scholarly journals Distributed Address Table (DAT): A Decentralized Model for End-to-End Communication in IoT

2021 ◽  
Author(s):  
Mohammed B. M. Kamel ◽  
Peter Ligeti ◽  
Adam Nagy ◽  
Christoph Reich
Keyword(s):  
Fog Computing ◽  
Hash Table ◽  
Third Party ◽  
Distribution Model ◽  
Distributed Hash Table ◽  
Trusted Third Party ◽  
Proposed Model ◽  
Communication Scheme ◽  
Nat Traversal ◽  
Decentralized Model

AbstractTo achieve a fully connected network in Internet of Things (IoT) there are number of challenges that have to be overcome. Among those, a big challenge is how to keep all of the devices accessible everywhere and every time. In the IoT network, the assumption is that each IoT device can be reached by any client at any given time. In practice, this is not always possible and without a proper mechanism the nodes behind a NAT are unable to communicate with each other directly, and their addresses have to be shared through a trusted third party. This challenge becomes harder by taking into consideration that most NAT traversal approaches have been developed prior to rising of the IoT, without taking into account the constrained nature of the participating devices and mostly depend on a centralized entity. In this paper we proposed the Distributed Address Table (DAT), a decentralized, secure and lightweight address distribution model that allows any two nodes to get the addresses of the other end without relying on a trusted third party. Structured Peer-to-Peer (P2P) overlay by utilizing Distributed Hash Table (DHT) technique is generated as its underlying communication scheme to ensure that all participating devices are accessible at any given time. This is achieved through simple, yet secure and efficient decentralized model. The DAT adopts the edge/fog computing paradigms to ensure a decentralized address distribution. The results showed that the proposed model is efficient. In addition, the security properties of the proposed model have been defined and proved.

scholarly journals LaMRD: Location-Aware and Decentralized Multi-Layer Resource Discovery for IoT

2021 ◽  
Author(s):  
Mohammed B. M. Kamel ◽  
Peter Ligeti ◽  
Christoph Reich
Keyword(s):  
Fog Computing ◽  
Hash Table ◽  
General System ◽  
Resource Discovery ◽  
Distributed Hash Table ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Security Issues ◽  
Location Aware ◽  
Security Properties

The resources in the Internet of Things (IoT) network are distributed among different parts of the network. Considering huge number of IoT resources, the task of discovering them is challenging. While registering them in a centralized server such as a cloud data center is one possible solution, but due to billions of IoT resources and their limited computation power, the centralized approach leads to some efficiency and security issues. In this paper we proposed a location aware and decentralized multi layer model of resource discovery (LaMRD) in IoT. It allows a resource to be registered publicly or privately, and to be discovered in a decentralized scheme in the IoT network. LaMRD is based on structured peer-to-peer (p2p) scheme and follows the general system trend of fog computing. Our proposed model utilizes Distributed Hash Table (DHT) technology to create a p2p scheme of communication among fog nodes. The resources are registered in LaMRD based on their locations which results in a low added overhead in the registration and discovery processes. LaMRD generates a single overlay and it can be generated without specific organizing entity or location based devices. LaMRD guarantees some important security properties and it showed a lower latency comparing to the cloud based and decentralized resource discovery.  

scholarly journals Agent-Based Coordinated Control of Power Electronic Converters in a Microgrid

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1031
Author(s):  
Maryam Nasri ◽  
Herbert L. Ginn ◽  
Mehrdad Moallem
Keyword(s):  
Hash Table ◽  
Power Sharing ◽  
Distributed Hash Table ◽  
Power Electronic ◽  
Power Electronic Converters ◽  
Agent Based ◽  
Development Framework ◽  
Study Results ◽  
Set Up ◽  
Microgrid Control

