheme provides adequate support for creating smart home applications based on wireless open source hardware devices.

Internet of Things (IoT) devices and applications are growing for smart home use cases. Although various security risks have been identified in smart home devices, studies reveal that the majority of the smart home devices released in the market have multiple security vulnerabilities and, in many cases, no security mechanisms are implemented. These vulnerabilities of smart home networks are mostly attributed to user unawareness of security. Many users are not aware and do not have the technical skills or knowledge of what is happening on their devices in their smart home environment. When an intruder connects to their device or takes advantage of it, users are unaware of such a connection. This paper introduces a configuration tool that helps users to create device interaction rules that are added to an existing Network Intrusion Detection System (NIDS) in the smart home network. These rules generate alarms that alert the user if unwanted interaction takes place between their devices or from an external network, and in this way increases user awareness of the security of their smart home network.

The adoption of smart home appliances has transformed household chores, offering enhanced convenience and efficiency. This study explores consumer behaviour among housewives in Melaka regarding the use of smart home appliance, with a focus on understanding factors that influence customer satisfaction. As smart home appliances integrate advanced technologies such as automation, remote control, and energy efficiency, it is essential to examine how housewives perceive and interact with these appliances. The study assesses the level of adoption, key determinants of satisfaction, and the overall impact of smart home appliance on daily household tasks. A descriptive research design and a quantitative research method were employed, utilizing a structured questionnaire distributed to 134 housewives in Melaka. Data collection and analysis were conducted using the Statistical Package for the Social Sciences (SPSS) Version 27. The research investigates the relationship between perceived ease of use, usefulness, cost, and customer satisfaction. Findings from this study provide insights into how smart home appliances influence consumer experiences, guiding manufacturers and marketers in improving product design, usability, and customer support services. By aligning smart appliance features with the specific needs and expectations of housewives, businesses can enhance customer satisfaction and promote the widespread adoption of smart home technologies.