UP-Home: A Self-Adaptive Solution for Smart Home Security

How are people using current smart home technologies, and how do they conceptualize future ones that are more interconnected and more capable than those available today? We deployed an online survey study to 150 participants to investigate use of and opinions about smart speakers, home robots, virtual assistants, and other smart home devices. We also gauged how impressions of connected smart home devices are shaped by the way the devices interact with one another. Through a mixed-methods qualitative and quantitative approach, we found that people mostly use single devices for single functions, and have simple and brief interactions with virtual assistants. However, they imagine their future devices to have more control over the physical environment (i.e., interact with each other) and envision them interacting with people in more socially complex ways. These findings motivate design considerations and research directions for connected smart home technologies.

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

Lightweight anonymous authentication protocol for resource-constrained smart home devices based on elliptic curve cryptography

Smart home technology is gaining popularity among end-users, as it allows them to remotely control a variety of devices in their homes. Such systems have obvious benefits in terms of automation, but at the same time pose significant threats to home owners if the underlying communications are not secure. To this end, we introduce a novel security protocol that simplifies the pairwise authentication and key exchange among smart home devices. The protocol leverages identity-based cryptography (IBC), thus relaxing the requirement for storing and managing public key certificates. Furthermore, to mitigate the risks associated with centralized key generation in IBC, we opt to generate the private keys in a distributed manner, involving all smart devices. We implemented our protocol on Raspberry Pi 3 devices and demonstrate its efficiency in terms of both computational and communication cost.

The wireless transmission of home area networks contributes to the vulnerabilities of smart homes. As a result, smart homes are vulnerable to malicious attacks like eavesdropping. To secure the transmissions, secret keys should be established for smart home devices. In practical smart home applications, smart home devices might be resource-constrained devices. Thus, the lightweight key establishment schemes are preferred. Typically, lightweight physical layer key extraction schemes can be employed by the smart home devices. However, the key generation rate of the schemes is low. To improve the key generation rate, in this paper we propose an adaptive physical layer key extraction scheme for smart homes by making use of the Received Signal Strength (RSS). Specifically, in our scheme, two smart home devices collect the RSS measurements by probing with each other. Then, the collected measurements are quantized by running the proposed Self-adaptive Lossless Quantization algorithm. Completing these operations, the two smart home devices can obtain the secret key. In our scheme, we design the self-adaptive lossless quantization algorithm to improve the key generation rate. To show the practicality of the new scheme, we implement it using the Ralink WiFi cards. Additionally, we analyse the performance of our scheme and compare it with that of other related works.

At home and abroad, smart home, after more than ten years development is getting more and more widely welcomed. Smart home technology is developing rapidly, and with the emergence of IPv6, smart home based on IPv6 is becoming a trend. Meanwhile, security and privacy protection of smart home is receiving more attention. Although IPv6 is more secure than IPV4, there are still issues of privacy loss. In this paper, we focus on the security and privacy protection of smart home based on IPv6 and propose two different solutions respectively, that is, security and privacy protection based on trust as well as that based on strategy. These two solutions achieve security and privacy protection via model about trust and strategy mechanism respectively. On the basis of these two solutions, a framework of security and privacy protection system of smart home is designed. Through the system we designed, the security and privacy protection of smart home based on IPv6 is achieved.

Background:Technological advances in the smart home have created new opportunities for supporting digital citizens’ well-being and facilitating their empowerment but have enabled new types of complex online harms to develop. Recent statistics have indicated that ‘smart’ technology ownership increases yearly, driven by lower costs and increased accessibility. Research on smart homes has also grown, focusing on technology perspectives at the expense of a user-centric approach sensitive to the smart home’s harms, risks, and vulnerabilities. Objective:This scoping review addresses the information gap by underscoring the scope of literature that exists regarding complex online harms, vulnerabilities, and risks associated with smart home technologies and citizens’ agency. The goal is to understand the state of knowledge, gaps in the literature, and areas for future study. The importance and originality of this paper lie in its interdisciplinary review and approach. It is hoped that this research will contribute to a deeper understanding of complex online harms in the smart home. Design:Three online databases were utilised to identify papers published between 2017 and 2022, from which we selected 235 publications written in English that addressed harms, risks, vulnerabilities, and agency in the smart home context. This allowed us to map contemporary literature to reveal significant gaps in our understanding of the complex online harms affecting smart home users and identify opportunities for further research. Results:This review identified emerging themes of ‘risks’, ‘vulnerabilities’, and ‘harms’ in that order of frequency within the literature on smart homes. The usage of terms is skewed towards computing science and information security, which comprised the majority of the literature at 54.6%. Human–computer interaction papers contributed 24.4%, while social sciences accounted for 16.2%. Conclusion:Risks, harms and vulnerabilities within smart home ecosystems and IoTs are ongoing issues with complexities that necessitate research. Privacy, security, and well-being are key themes that embody the scope of complex harms affecting smart home devices in the broad literature. This review establishes disciplinary research gaps, especially in user-centred perspectives, due to a heavy technology focus in the existing literature. Therefore, further research is needed to address emergent risks, harms and vulnerabilities of smart home devices and understand how user agency and autonomy can complement the design, interface, and socio-technical aspects of smart home systems.

