Orchestration Security Challenges in the Fog Computing

2020 ◽  
pp. 196-207
Author(s):  
Nerijus Šatkauskas ◽  
Algimantas Venčkauskas ◽  
Nerijus Morkevičius ◽  
Agnius Liutkevičius
Keyword(s):  
Fog Computing ◽  
Security Challenges

Security challenges in fog-computing environment: a systematic appraisal of current developments

2019 ◽  
Vol 5 (4) ◽  
pp. 209-233 ◽  
Author(s):  
Jimoh Yakubu ◽  
Shafi’i Muhammad Abdulhamid ◽  
Haruna Atabo Christopher ◽  
Haruna Chiroma ◽  
Mohammed Abdullahi
Keyword(s):  
Fog Computing ◽  
Computing Environment ◽  
Security Challenges ◽  
Systematic Appraisal

Security Challenges in Fog Computing

2019 ◽  
pp. 148-164
Author(s):  
Anshu Devi ◽  
Ramesh Kait ◽  
Virender Ranga
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Cloud Security ◽  
Trust Model ◽  
Security Threats ◽  
New Paradigm ◽  
Computing Model ◽  
Security Challenges ◽  
Security Concerns ◽  
Distinct Features

Fog computing is a term coined by networking giant Cisco. It is a new paradigm that extends the cloud computing model by conferring computation, storage, and application services at the periphery of networks. Fog computing is a gifted paradigm of cloud computing that facilitates the mobility, portability, heterogeneity, and processing of voluminous data. These distinct features of fog help to reduce latency and make it suitable for location-sensitive applications. Fog computing features raise new security concerns and challenges. The existing cloud security has not been implemented directly due to mobility, heterogeneity of fog nodes. As we know, IoT has to process large amount of data quickly; therefore, it has various functionality-driven applications that escalate security concerns. The primary aim of this chapter is to present the most recent security aspects such as authentication and trust, reputation-based trust model, rogue fog node and authentication at different level, security threats, challenges, and also highlights the future aspects of fog.

Fog Computing Security Challenges and Future Directions [Energy and Security]

2019 ◽  
Vol 8 (3) ◽  
pp. 92-96 ◽  
Author(s):  
Deepak Puthal ◽  
Saraju P. Mohanty ◽  
Sanjivani Ashok Bhavake ◽  
Graham Morgan ◽  
Rajiv Ranjan
Keyword(s):  
Fog Computing ◽  
Future Directions ◽  
Security Challenges

scholarly journals An Anomaly Mitigation Framework for IoT Using Fog Computing

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1565
Author(s):  
Muhammad Aminu Lawal ◽  
Riaz Ahmed Shaikh ◽  
Syed Raheel Hassan
Keyword(s):  
Smart Cities ◽  
Fog Computing ◽  
Multiclass Classification ◽  
Attack Detection ◽  
Gradient Boosting ◽  
Ip Address ◽  
Computing Paradigm ◽  
Security Challenges ◽  
Extreme Gradient Boosting ◽  
Boosting Algorithm

The advancement in IoT has prompted its application in areas such as smart homes, smart cities, etc., and this has aided its exponential growth. However, alongside this development, IoT networks are experiencing a rise in security challenges such as botnet attacks, which often appear as network anomalies. Similarly, providing security solutions has been challenging due to the low resources that characterize the devices in IoT networks. To overcome these challenges, the fog computing paradigm has provided an enabling environment that offers additional resources for deploying security solutions such as anomaly mitigation schemes. In this paper, we propose a hybrid anomaly mitigation framework for IoT using fog computing to ensure faster and accurate anomaly detection. The framework employs signature- and anomaly-based detection methodologies for its two modules, respectively. The signature-based module utilizes a database of attack sources (blacklisted IP addresses) to ensure faster detection when attacks are executed from the blacklisted IP address, while the anomaly-based module uses an extreme gradient boosting algorithm for accurate classification of network traffic flow into normal or abnormal. We evaluated the performance of both modules using an IoT-based dataset in terms response time for the signature-based module and accuracy in binary and multiclass classification for the anomaly-based module. The results show that the signature-based module achieves a fast attack detection of at least six times faster than the anomaly-based module in each number of instances evaluated. The anomaly-based module using the XGBoost classifier detects attacks with an accuracy of 99% and at least 97% for average recall, average precision, and average F1 score for binary and multiclass classification. Additionally, it recorded 0.05 in terms of false-positive rates.

scholarly journals IoT Registration and Authentication in Smart City Applications with Blockchain

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1323
Author(s):  
Célio Márcio Soares Ferreira ◽  
Charles Tim Batista Garrocho ◽  
Ricardo Augusto Rabelo Oliveira ◽  
Jorge Sá Silva ◽  
Carlos Frederico Marcelo da Cunha Cavalcanti
Keyword(s):  
Time Management ◽  
Smart Cities ◽  
Fog Computing ◽  
Denial Of Service ◽  
Urban Environments ◽  
Edge Computing ◽  
Primary Data ◽  
Security Challenges ◽  
Security Information ◽  
Iot Devices