This paper presents the implementation of an agent-based architecture suitable for the coordination of power electronic converters in stand-alone microgrids. To this end, a publish-subscribe agent architecture was utilized as a distributed microgrid control platform. Over a distributed hash table (DHT) searching overlay, the publish-subscribe architecture was identified based on a numerical analysis as a scalable agent-based technology for the distributed real-time coordination of power converters in microgrids. The developed framework was set up to deploy power-sharing distributed optimization algorithms while keeping a deterministic time period of a few tens of milliseconds for a system with tens of converters and when multiple events might happen concurrently. Several agents participate in supervisory control to regulate optimum power-sharing for the converters. To test the design, a notional shipboard system, including several converters, was used as a case study. Results of implementing the agent-based publish-subscribe control system using the Java Agent Development Framework (JADE) are presented.

Improved Blockchain Commodity Traceability System Using Distributed Hash Table

2020 ◽  
Author(s):  
Wu Junhui ◽  
Wu Tuolei ◽  
Wu Yusheng ◽  
Chen Jie ◽  
Lin Kaiyan ◽  
...  
Keyword(s):  
Hash Table ◽  
Distributed Hash Table ◽  
Traceability System

Enhancing Privacy in PUF-Cash through Multiple Trusted Third Parties and Reinforcement Learning

2022 ◽  
Vol 18 (1) ◽  
pp. 1-26
Author(s):  
Georgios Fragkos ◽  
Cyrus Minwalla ◽  
Eirini Eleni Tsiropoulou ◽  
Jim Plusquellic
Keyword(s):  
User Anonymity ◽  
Third Party ◽  
Security And Privacy ◽  
Machine Learning Techniques ◽  
User Privacy ◽  
Trusted Third Party ◽  
Physical Unclonable Functions ◽  
Learning Techniques ◽  
Direct Contrast ◽  
Debit Cards

Electronic cash ( e-Cash ) is a digital alternative to physical currency such as coins and bank notes. Suitably constructed, e-Cash has the ability to offer an anonymous offline experience much akin to cash, and in direct contrast to traditional forms of payment such as credit and debit cards. Implementing security and privacy within e-Cash, i.e., preserving user anonymity while preventing counterfeiting, fraud, and double spending, is a non-trivial challenge. In this article, we propose major improvements to an e-Cash protocol, termed PUF-Cash, based on physical unclonable functions ( PUFs ). PUF-Cash was created as an offline-first, secure e-Cash scheme that preserved user anonymity in payments. In addition, PUF-Cash supports remote payments; an improvement over traditional currency. In this work, a novel multi-trusted-third-party exchange scheme is introduced, which is responsible for “blinding” Alice’s e-Cash tokens; a feature at the heart of preserving her anonymity. The exchange operations are governed by machine learning techniques which are uniquely applied to optimize user privacy, while remaining resistant to identity-revealing attacks by adversaries and trusted authorities. Federation of the single trusted third party into multiple entities distributes the workload, thereby improving performance and resiliency within the e-Cash system architecture. Experimental results indicate that improvements to PUF-Cash enhance user privacy and scalability.

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 The Management Strategy of Metadata in Large-scale Network Storage System

2018 ◽  
Vol 228 ◽  
pp. 01011
Author(s):  
Haifeng Zhong ◽  
Jianying Xiong
Keyword(s):  
Large Scale ◽  
Storage System ◽  
Hash Table ◽  
Distributed Hash Table ◽  
Distributed Data ◽  
Mass Storage ◽  
Large Scale Network ◽  
Network Storage System ◽  
Mass Storage System ◽  
Scale Network

The wan Internet storage system based on Distributed Hash Table uses fully distributed data and metadata management, and constructs an extensible and efficient mass storage system for the application based on Internet. However, such systems work in highly dynamic environments, and the frequent entry and exit of nodes will lead to huge communication costs. Therefore, this paper proposes a new hierarchical metadata routing management mechanism based on DHT, which makes full use of the node stabilization point to reduce the maintenance overhead of the overlay. Analysis shows that the algorithm can effectively improve efficiency and enhance stability.

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