Article
Computer Science, Information Systems
Zhiyi Zhang, Tianyuan Yu, Xinyu Ma, Yu Guan, Philipp Moll, Lixia Zhang
Summary: The rapid deployment of smart homes controlled by remote servers has raised concerns about security and privacy. In this article, the design of Sovereign, a home Internet of Things (IoT) system framework that gives end users complete control over their home IoT systems, is described. Sovereign enables direct, secure device-to-device communication and utilizes semantic names to construct usable security solutions.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Waseem Iqbal, Haider Abbas, Pan Deng, Jiafu Wan, Bilal Rauf, Yawar Abbas, Imran Rashid
Summary: Smart connected devices are the first choice of cybercriminals for spreading spy wares and different security attacks. The current security standards and protocols for Internet of Things (IoT) have failed in providing security to these devices. A network-level security architecture based on lightweight cryptographic parameters is required to overcome the resource constraintness and security barriers of smart devices.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Joy Brahma, Debanjan Sadhya
Summary: This study focuses on privacy concerns in IoT devices, particularly user activity inference attacks. By combining dummy packet generation with dynamic link padding, this study introduces a new defense mechanism that can reduce false positives for device state identification and decrease traffic overhead.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Energy & Fuels
Zahra Solatidehkordi, Jayroop Ramesh, A. R. Al-Ali, Ahmed Osman, Mostafa Shaaban
Summary: The increase in household energy consumption globally has highlighted the need for effective management and monitoring of electricity usage. This study proposes a smart home appliance classification system that utilizes deep learning and a comprehensive database for training, achieving competitive results across various appliances. The model is deployed on a Raspberry Pi micro-controller and interfaces with smart meters to provide almost real-time appliance classification to end users or utility providers through a mobile application.
Review
Psychology, Multidisciplinary
David Buil-Gil, Steven Kemp, Stefanie Kuenzel, Lynne Coventry, Sameh Zakhary, Daniel Tilley, James Nicholson
Summary: The connection of home electronic devices to the internet enables remote control and data collection, but also poses security and privacy risks. A systematic literature review revealed that smart homes may threaten confidentiality, authentication, and system controls. The most common harm identified was privacy intrusion, while hacking, malware, and DoS attacks were less frequently studied. Technical measures are proposed to mitigate digital harms, but social prevention mechanisms are less considered.
COMPUTERS IN HUMAN BEHAVIOR
(2023)
Article
Computer Science, Information Systems
Davide Ferraris, Daniel Bastos, Carmen Fernandez-Gago, Fadi El-Moussa
Summary: Smart home devices like Amazon Echo and Google Home have raised concerns about privacy invasion due to their intrusive nature, but studies show that perceived benefits outweigh risks for consumers. Users place a high level of trust in these devices, sometimes overlooking the importance of security controls, which may lead to potential security issues.
INTERNATIONAL JOURNAL OF INFORMATION SECURITY
(2021)
Article
Computer Science, Information Systems
Qing Yang, Hao Wang
Summary: This article proposes a blockchain-based transactive energy management system for smart homes, addressing the challenges of low efficiency and privacy leakage in traditional TEM methods. Through a privacy-preserving distributed algorithm, users can optimally manage their energy usages via smart contracts on the blockchain, resulting in a 25% reduction in overall cost and feasibility on practical IoT devices.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Theory & Methods
Amjad Qashlan, Priyadarsi Nanda, Manoranjan Mohanty
Summary: Secure and private communications in IoT for smart home systems are challenging. This paper proposes a privacy-preserving data aggregation mechanism using differential privacy and blockchain to protect sensitive personal information. The approach is evaluated using public datasets and shows that the differential private models can provide privacy protection while sacrificing some model utility.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Information Systems
Muhammad Tanveer, Ghulam Abbas, Ziaul Haq Abbas, Muhammad Bilal, Amrit Mukherjee, Kyung Sup Kwak
Summary: This article introduces a lightweight user AKE scheme (LAKE-6SH) for smart home networks, which establishes private session keys between users and network entities to achieve authenticity of RUs using the SHA-256 hash function, exclusive-OR operation, and a simple authenticated encryption primitive. The scheme has been informally validated to be secure against various security attacks, and further validated formally through the random oracle model and Scyther validation. Additionally, LAKE-6SH is shown to provide better security features with low communication and computational overheads.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Yuan Luo, Long Cheng, Hongxin Hu, Guojun Peng, Danfeng Yao
Summary: This study highlights the privacy risks in IoT systems and introduces a privacy leakage analysis method called ALTA, which can infer specific running applications in smart homes through IoT traffic tracking and learn rich contextual information.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Multidisciplinary Sciences
Hua Du, Qi Han, Dujuan Yang, Bauke de Vries, Thomas van Houten
Summary: This study investigates the trade-offs individuals make between sharing privacy-sensitive data and the potential environmental and economic benefits of smart home energy appliances. The findings reveal that the trade-offs are influenced by product attributes such as the type of data processed, the reason for processing, data sharing frequency, and financial gain. The research highlights the gap between privacy attitudes and behaviors and provides valuable insights for smart appliance retailers, manufacturers, and governments.