The advent of 5G will bring a massive adoption of IoT devices across our society. IoT Applications (IoT Apps) will be the primary data collection base. This scenario leads to unprecedented scalability and security challenges, with one of the first areas for these applications being Smart Cities (SC). IoT devices in new network paradigms, such as Edge Computing and Fog Computing, will collect data from urban environments, providing real-time management information. One of these challenges is ensuring that the data sent from Edge Computing are reliable. Blockchain has been a technology that has gained the spotlight in recent years, due to its robust security in fintech and cryptocurrencies. Its strong encryption and distributed and decentralized network make it potential for this challenge. Using Blockchain with IoT makes it possible for SC applications to have security information distributed, which makes it possible to shield against Distributed Denial of Service (DDOS). IoT devices in an SC can have a long life, which increases the chance of having security holes caused by outdated firmware. Adding a layer of identification and verification of attributes and signature of messages coming from IoT devices by Smart Contracts can bring confidence in the content. SC Apps that extract data from legacy and outdated appliances, installed in inaccessible, unknown, and often untrusted urban environments can benefit from this work. Our work’s main contribution is the development of API Gateways to be used in IoT devices and network gateway to sign, identify, and authorize messages. For this, keys and essential characteristics of the devices previously registered in Blockchain are used. We will discuss the importance of this implementation while considering the SC and present a testbed that is composed of Blockchain Ethereum and real IoT devices. We analyze the transfer time, memory, and CPU impacts during the sending and processing of these messages. The messages are signed, identified, and validated by our API Gateways and only then collected for an IoT data management application.

scholarly journals The Security of Big Data in Fog-Enabled IoT Applications Including Blockchain: A Survey

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1788 ◽  
Author(s):  
Noshina Tariq ◽  
Muhammad Asim ◽  
Feras Al-Obeidat ◽  
Muhammad Zubair Farooqi ◽  
Thar Baker ◽  
...  
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
Critical Infrastructure ◽  
Fog Computing ◽  
Security Requirements ◽  
Security Challenges ◽  
Depth Analysis ◽  
Comprehensive Comparison ◽  
Attack Surface ◽  
Criminal Groups

The proliferation of inter-connected devices in critical industries, such as healthcare and power grid, is changing the perception of what constitutes critical infrastructure. The rising interconnectedness of new critical industries is driven by the growing demand for seamless access to information as the world becomes more mobile and connected and as the Internet of Things (IoT) grows. Critical industries are essential to the foundation of today’s society, and interruption of service in any of these sectors can reverberate through other sectors and even around the globe. In today’s hyper-connected world, the critical infrastructure is more vulnerable than ever to cyber threats, whether state sponsored, criminal groups or individuals. As the number of interconnected devices increases, the number of potential access points for hackers to disrupt critical infrastructure grows. This new attack surface emerges from fundamental changes in the critical infrastructure of organizations technology systems. This paper aims to improve understanding the challenges to secure future digital infrastructure while it is still evolving. After introducing the infrastructure generating big data, the functionality-based fog architecture is defined. In addition, a comprehensive review of security requirements in fog-enabled IoT systems is presented. Then, an in-depth analysis of the fog computing security challenges and big data privacy and trust concerns in relation to fog-enabled IoT are given. We also discuss blockchain as a key enabler to address many security related issues in IoT and consider closely the complementary interrelationships between blockchain and fog computing. In this context, this work formalizes the task of securing big data and its scope, provides a taxonomy to categories threats to fog-based IoT systems, presents a comprehensive comparison of state-of-the-art contributions in the field according to their security service and recommends promising research directions for future investigations.

scholarly journals Intrusion Detection System Based on Decision Tree over Big Data in Fog Environment

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Kai Peng ◽  
Victor C. M. Leung ◽  
Lixin Zheng ◽  
Shangguang Wang ◽  
Chao Huang ◽  
...  
Keyword(s):  
Big Data ◽  
Intrusion Detection ◽  
Decision Tree ◽  
Intrusion Detection System ◽  
Detection System ◽  
Fog Computing ◽  
Full Dataset ◽  
Security Challenges ◽  
Protection Technology ◽  
Decision Tree Method

Fog computing, as the supplement of cloud computing, can provide low-latency services between mobile users and the cloud. However, fog devices may encounter security challenges as a result of the fog nodes being close to the end users and having limited computing ability. Traditional network attacks may destroy the system of fog nodes. Intrusion detection system (IDS) is a proactive security protection technology and can be used in the fog environment. Although IDS in tradition network has been well investigated, unfortunately directly using them in the fog environment may be inappropriate. Fog nodes produce massive amounts of data at all times, and, thus, enabling an IDS system over big data in the fog environment is of paramount importance. In this study, we propose an IDS system based on decision tree. Firstly, we propose a preprocessing algorithm to digitize the strings in the given dataset and then normalize the whole data, to ensure the quality of the input data so as to improve the efficiency of detection. Secondly, we use decision tree method for our IDS system, and then we compare this method with Naïve Bayesian method as well as KNN method. Both the 10% dataset and the full dataset are tested. Our proposed method not only completely detects four kinds of attacks but also enables the detection of twenty-two kinds of attacks. The experimental results show that our IDS system is effective and precise. Above all, our IDS system can be used in fog computing environment over big data.

scholarly journals Access Control of EHR Records in a Heterogeneous Cloud Infrastructure

2021 ◽  
Vol 25 (2) ◽  
pp. 485-516
Author(s):  
Zoltán Szabó ◽  
Vilmos Bilicki
Keyword(s):  
Access Control ◽  
Fog Computing ◽  
Cloud Infrastructure ◽  
Security Framework ◽  
Healthcare Applications ◽  
Public And Private ◽  
Healthcare Data ◽  
Security Challenges ◽  
Special Cases ◽  
Heterogeneous Cloud

Since the advent of smartphones, IoT and cloud computing, we have seen an industry-wide requirement to integrate different healthcare applications with each other and with the cloud, connecting multiple institutions or even countries. But despite these trends, the domain of access control and security of sensitive healthcare data still raises a serious challenge for multiple developers and lacks the necessary definitions to create a general security framework addressing these issues. Taking into account newer, more special cases, such as the popular heterogeneous infrastructures with a combination of public and private clouds, fog computing, Internet of Things, the area becomes more and more complicated. In this paper we will introduce a categorization of these required policies, describe an infrastructure as a possible solution to these security challenges, and finally evaluate it with a set of policies based on real-world requirements.

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