scholarly journals A Fog Computing-based Framework for Privacy Preserving IoT Environments

2020 ◽  
Vol 17 (3) ◽  
pp. 306-315
Author(s):  
Dhiah el Diehn Abou-Tair ◽  
Simon Büchsenstein ◽  
Ala’ Khalifeh
Keyword(s):  
Cloud Computing ◽  
Storage Capacity ◽  
Fog Computing ◽  
Security Analysis ◽  
Vital Signs ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Computing Power ◽  
Privacy Threats ◽  
Iot Devices

Privacy is becoming an indispensable component in the emerging Internet of Things (IoT) context. However, the IoT based devices and tools are exposed to several security and privacy threats, especially that these devices are mainly used to gather data about users’ habits, vital signs, surround environment, etc., which makes them a lucrative target to intruders. Up to date, conventional security and privacy mechanisms are not well optimized for IoT devices due to their limited energy, storage capacity, communication functionality and computing power, which influenced researchers to propose new solutions and algorithms to handle these limitations. Fog and cloud computing have been recently integrated in IoT environment to solve their resources’ limitations, thus facilitating new life scenarios-oriented applications. In this paper, a security and privacy preserving framework is proposed, which utilizes Fog and cloud computing in conjunction with IoT devices that aims at securing the users’ data and protecting their privacy. The framework has been implemented and tested using available technologies. Furthermore, a security analysis has been verified by simulating several hypothetical attack scenarios, which showed the effectiveness of the proposed framework and its capability of protecting the users’ information.

scholarly journals Privacy-Preserving Data Aggregation against False Data Injection Attacks in Fog Computing

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2659 ◽  
Author(s):  
Yinghui Zhang ◽  
Jiangfan Zhao ◽  
Dong Zheng ◽  
Kaixin Deng ◽  
Fangyuan Ren ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Aggregation ◽  
Homomorphic Encryption ◽  
Fog Computing ◽  
Cloud Service ◽  
Privacy Preserving ◽  
Location Awareness ◽  
False Data Injection ◽  
Injection Attacks ◽  
Iot Devices

As an extension of cloud computing, fog computing has received more attention in recent years. It can solve problems such as high latency, lack of support for mobility and location awareness in cloud computing. In the Internet of Things (IoT), a series of IoT devices can be connected to the fog nodes that assist a cloud service center to store and process a part of data in advance. Not only can it reduce the pressure of processing data, but also improve the real-time and service quality. However, data processing at fog nodes suffers from many challenging issues, such as false data injection attacks, data modification attacks, and IoT devices’ privacy violation. In this paper, based on the Paillier homomorphic encryption scheme, we use blinding factors to design a privacy-preserving data aggregation scheme in fog computing. No matter whether the fog node and the cloud control center are honest or not, the proposed scheme ensures that the injection data is from legal IoT devices and is not modified and leaked. The proposed scheme also has fault tolerance, which means that the collection of data from other devices will not be affected even if certain fog devices fail to work. In addition, security analysis and performance evaluation indicate the proposed scheme is secure and efficient.

scholarly journals Security Problems in Iot Model and Privacy Preserving in Various Iot Devices

2019 ◽  
Vol 8 (4) ◽  
pp. 4418-4421
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Data Publishing ◽  
Series Data ◽  
Personal Privacy ◽  
Privacy Threats ◽  
Security Concerns ◽  
Iot Devices

It is instead required for IoT units to equip along with the potential to withstand security and privacy threats when fulfilling the intended useful criteria and services. To obtain these targets, there are many brand-new problems for the IoT to apply personal privacy-preserving records manipulation. Initially, data professionals need to have to process privacysensitive data to remove the counted on details without particular privacy enclosure. Within this paper, our company temporarily showed the kinds of security concerns in IoT style, personal privacy-preserving in different IoT devices as well as additional challenges and also method for privacy-preserving time-series data publishing

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 A Study on Data Security In Fog Computing

2018 ◽  
Vol 7 (2.19) ◽  
pp. 50
Author(s):  
P S.Apirajitha
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Security ◽  
Fog Computing ◽  
Daily Basis ◽  
Long Distance ◽  
Computing Power ◽  
On Demand ◽  
Iot Devices ◽  
The Cost

