A Smart Home System based on Internet of Things
- URL: http://arxiv.org/abs/2009.05328v1
- Date: Fri, 11 Sep 2020 10:34:48 GMT
- Title: A Smart Home System based on Internet of Things
- Authors: Rihab Fahd Al-Mutawa, Fathy Albouraey Eassa
- Abstract summary: Authorization and authentication are challenging IoT security operations.
This paper applies an extra layer of security of multi-factor authentication to act as a prevention method for mitigating unauthorized access.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The Internet of Things (IoT) describes a network infrastructure of
identifiable things that share data through the Internet. A smart home is one
of the applications for the Internet of Things. In a smart home, household
appliances could be monitored and controlled remotely. This raises a demand for
reliable security solutions for IoT systems. Authorization and authentication
are challenging IoT security operations that need to be considered. For
instance, unauthorized access, such as cyber-attacks, to a smart home system
could cause danger by controlling sensors and actuators, opening the doors for
a thief. This paper applies an extra layer of security of multi-factor
authentication to act as a prevention method for mitigating unauthorized
access. One of those factors is face recognition, as it has recently become
popular due to its non-invasive biometric techniques, which is easy to use with
cameras attached to most trending computers and smartphones. In this paper, the
gaps in existing IoT smart home systems have been analyzed, and we have
suggested improvements for overcoming them by including necessary system
modules and enhancing user registration and log-in authentication. We propose
software architecture for implementing such a system. To the best of our
knowledge, the existing IoT smart home management research does not support
face recognition and liveness detection within the authentication operation of
their suggested software architectures.
Related papers
- Detection of Energy Consumption Cyber Attacks on Smart Devices [1.515687944002438]
This paper presents a lightweight technique for detecting energy consumption attacks on smart home devices by analyzing received packets.
It accounts for resource constraints and promptly alerts administrators upon detecting an attack.
arXiv Detail & Related papers (2024-04-30T10:29:25Z) - Secure Supervised Learning-Based Smart Home Authentication Framework [0.7607700105031543]
A secure authentication protocol needs to be established between the smart devices and the user.
Most of the existing smart home authentication protocols were identified to fail in facilitating a secure mutual authentication.
SSL-SHAF is proposed as are liable mutual authentication that can be contextually imposed for better security.
arXiv Detail & Related papers (2024-02-01T13:01:47Z) - Effective Intrusion Detection in Heterogeneous Internet-of-Things Networks via Ensemble Knowledge Distillation-based Federated Learning [52.6706505729803]
We introduce Federated Learning (FL) to collaboratively train a decentralized shared model of Intrusion Detection Systems (IDS)
FLEKD enables a more flexible aggregation method than conventional model fusion techniques.
Experiment results show that the proposed approach outperforms local training and traditional FL in terms of both speed and performance.
arXiv Detail & Related papers (2024-01-22T14:16:37Z) - Classification of cyber attacks on IoT and ubiquitous computing devices [49.1574468325115]
This paper provides a classification of IoT malware.
Major targets and used exploits for attacks are identified and referred to the specific malware.
The majority of current IoT attacks continue to be of comparably low effort and level of sophistication and could be mitigated by existing technical measures.
arXiv Detail & Related papers (2023-12-01T16:10:43Z) - Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future [6.422895251217666]
This paper reviews forensic and security issues associated with IoT in different fields.
Most IoT devices are vulnerable to attacks due to a lack of standardized security measures.
To fulfil the security-conscious needs of consumers, IoT can be used to develop a smart home system.
arXiv Detail & Related papers (2023-09-06T04:41:48Z) - When Authentication Is Not Enough: On the Security of Behavioral-Based Driver Authentication Systems [53.2306792009435]
We develop two lightweight driver authentication systems based on Random Forest and Recurrent Neural Network architectures.
We are the first to propose attacks against these systems by developing two novel evasion attacks, SMARTCAN and GANCAN.
Through our contributions, we aid practitioners in safely adopting these systems, help reduce car thefts, and enhance driver security.
arXiv Detail & Related papers (2023-06-09T14:33:26Z) - Safe RAN control: A Symbolic Reinforcement Learning Approach [62.997667081978825]
We present a Symbolic Reinforcement Learning (SRL) based architecture for safety control of Radio Access Network (RAN) applications.
We provide a purely automated procedure in which a user can specify high-level logical safety specifications for a given cellular network topology.
We introduce a user interface (UI) developed to help a user set intent specifications to the system, and inspect the difference in agent proposed actions.
arXiv Detail & Related papers (2021-06-03T16:45:40Z) - Dos and Don'ts of Machine Learning in Computer Security [74.1816306998445]
Despite great potential, machine learning in security is prone to subtle pitfalls that undermine its performance.
We identify common pitfalls in the design, implementation, and evaluation of learning-based security systems.
We propose actionable recommendations to support researchers in avoiding or mitigating the pitfalls where possible.
arXiv Detail & Related papers (2020-10-19T13:09:31Z) - Smart Home, security concerns of IoT [91.3755431537592]
The IoT (Internet of Things) has become widely popular in the domestic environments.
People are renewing their homes into smart homes; however, the privacy concerns of owning many Internet connected devices with always-on environmental sensors remain insufficiently addressed.
Default and weak passwords, cheap materials and hardware, and unencrypted communication are identified as the principal threats and vulnerabilities of IoT devices.
arXiv Detail & Related papers (2020-07-06T10:36:11Z) - Scalable and Secure Architecture for Distributed IoT Systems [1.4209473797379666]
We propose to improve the IoT architecture with additional security features using Artificial Intelligence (AI) and blockchain technology.
We enhance the IoT system security with an AI-component at the gateway level to detect and classify suspected activities, malware, and cyber-attacks using machine learning techniques.
arXiv Detail & Related papers (2020-04-20T23:50:43Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.