Article
Green & Sustainable Science & Technology
Wonyoung Choi, Jisu Kim, SangEun Lee, Eunil Park
Summary: The Internet of Things has revolutionized various domains in society, with smart homes being one of the most significantly affected areas. Research findings show notable improvements and developments in the smart home-Internet of Things domain, providing valuable insights for future directions.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Computer Science, Information Systems
Yuan Su, Yanping Li, Jiliang Li, Kai Zhang
Summary: The LCEDA scheme aims to protect the privacy of smart grid data and improve the efficiency and reliability of data aggregation. By reducing communication and computation costs, efficiently updating masking value shares, and supporting dynamic enrollment and revocation of smart meters, the LCEDA scheme provides a lightweight and efficient solution for secure data aggregation in smart grid.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Shuodi Hui, Zhenhua Wang, Xueshi Hou, Xiao Wang, Huandong Wang, Yong Li, Depeng Jin
Summary: Privacy leakage of Internet of Things (IoT) has become a significant challenge as IoT services become more popular on mobile networks. While previous work has provided general structures for analyzing IoT privacy and case studies for specific devices or scenarios, conducting a comprehensive and systematic study of large-scale IoT privacy leakage in the real world remains challenging. Our method to quantify IoT privacy leakage on a large-scale mobile network traffic data set demonstrates considerable risks for IoT users, devices, and platforms respectively, and shows that IoT devices have a larger scale of privacy leakage than users and platforms, with different daily patterns of privacy leakage. Three case studies on location information, application calling, and voice service illustrate the ability of a third party to profile a network entity in both cyberspace and physical space.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Hongwei Luo, Chao Wang, Hao Luo, Fan Zhang, Feng Lin, Guoai Xu
Summary: This article introduces a gateway-based 2 factor authentication (G2F) framework to enhance the security of IoT device management. By utilizing a hardware token to interact with the local gateway node, G2F ensures user authentication security and allows for multiple simultaneous operations. Through implementation on Alibaba Cloud, G2F demonstrates the ability to protect against malicious attacks with high authentication efficiency.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Muhammed Yilmaz, Ahmet Murat Ozbayoglu, Bulent Tavli
Summary: This study proposes a deep neural network-based model to determine the lifetime of wireless sensor networks near-optimally almost instantly, with an average accuracy exceeding 98.5%. Learning-based algorithms are able to produce near-optimal results more rapidly compared to mixed integer programming models.
Article
Economics
Jeyhun Karimov, Murat Ozbayoglu, Bulent Tavli, Erdogan Dogdu
Summary: The problem of ATM menu optimization is formulated as a Mixed Integer Programming (MIP) framework, with parameters derived from a comprehensive actual ATM menu usage database. Two heuristic approaches are proposed to reduce computational complexity, enabling customization for ergonomic factors and optimization of various menu design problems. Performance evaluations using real ATM data demonstrate the superior performance of the optimization solution.
