Information extraction from sensor networks using the Watershed transform algorithm

Wireless sensor networks are an effective tool to provide fine resolution monitoring of the physical environment. Sensors generate continuous streams of data, which leads to several computational challenges. As sensor nodes become increasingly active devices, with more processing and communication resources, various methods of distributed data processing and sharing become feasible. The challenge is to extract information from the gathered sensory data with a specified level of accuracy in a timely and power-efficient approach. This paper presents a new solution to distributed information extraction that makes use of the morphological Watershed algorithm. The Watershed algorithm dynamically groups sensor nodes into homogeneous network segments with respect to their topological relationships and their sensing-states. This setting allows network programmers to manipulate groups of spatially distributed data streams instead of individual nodes. This is achieved by using network segments as programming abstractions on which various query processes can be executed. Aiming at this purpose, we present a reformulation of the global Watershed algorithm. The modified Watershed algorithm is fully asynchronous, where sensor nodes can autonomously process their local data in parallel and in collaboration with neighbouring nodes. Experimental evaluation shows that the presented solution is able to considerably reduce query resolution cost without scarifying the quality of the returned results. When compared to similar purpose schemes, such as “Logical Neighborhood”, the proposed approach reduces the total query resolution overhead by up to 57.5%, reduces the number of nodes involved in query resolution by up to 59%, and reduces the setup convergence time by up to 65.1%

Modelling Clustering of Wireless Sensor Networks with Synchronised Hyperedge Replacement

This paper proposes Synchronised Hyperedge Replacement (SHR) as a suitable modelling framework for Wireless Sensor Networks (WSNs). SHR facilitates explicit modelling of WSNs applications environmental conditions (that significantly affect applications performance) while providing a sufficiently high level of abstraction for the specification of the underling coordination mechanisms. Because it is an intractable problem to solve in distributed manner, and distribution is important, we propose a new Nutrient-flow-based Distributed Clustering (NDC) algorithm to be used as a working example. The key contribution of this work is to demonstrate that SHR is sufficiently expressive to describe WSNs algorithms and their behaviour at a suitable level of abstraction to allow onward analysis

Buffer-aided 5G cooperative networks: Considering the source delay

© 2019 Association for Computing Machinery. Applying relays employed with data buffers drastically enhance the performance of cooperative networks. However, lengthening the packet delay is still a serious challenge for cooperative networks. This paper thoroughly studies a new factor affecting the packet delay which is the source delay. This factor plays a key role in calculating the total delay that messages encounter before reaching their destination. This delay is crucial especially in applications that require their messages to get transmitted as fast as possible. Markov chain is employed to model the system and analyze the source delay. Numerical simulations verify the analytical model, the results show that buffer-aided relays can beat non-buffer relays in terms of average packet delay, especially at low signal to noise ratio (SNR) range. This makes adding buffers to relays an attractive solution for the packet delay in 5G applications

Data preservation system using BoCA : Blockchain-of-Custody Application

The recent growth in popularity of blockchains has been primarily fueled by their support of cryptocurrencies and smart contracts. However, a blockchain is primarily a distributed, trustworthy ledger and one of its greatest features is its ability to preserve data in a robust and verifiable manner. In this paper we present a general Blockchain-of-Custody Application proof-of-concept. BoCA allows data to be preserved on the blockchain in a transparent and verifiable way. We present our application and discuss the advantages this approach has over the state-of-the-art, as well as discuss different scenarios in which it could be used

Towards robust autonomous driving systems through adversarial test set generation

Correct environmental perception of objects on the road is vital for the safety of autonomous driving. Making appropriate decisions by the autonomous driving algorithm could be hindered by data perturbations and more recently, by adversarial attacks. We propose an adversarial test input generation approach based on uncertainty to make the machine learning (ML) model more robust against data perturbations and adversarial attacks. Adversarial attacks and uncertain inputs can affect the ML model’s performance, which can have severe consequences such as the misclassification of objects on the road by autonomous vehicles, leading to incorrect decision-making. We show that we can obtain more robust ML models for autonomous driving by making a dataset that includes highly-uncertain adversarial test inputs during the re-training phase. We demonstrate an improvement in the accuracy of the robust model by more than 12%, with a notable drop in the uncertainty of the decisions returned by the model. We believe our approach will assist in further developing risk-aware autonomous systems.acceptedVersio

