AntibIoTic: The Fog-enhanced distributed security system to protect the (legacy) Internet of Things

2021 ◽  
pp. 1-37
Author(s):  
Michele De Donno ◽  
Xenofon Fafoutis ◽  
Nicola Dragoni
Keyword(s):  
Internet Of Things ◽  
Fog Computing ◽  
Security System ◽  
Security And Privacy ◽  
Aggregated Data ◽  
Fine Grained ◽  
Computational Overhead ◽  
Distributed Security ◽  
Cloud Server ◽  
Iot Devices

The Internet of Things (IoT) is evolving our society; however, the growing adoption of IoT devices in many scenarios brings security and privacy implications. Current security solutions are either unsuitable for every IoT scenario or provide only partial security. This paper presents AntibIoTic 2.0, a distributed security system that relies on Fog computing to secure IoT devices, including legacy ones. The system is composed of a backbone, made of core Fog nodes and Cloud server, a Fog node acting at the edge as the gateway of the IoT network, and a lightweight agent running on each IoT device. The proposed system offers fine-grained, host-level security coupled with network-level protection, while its distributed nature makes it scalable, versatile, lightweight, and easy to deploy, also for legacy IoT deployments. AntibIoTic 2.0 can also publish anonymized and aggregated data and statistics on the deployments it secures, to increase awareness and push cooperations in the area of IoT security. This manuscript recaps and largely expands previous works on AntibIoTic, providing an enhanced design of the system, an extended proof-of-concept that proves its feasibility and shows its operation, and an experimental evaluation that reports the low computational overhead it causes.

Security Issues in Fog Computing for Internet of Things

2020 ◽  
pp. 53-63 ◽  
Author(s):  
D. N. Kartheek ◽  
Bharath Bhushan
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Fog Computing ◽  
Security And Privacy ◽  
Privacy Concerns ◽  
Security Issues ◽  
Privacy Measures ◽  
Speed Up ◽  
Iot Devices ◽  
Privacy Issues

The inherent features of internet of things (IoT) devices, like limited computational power and storage, lead to a novel platform to efficiently process data. Fog computing came into picture to bridge the gap between IoT devices and data centres. The main purpose of fog computing is to speed up the computing processing. Cloud computing is not feasible for many IoT applications; therefore, fog computing is a perfect alternative. Fog computing is suitable for many IoT services as it has many extensive benefits such as reduced latency, decreased bandwidth, and enhanced security. However, the characteristics of fog raise new security and privacy issues. The existing security and privacy measures of cloud computing cannot be directly applied to fog computing. This chapter gives an overview of current security and privacy concerns, especially for the fog computing. This survey mainly focuses on ongoing research, security challenges, and trends in security and privacy issues for fog computing.

scholarly journals Fine-Grained Attribute-Based Multikeyword Search for Shared Multiowner in Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yunhong Zhou ◽  
Jiehui Nan ◽  
Licheng Wang
Keyword(s):  
Internet Of Things ◽  
Keyword Search ◽  
Security Analysis ◽  
Security And Privacy ◽  
Management Service ◽  
Specific Data ◽  
Fine Grained ◽  
Secure Search ◽  
Data Owner ◽  
Iot Devices

At present, with the popularity of Internet of things (IoT), a huge number of datasets generated by IoT devices are being uploaded to the cloud storage in remote data management service, but a series of security and privacy defects also arises, where one of the best ways for preventing data disclosure is encryption. Among them, searchable encryption (SE) is considered to be a very attractive cryptographic technology, since it allows users to search records in an encrypted form and to protect user’s data on an untrusted server. For the sake of enhancing search permission, attribute-based keyword search (ABKS) is an efficient method to provide secure search queries and fine-grained access authentications over ciphertexts. However, most existing ABKS schemes concentrate on single keyword search, which usually returns redundant and irrelevant results, so it would cost some unnecessary computation and communication resources. Furthermore, existing work in the literature mostly only supports unshared multiowner where a specific data owner owns each file, which is not able to satisfy more desired expressive search. In this work, we propose a novel attribute-based multikeyword search for shared multiowner (ABMKS-SM) primitive in IoT to achieve enhanced access control for users; meanwhile, it can support multikeyword search over ciphertexts and give a formal security analysis in the adaptive against chosen keyword attack (IND-CKA) model. Finally, we have also implemented this prototype to show efficiency when compared with some previous schemes.

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

scholarly journals A Hybrid Optimized LSTM Models for Human Activity Recognition with IOT Devices

2021 ◽  
pp. 182-189
Author(s):  
S. Arokiaraj ◽  
Dr. N. Viswanathan
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Short Term Memory ◽  
The Other ◽  
Learning Models ◽  
Computational Overhead ◽  
Temporal Features ◽  
Human Movements ◽  
Proposed Model ◽  
Iot Devices