The rapid adoption of Internet of Things (IoT) devices in smart homes has led to growing security vulnerabilities, primarily due to the limitations of traditional, static access control mechanisms. This paper presents a novel, dynamic access control policy that leverages the immutable and transparent nature of Blockchain technology, specifically Ethereum, along with machine learning algorithms to enhance security measures. By integrating machine learning algorithms like Support Vector Machines (SVM) and Neural Networks, the proposed system can adapt and respond to changing behavioural patterns and potential threats in real time. Additionally, a caching mechanism implemented on the Ethereum Blockchain is introduced to optimize system performance and reduce latency. Experimental results demonstrate significant improvements in access control security, system efficiency, and adaptability. The findings of this paper not only contribute to the advancement of secure access control policies for IoT smart homes but pave the way for future research in integrating Blockchain and machine learning for robust and scalable IoT security solutions.

Home automation system has achieved an enormous reputation in recent years, as day-to-day life is getting simpler due to the speedy growth of modern technology. Various implemented systems have been offered in the sphere of Home Automation but have apparently failed to provide cost-effective solutions for the same. In this paper, we provide a low-cost smart Home Automation and Security System (HASS) using Wireless Fidelity (Wi-Fi), and Bluetooth. These materialize the concept of internetworking of smart devices. A Wireless Sensor Network (WSN) based on Wi-Fi is considered to monitor and control the smart environment, safety as well as electrical parameters of a smart interconnected home. The Android application-based Graphical User Interface (GUI) on a Smartphone is used to give facility to users for seamless control over the devices in a smart home. It may also consist of home security for example access control and alarm systems. When connected to the Internet, home devices are an important element of the Internet of Things (IoT). Home security includes both the security hardware placed on a property and individuals' personal security practices. Security devices consist of a door locking, alert alarm, lighting, motion detectors, and security camera system. Additionally, several special features include such as ensuring windows are closed, each door is locked, all alarms are activated, and extra keys are not secret outside.

This chapter reviews the overall electrical network from the generation to transmission and distribution and finally to consumer. It discusses electrical network architecture and energy monitoring points, causes of energy losses and the scope for energy losses reduction. Further load shedding, utility demand energy management system using automation and the role of buildings in energy conservation have been discussed. An overview of energy management devices used in the substation, automation protocols, smart devices, and applicable standards. The importance and need for energy conservation in consumer’s house, using IoT devices. What is smart home, various components, home automation techniques their principle and architecture, current scenario and future scope of technology in smart home. This chapter also discusses the design trade-offs with an emphasis on energy conservation. It discusses data security model, data encryption, and their practical approaches in smart home. It classifies the various important components in smart home. Use of artificial intelligence and signal processing using IoT-based devices in smart home has also been brought out.

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.

The Internet of Things (IoT) has enabled smart home devices to provide users with the convenience of monitoring and controlling their homes directly from their smartphones. However, connecting these devices to the internet and to each other introduces significant security and privacy challenges, including the need to ensure the confidentiality, integrity, and authenticity of the data they collect and exchange. Due to inherent vulnerabilities, smart home devices are susceptible to various forms of cyberattacks, which can compromise the safety and trustworthiness of the smart home environment. Consequently, assessing and understanding these security risks is essential to determine the resilience of such devices. For smart home technologies to achieve widespread adoption, they must gain user confidence through robust security and privacy safeguards. As with many technology-driven sectors, maintaining security remain a critical and ongoing challenge. As homes become increasingly digitized and the adoption of smart devices continues to grow, the likelihood of targeted attacks has also increased. Therefore, this research proposes a methodology comprising four phases: information gathering to identify the device’s FCC ID, establishing the laboratory environment, conducting the exploitation phase, and analyzing the results of the vulnerability assessment. The main objective is to identify potential weaknesses in selected smart home devices. Experimental results revealed that the tested device is vulnerable to replay attacks, in which retransmission of captured packets prompts the device to execute unintended commands.