A Distributed Cellular Automaton Algorithm for Barrier Formation in Mobile Sensor Networks

There is growing interest in the application of wireless sensor networks to the problem of monitoring international borders. In this application, barrier coverage is essential in order to ensure that intrusion events are detected. The use of mobile sensors has the potential to enable barrier coverage to be achieved and maintained in hostile environments where the orderly deployment of sensors is impossible. In this paper, we present a distributed cellular automaton based algorithm for autonomous deployment of mobile sensors to achieve barrier coverage. We compare the algorithm with an existing, state-of- the-art algorithm and show that our proposed algorithm achieves barrier coverage with competitive or improved energy cost, and with a communication overhead that is orders of magnitude less. For dense deployment scenarios, our algorithm uses up to six times less energy than the state-of-the-art algorithm

A distributed data extraction and visualisation service for wireless sensor networks

With the increase in applications of wireless sensor networks, data extraction and visualisation have become a key issue to develop and operate these networks. Wireless sensor networks typically gather data at a discrete number of locations. By bestowing the ability to predict inter-node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. The aim of this thesis is to develop a service for maximising information return from large scale wireless sensor networks. This aim will be achieved through the development of a distributed information extraction and visualisation service called the mapping service. In the distributed mapping service, groups of network nodes cooperate to produce local maps which are cached and merged at a sink node, producing a map of the global network. Such a service would greatly simplify the production of higher-level information-rich representations suitable for informing other network services and the delivery of field information visualisations. The proposed distributed mapping service utilises a blend of both inductive and deductive models to successfully map sense data and the universal physical principles. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of a sense modality. Furthermore, the proposed mapping service responds to changes in the environmental conditions that may impact the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a newdistributed self-adaptation algorithm, Virtual Congress Algorithm,which is based on the concept of virtual congress is proposed, with the goal of saving more power and generating more accurate data visualisation.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Secure Key Exchange Against Man-in-the-Middle Attack: Modified Diffie-Hellman Protocol

One of the most famous key exchange protocols is Diffie-Hellman Protocol (DHP) which is a widely used technique on which key exchange systems around the world depend. This protocol is simple and uncomplicated, and its robustness is based on the Discrete Logarithm Problem (DLP). Despite this, he is considered weak against the man-in-the-middle attack. This article presents a completely different version of the DHP protocol. The proposed version is based on two verification stages. In the first step, we check if the pseudo-random value α that Alice sends to Bob has been manipulated! In the second step, we make sure that the random value β that Bob sends to Alice is not manipulated. The man-in-the-middle attacker Eve can impersonate neither Alice nor Bob, manipulate their exchanged values, or discover the secret encryption key

Threats on the horizon: Understanding security threats in the era of cyber-physical systems

Disruptive innovations of the last few decades, such as smart cities and Industry 4.0, were made possible by higher integration of physical and digital elements. In today's pervasive cyber-physical systems, connecting more devices introduces new vulnerabilities and security threats. With increasing cybersecurity incidents, cybersecurity professionals are becoming incapable of addressing what has become the greatest threat climate than ever before. This research investigates the spectrum of risk of a cybersecurity incident taking place in the cyber-physical-enabled world using the VERIS Community Database. The findings were that the majority of known actors were from the US and Russia, most victims were from western states and geographic origin tended to reflect global affairs. The most commonly targeted asset was information, with the majority of attack modes relying on privilege abuse. The key feature observed was extensive internal security breaches, most often a result of human error. This tends to show that access in any form appears to be the source of vulnerability rather than incident specifics due to a fundamental trade-off between usability and security in the design of computer systems. This provides fundamental evidence of the need for a major reevaluation of the founding principles in cybersecurity

Policy specification and verification for blockchain and smart contracts in 5G networks

open access articleBlockchain offers unprecedented opportunities for innovation in financial transactions. A whole new world of opportunities for banking, lending, insurance, money transfer, investments, and stock markets awaits. However, the potential for wide-scale adoption of blockchain is hindered with cybersecurity and privacy issues. We provide an overview of the risks and security requirements and give an outlook for future research that could be helpful in solving some of the challenges. We also present an approach for policy specification and verification of financial transactions based on smart contracts