COMPUTATIONAL ECONOMICS
(2022)
Article
Automation & Control Systems
Cihan Emre Kement, Hakan Gultekin, Bulent Tavli
Summary: This study introduces a privacy-aware stochastic multiobjective optimization framework that enables fair optimization of objectives and explores the relationship between consumers and utility companies. The results show that near-optimal privacy performance can be achieved with small compromises on other objectives.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Computer Science, Hardware & Architecture
Vahid Khalilpour Akram, Orhan Dagdeviren, Bulent Tavli
Summary: This study introduces a coverage-aware distributed k-connectivity maintenance algorithm that efficiently restores k-connectivity while maintaining coverage.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2022)
Article
Computer Science, Interdisciplinary Applications
Hakan Gultekin, Sinan Gurel, Rabia Taspinar
Summary: This study focuses on optimizing the sequencing and speeds of a material handling robot in a flowshop production system, aiming to find Pareto efficient solutions through second order cone programming and a heuristic algorithm. The proposed approaches help decision-makers strike a balance between throughput and energy efficiency.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Computer Science, Information Systems
Muhammed Fatih Carsancakli, Md Abdullah Al Imran, Huseyin Ugur Yildiz, Ali Kara, Bulent Tavli
Summary: After conducting a concise literature survey on LWSN reliability, a comprehensive optimization framework is proposed to model the operation of LWSN, which includes three transmission power and packet size assignment strategies. The study reveals that coordinated node failures have a more severe impact on NL compared to random node failures in strongly connected LWSNs, leading to a significant decrease in NL.
Article
Computer Science, Information Systems
Muhammed Cobanlar, Huseyin Ugur Yildiz, Vahid Khalilpour Akram, Orhan Dagdeviren, Bulent Tavli
Summary: In this study, an optimization framework is created to explore the tradeoff between network lifetime (NLT) and reliability based on k-connectivity in underwater wireless sensor networks (UWSNs).
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Hardware & Architecture
Ali Murat Demirtas, Mehmet Saygin Seyfioglu, Irem Bor-Yaliniz, Bulent Tavli, Halim Yanikomeroglu
Summary: To address the growing demand for connectivity in communications, it is necessary to adopt innovative solutions such as using unmanned aerial vehicles (UAVs) as mobile base stations. This article presents an overview of the UAV base station trajectory optimization problem for next generation wireless networks and demonstrates that a convolutional neural network (CNN) model can be trained to accurately infer the location of a UAV base station in real time. Performance evaluations show that the proposed approach, trained with given labels and mobile user locations, can approximate the results of the optimization algorithm with high fidelity and outperform reinforcement learning-based approaches in resource-constrained settings. Future research challenges and key issues are also discussed.
IEEE CONSUMER ELECTRONICS MAGAZINE
(2023)
Article
Energy & Fuels
Cihan Emre Kement, Marija Ilic, Hakan Gultekin, Cihan Tugrul Cicek, Bulent Tavli
Summary: This study addresses the importance of load shaping for protecting consumer privacy in smart grids and presents a multi-objective optimization framework to analyze the interplay between privacy maximization, user cost minimization, and user discomfort minimization. The results reveal that joint shaping of real and reactive power components can significantly improve privacy preservation performance.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Proceedings Paper
Computer Science, Hardware & Architecture
Burak Emre Un, Huseyin Ugur Yildiz, Bulent Tavli
Summary: The failure of critical nodes in underwater wireless sensor networks can significantly reduce network lifetimes and increase energy consumption overhead.
2021 IEEE INTERNATIONAL BLACK SEA CONFERENCE ON COMMUNICATIONS AND NETWORKING (IEEE BLACKSEACOM)
(2021)
Article
Computer Science, Interdisciplinary Applications
Cihan Tugrul Cicek, Zuo-Jun Max Shen, Hakan Gultekin, Bulent Tavli
Summary: This study focuses on the dynamic covering location problem of an unmanned aerial vehicle base station (UAV-BS), which is crucial for applications in smart grid and disaster relief. Traditional planar covering location approaches are limited due to the vertical movement ability of UAV-BS and nonconvex covering functions in wireless communication. New formulations and algorithms are developed to maximize total coverage within a finite time horizon, with a particular emphasis on nonconvex mixed-integer nonlinear programming and Lagrangean decomposition algorithm (LDA). Additionally, a continuum approximation (CA) model is proposed as a promising approach in terms of computational time and solution accuracy, especially for large-scale problems.
INFORMS JOURNAL ON COMPUTING
(2021)