With the widespread popularity of smart home devices and the emergence of smart home integration platforms such as Google, Amazon, and Xiaomi, the smart home industry is in a stage of vigorous development. While smart homes provide users with convenient and intelligent living, the problem of smart home devices leaking user privacy has become increasingly prominent. Smart home devices give users the ability to remotely control home devices, but they also reflect user home activities in traffic data, which brings the risk of privacy leaks. Potential attackers can use traffic classification technology to analyze traffic characteristics during traffic transmission (e.g., at the traffic exit of a smart home gateway) and infer users’ private information, such as their home activities, causing serious consequences of privacy leaks. To address the above problems, this paper focuses on research on privacy protection technology based on traffic obfuscation. By using traffic obfuscation technology to obscure the true traffic of smart home devices, it can prevent malicious traffic listeners from analyzing user privacy information based on traffic characteristics. We propose an enhanced smart home traffic obfuscation method called SHTObfuscator (Smart Home Traffic Obfuscator) based on the virtual user technology concept and a virtual user behavior construction method based on logical integrity. By injecting traffic fingerprints of different device activities into the real traffic environment of smart homes as obfuscating traffic, attackers cannot distinguish between the real device working status and user behavior privacy in the current home, effectively reducing the effect of traffic classification attack models. The protection level can be manually or automatically adjusted, achieving a balance between privacy protection and bandwidth overhead. The experimental results show that under the highest obfuscation level, the obfuscation method proposed in this paper can effectively reduce the classification effect of the attack model from 95% to 25%.

Dear Readers,  It gives me great pleasure to announce the fourth regular issue of 2024. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research. I am also very proud to announce that our journal has been included in the Free Journal Network as one of the listed high-quality journals in this field. Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to introduce six papers by 22 authors from nine countries: Brazil, Czech Republic, Germany, Iran, Jordan, Portugal, Thailand, Turkey, and the USA. In a collaboration between researchers from the Czech Republic and Germany, Sivaramasamy Elayaraja, Sunil Yeruva Vlastimil Stejskal, and Satish Nandipati look into multi-class microscopic image analysis of protozoan parasites using convolutional neural network and perform a study on 4740 microscopic images. André Diegues Fernandes, João Cruz, Miguel Mira da Silva, and Rúben Pereira from Portugal cover a systematic literature review for mapping and integrating security and risk standards. In a collaborative research between Jordan and the USA, Sahar Idwan, Junaid Zubairi, Syed Ali Haider, and Wael Etaiwi introduce their reactive traffic congestion control method based on a hierarchical graph approach. Shahrzad Riahi, Ramtin Khosravi, and Fatemeh Ghassemi from Iran conduct a study on knowledge-related policy analysis in an inference-enabled actor model. Josival Silva, Nelson Rosa, and Fernando Aires from Brazil research and present UP-Home, a self-adaptive solution that manages the security of smart homes by industry standards, and identifies and mitigates smart home security vulnerabilities. Last but not least, Sait Can Yucebas, Sukran Yalpir, Levent Genc, and Melike Dogan from Turkey discuss their research on price prediction and determination of the factors influencing real estate prices using X-Means clustering and CART decision trees. Enjoy Reading! Cordially, Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria

The Internet of Things (IoT) carries the meaning of a developing prototype that focuses on the connection between devices, objects, sensors and users. Using IoT, the method of communications and interactions changes in form of ‘Human to Thing’ to ‘Thing to Thing’. IoT technology is rapidly evolving and spreading its technology influence across various domains including healthcare (personal and enterprise), smart campuses, smart homes, smart mobility, and Industry 4.0. As a result, a lot of IoT devices are being used as a crucial component as one of human made high-tech butlers of everyday lifestyle. This paper focuses on the IoT security threats and vulnerabilities that shall be considered in the implementation of IoT ecosystem by conducting a research in the area of smart home environment. The current security threats and vulnerabilities are being discussed in the contexts of the IoT architecture layers, which is the application layer, network layer and physical layer are also presented. This paper also provides an analysis of the possible threats and proposes possible solutions for improving the security of the IoT smart home, that may influence as beneficial factors that are able to promote a secured eco-system of IoT devices in smart home operational environment.