With the advent of Internet of things(IoT),HA (HA) recognition has contributed the more application in health care in terms of diagnosis and Clinical process. These devices must be aware of human movements to provide better aid in the clinical applications as well as user’s daily activity.Also , In addition to machine and deep learning algorithms, HA recognition systems has significantly improved in terms of high accurate recognition. However, the most of the existing models designed needs improvisation in terms of accuracy and computational overhead. In this research paper, we proposed a BAT optimized Long Short term Memory (BAT-LSTM) for an effective recognition of human activities using real time IoT systems. The data are collected by implanting the Internet of things) devices invasively. Then, proposed BAT-LSTM is deployed to extract the temporal features which are then used for classification to HA. Nearly 10,0000 dataset were collected and used for evaluating the proposed model. For the validation of proposed framework, accuracy, precision, recall, specificity and F1-score parameters are chosen and comparison is done with the other state-of-art deep learning models. The finding shows the proposed model outperforms the other learning models and finds its suitability for the HA recognition.

scholarly journals Design a blockchain-based middleware layer in the Internet of Things Architecture

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Tanweer Alam
Keyword(s):  
Internet Of Things ◽  
Fog Computing ◽  
Smart Devices ◽  
The Internet ◽  
Novel Approach ◽  
Generation Computing ◽  
Critical Issues ◽  
Iot Devices ◽  
The Internet Of Things

In next-generation computing, the role of cloud, internet and smart devices will be capacious. Nowadays we all are familiar with the word smart. This word is used a number of times in our daily life. The Internet of Things (IoT) will produce remarkable different kinds of information from different resources. It can store big data in the cloud. The fog computing acts as an interface between cloud and IoT. The extension of fog in this framework works on physical things under IoT. The IoT devices are called fog nodes, they can have accessed anywhere within the range of the network. The blockchain is a novel approach to record the transactions in a sequence securely. Developing a new blockchains based middleware framework in the architecture of the Internet of Things is one of the critical issues of wireless networking where resolving such an issue would result in constant growth in the use and popularity of IoT. The proposed research creates a framework for providing the middleware framework in the internet of smart devices network for the internet of things using blockchains technology. Our main contribution links a new study that integrates blockchains to the Internet of things and provides communication security to the internet of smart devices.

Security and Privacy Issues in IoT

2019 ◽  
pp. 129-156
Author(s):  
S. R. Mani Sekhar ◽  
Sharmitha S. Bysani ◽  
Vasireddy Prabha Kiranmai
Keyword(s):  
Cloud Computing ◽  
Information Systems ◽  
Internet Of Things ◽  
Case Studies ◽  
Communication Systems ◽  
Fog Computing ◽  
Security And Privacy ◽  
Privacy Issues

Security and privacy issues are the challenging areas in the field of internet of things (IoT) and fog computing. IoT and fog has become an involving technology allowing major changes in the field of information systems and communication systems. This chapter provides the introduction of IoT and fog technology with a brief explanation of how fog is overcoming the challenges of cloud computing. Thereafter, the authors discuss the different security and privacy issues and its related solutions. Furthermore, they present six different case studies which will help the reader to understand the platform of IoT in fog.

Healthcare-Internet of Things and Its Components

2021 ◽  
pp. 258-277
Author(s):  
Aman Tyagi
Keyword(s):  
Internet Of Things ◽  
Fog Computing ◽  
Communication Technologies ◽  
The Internet ◽  
Healthcare Resources ◽  
Iot Security ◽  
Global Epidemic ◽  
Security Issues ◽  
Analyse Data ◽  
Iot Devices

Elderly population in the Asian countries is increasing at a very fast rate. Lack of healthcare resources and infrastructure in many countries makes the task of provding proper healthcare difficult. Internet of things (IoT) in healthcare can address the problem effectively. Patient care is possible at home using IoT devices. IoT devices are used to collect different types of data. Various algorithms may be used to analyse data. IoT devices are connected to the internet and all the data of the patients with various health reports are available online and hence security issues arise. IoT sensors, IoT communication technologies, IoT gadgets, components of IoT, IoT layers, cloud and fog computing, benefits of IoT, IoT-based algorithms, IoT security issues, and IoT challenges are discussed in the chapter. Nowadays global epidemic COVID19 has demolished the economy and health services of all the countries worldwide. Usefulness of IoT in COVID19-related issues is explained here.

Towards the Protection and Security in Fog Computing for Industrial Internet of Things

2021 ◽  
pp. 17-32
Author(s):  
G. Rama Subba Reddy ◽  
K. Rangaswamy ◽  
Malla Sudhakara ◽  
Pole Anjaiah ◽  
K. Reddy Madhavi
Keyword(s):  
Internet Of Things ◽  
Distributed Computing ◽  
Fog Computing ◽  
Security And Privacy ◽  
Safety Measures ◽  
Iot Applications ◽  
Industrial Internet ◽  
Sensor Devices ◽  
Key Enabling Technologies ◽  
Privacy Issues

Internet of things (IoT) has given a promising chance to construct amazing industrial frameworks and applications by utilizing wireless and sensor devices. To support IIoT benefits efficiently, fog computing is typically considered as one of the potential solutions. Be that as it may, IIoT services still experience issues such as high-latency and unreliable connections between cloud and terminals of IIoT. In addition to this, numerous security and privacy issues are raised and affect the users of the distributed computing environment. With an end goal to understand the improvement of IoT in industries, this chapter presents the current research of IoT along with the key enabling technologies. Further, the architecture and features of fog computing towards the fog-assisted IoT applications are presented. In addition to this, security and protection threats along with safety measures towards the IIoT applications are discussed.

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