An Outline of Threats and Sensor Cloud Infrastructure in Wireless Sensor Network

Abstract

Wireless sensor networks are utilized in vital situations like military and commercial applications, traffic surveillance, habitat monitoring, and many other applications. WSNs have to face various issues and challenges in terms of memory, communication, energy, computation, and storage, which require efficient management of huge amount of sensor data. Therefore, storage is an important issue in the WSN. Emergence of Sensor-Cloud infrastructure overcomes several shortcomings of WSN such as storage capacity and offers high processing capabilities for huge sensor data. Security is also the major challenge that is faced by the sensor network. This chapter includes a brief overview of the importance of cloud computing in sensor networks and the goal of DDoS and Node Capture Attack in WSN. This chapter includes descriptions of different modeling techniques of Node Capture attack and various detection and key pre-distribution schemes to invent a new technique to improve network resilience against node capture attacks.

A Cloud-Based Machine Learning Approach to Reduce Noise in ECG Arrhythmias for Smart Healthcare Services

“…e estimations of TDEs (τ o and f d ) from returning signals, r(m, l), of the investigated RSs using equations (10) and (11) are simplified from state assessment as estimations of x k from known y k measurements where EKFs are analytical simplifications of Bayesian frameworks and conditional PDFs in Bayesian framework equations ( 12)-( 14) are assumed to be Gaussians as shown in the following equations:…”

“…In Doppler shift estimation, the proposed OIUKF-based estimation yields a decreased NMSE value of 0.00094, whereas other approaches such as EKFs, UKFs, and KLMS-(1) Set step sizes for TDEs and Doppler effects (2) Assign generation counter t � 1 and value for Max Gen//maximum generations (3) Assign initial population with step sizes of TDEs and Doppler effects (4) Repeat (5) Sort all the elephants according to their fitness via filter function (6) ci is the step size for all clans (7) ci do for all elephants j in the clan (8) Update xci, and generate xn, cj by equation ( 29), generate mutation is via mutation operator (9) if xci, j � xbest , ci then (10) Update xci, and generate xn, cj by equation ( 30) via step size in TDEs and Doppler effect (11) end if (12) end for (13) end for ( 14) Do this for all ci clans in the population (15) Get rid of the clan's worst elephant.ci by equation (32) and apply circle map (16) end for (17) Assess the population in light of the newly revised positions according to step size for TDEs and Doppler effect (18) modified NC give higher NMSE values of 0.36, 0.045, and 0.0092, respectively, after 5000 iterations in scenario 2 represented in Figure 4.…”

“…Rather than producing linear models, they approach nonlinear systems using first-order linearization, which results in linear models [ 11 ]. Because of their weak accuracy and stability in difficult situations with low SNRs and heavy-tailed clutters, they are unable to distinguish between targets with high certainty.…”

Hybrid Encryption Method for Health Monitoring Systems Based on Machine Learning

“…In order to ensure that the logic of the programme was tested at every step of its development, I fed erroneous inputs into it and observed the resulting error messages at each stage of its development. Each and every one of the loops and conditional statements is submitted to boundary condition testing and validation in order to guarantee that they work appropriately [ 19 ].…”

“…Hybrid cryptography is the combination of two technologies that act in a complimentary way, with each performing a separate role. Symmetric key algorithms generate keys that are used for bulk data encryption, while asymmetric key algorithms generate keys that are utilised for automated key distribution [ 19 ].…”