During the years, Cloud Computing is a popular paradigm which provide access to configurable resources on devices at any time,with on demand. Cloud Computing provides many benefits to enterprises by reducing the cost and allowing them to concentrate on their core business. Apart from this , the Development of Internet of Things came into existence, where the cloud divulge a long distance between users and its environment. Cloud Computing is also referred as heavy computing and dense form of computing power. In Spite of this  a new computing has been proposed called Fog Computing also known as Fogging, which overcomes the problem of cloud. Fog computing which majority supports the concepts of Internet of Things(IoT), where many  IoT devices are used by users on daily basis which are connected to each other. Fog Computing is also an extended version of cloud computing.  

scholarly journals Privacy-Preserving Internet of Things: Techniques and Applications

2019 ◽  
Vol 8 (6) ◽  
pp. 3229-3234 ◽  
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Fog Computing ◽  
Privacy Preserving ◽  
Sensitive Information ◽  
Multiparty Computation ◽  
Iot Applications ◽  
Attribute Based Encryption ◽  
Daily Behavior ◽  
Iot Devices

Privacy has become an imperative term in the recent technology developments. Lots of data are being collected through every digital activity of users. The expeditious development of IoT applications have raised the concern about the privacy of the IoT systems. The data collected via IoT sensors can reveal the daily behavior of the users, location, and other sensitive information. Hence, it is necessary to preserve the privacy of data collected by IoT devices. A large number of techniques and approaches have been implemented and used in different IoT based applications such as cloud computing based IoT, fog computing based IoT, blockchain based IoT and trajectory applications. In this paper, we present a detailed investigation of the existing approaches to preserve the privacy of data in IoT applications. The techniques like k-anonymity, secure multiparty computation, attribute based encryption and homomorphic encryption are analyzed. Finally, a comparative analysis of privacy preserving techniques with its applications are presented.

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

Survey on DDoS Attacks and Defense Mechanisms in Cloud and Fog Computing

2018 ◽  
Vol 10 (3) ◽  
pp. 61-83 ◽  
Author(s):  
Deepali Chaudhary ◽  
Kriti Bhushan ◽  
B.B. Gupta
Keyword(s):  
Cloud Computing ◽  
Defense Mechanisms ◽  
Low Cost ◽  
Fog Computing ◽  
Smart Devices ◽  
Cloud Environment ◽  
Security Issue ◽  
Process Data ◽  
Ddos Attack ◽  
Iot Devices

This article describes how cloud computing has emerged as a strong competitor against traditional IT platforms by offering low-cost and “pay-as-you-go” computing potential and on-demand provisioning of services. Governments, as well as organizations, have migrated their entire or most of the IT infrastructure to the cloud. With the emergence of IoT devices and big data, the amount of data forwarded to the cloud has increased to a huge extent. Therefore, the paradigm of cloud computing is no longer sufficient. Furthermore, with the growth of demand for IoT solutions in organizations, it has become essential to process data quickly, substantially and on-site. Hence, Fog computing is introduced to overcome these drawbacks of cloud computing by bringing intelligence to the edge of the network using smart devices. One major security issue related to the cloud is the DDoS attack. This article discusses in detail about the DDoS attack, cloud computing, fog computing, how DDoS affect cloud environment and how fog computing can be used in a cloud environment to solve a variety of problems.

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.

Confidentiality and Safekeeping Problems and Techniques in Fog Computing

2021 ◽  
pp. 1855-1873
Author(s):  
Nida Kauser Khanum ◽  
Pankaj Lathar ◽  
G. M. Siddesh
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Fog Computing ◽  
Video Stream ◽  
Security And Privacy ◽  
Surveillance Video ◽  
Speech Data ◽  
Real Time Applications ◽  
Privacy Issues ◽  
Intrusion Detection And Prevention

Fog computing is an extension of cloud computing, and it is one of the most important architypes in the current world. Fog computing is like cloud computing as it provides data storage, computation, processing, and application services to end-users. In this chapter, the authors discuss the security and privacy issues concerned with fog computing. The issues present in cloud are also inherited by fog computing, but the same methods available for cloud computing are not applicable to fog computing due to its decentralized nature. The authors also discuss a few real-time applications like healthcare systems, intelligent food traceability, surveillance video stream processing, collection, and pre-processing of speech data. Finally, the concept of decoy technique and intrusion detection and prevention technique is covered.

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