Pm3110 Unit 3 Lab Report

Figure ‎3 13 : A photo and SEM micrographs of flank face; (a) a photo of flank face and tool wear region (b) SEM micrograph of flank face; a micro fracture is shown (c) highly magnified flank face shows some holes and scratches probably caused by TiC particles and a smooth adhered layer which has covered the scratches and grooves. It can be seen that the sharp cutting edge of an unused tool has been chamfered after 1 second of machining and has left a sheared surface at the wear land.

Place your pH meter in your sample and begin reading. Once your pH meter is placed in your sample, press the measure button and leave the pH meter in your sample for approximately 1-2 minutes.

An extension of this approach is in-network aggregation which aggregates data progressively as it is passed through a network. In-network data aggregation can reduce the data packet size, the number of data transmissions and the number of nodes involved in gathering data from a WSN. Therefore, in the field of WSNs, privacy-preserving data aggregation is becoming a hot issue in WSNs. To address this issue, some protocols have been proposed. In this, they provide a comprehensive summary and comparison of the existing privacy-preserving data aggregation protocols for WSNs. WSN is related to privacy-preserving data aggregation protocols (Ping et al 2012). In the authors reviewed privacy-preserving techniques for protecting two types of private information: data-oriented and context-oriented privacy. First, authors focuses only on data privacy in order to provide detailed overviews of the existing privacy-preserving data aggregation protocols for WSNs (Ping et al 2012). Two main security challenges in secure data aggregation are confidentiality and integrity of data (Sugandhi et al 2013). While traditionally encryption is used to provide end to end confidentiality in Wireless Sensor Network (WSN), the aggregators in a secure data aggregation scenario need to decrypt the encrypted data to perform aggregation. Thus, while data aggregation improves energy efficiency of a network, it complicates the existing

Abstract— the data aggregation is mostly used energy efficient mechanism in Wireless Sensor Networks (WSN). Preserving data security is a challenging problem in wireless sensor networks. Because of the resource characteristic, security & privacy issues there in assume critical investigation. Many aspects of investigation, one has been the design of a secure clustering protocol in which a sensed data or information to be delivered to an appropriate receiver securely and efficiently with least amount of energy consumption. Different methods are used to solve problem of security. We shows that different technique and method in this paper.

With the recent technological advancements of smaller sensor devices enabling ubiquitous sensing capabilities and driven by the adoption of global standard technologies, Wireless Sensor networks (WSN) are evolving as one of the most significant technologies of 21st century (Ruiz-Garcia, Lunadei, Barreiro, & Robla, 2009). Though wired networks provide more stable and reliable communication, sensor networks with dense wireless networks of small, low cost sensors collecting and disseminating environment data has facilitated monitoring and controlling of physical environments from remote locations with better accuracy. Moreover, with the unique characteristics of flexibility, energy efficiency, distributed intelligence, low cost and most importantly with very good monitoring capabilities Wireless sensor networks serve wide range of applications in various fields such as remote environmental monitoring, home security, industry applications, military purposes such as target tracking along with preparing a ubiquitous computing environment (Ruiz-Garcia et al., 2009).

For cluster-based WSNs (CWSNs), secure data transmission, where like dynamically and periodically the clusters are shaped. The analysis problems associated with WSNs security and knowledge aggregation with reference to the protection and security analysis against various attacks, we show the quality of being usable of the SET-IBS and SET-IBOOS protocols. For a fuzzy approach and SET-IBS formula employing a combination in our planned system, for WSNs a replacement routing technique to extend network amount of some time from the supply to the destination by affirmative the best remaining battery power. The proposal is to envision an optimum routing path, minimum vary of hops, and minimum traffic load in terms of leveling energy consumption and for some time maximization of network quantity for the planned technique. To demonstrate the effectiveness, in two completely different topographical areas using similar routing criteria with the A-star search formula we tend to match our approach and fuzzy approach.

Thus, this protocol can be applied to a wide range of mobile sensing systems with various scales, plaintext spaces, aggregation loads and resource constraints. Based on the Sum aggregation protocol, he also proposed two schemes to derive the Min aggregate of time-series data. One scheme can obtain the accurate Min while the other one can obtain an approximate Min with provable error guarantee at much lower cost.

Abstract— In this paper data aggregation using multipath routing is proposed. In existing system, under hybrid scheme, it each sensor nodes generates information by sensing its physical environment and transmit to sink by multi hop communication. In network aggregation computation intermediate forwarding nodes can substantially increase the network life time but amount of data contained in single packet and make the system vulnerability to packet loss. Instead of retransmission it takes the additional time. Multi path routing multipath multi speed routing protocol is used to improving the performance of data aggregation due to avoiding these problems.

Ju young Kim et al presented a study of the different threats, attacks and vulnerabilities for Wireless Sensor Networks (WSNs). In node capture attack, an attacker gains complete gain over a node by physically accessing the node. Then the attacker can remove the cryptographic functions and get the access to the data stored on that captured node. The countermeasures for reducing the risk of eavesdropping on wireless transmissions are the use of encryption to preserve confidentiality and it should be more difficult to locate and intercept the wireless signals [5]. Hardware attestation, software authentication and validation are the countermeasures against the software attacks. The different classes of these threats are defined to identify a possible countermeasure

This section gives the description about the sensors, respective public and private key pair model and event generation in the network. This is followed by the threat model of the network and the kind of adversaries which pose threat to the network. The design goals of the proposed scheme are also listed.

Wireless sensor networks (WSN) are self- governing sensors that are widely distributed in the respective environment. They are also referred as wireless sensor and actuator networks (WSAN). They are used to observe physical or environmental conditions, for example, temperature, sound, natural activities etc. They collect data from each active node and pass it to the network to the centralized location. There are many flaws occurred in wireless sensor network like user authentication as well as data travel in the network is not so much secure. We are developing a technique in which firstly we are allowing the user to pass the hard security authentication scheme and then the user can join the network. Further we are also providing a secure file transmission in network via public and private key concept. In this way we maintain the secure and authenticated transmission of data in predescribed environment.

Clustering of Wireless Sensor Network is important to increase the network scalability. Cluster Based Wireless sensor Network (CWSN) are organised in hierarchical manner. In CWSN a leader node called Cluster Head (CH) is responsible for aggregation of data from the leaf nodes which are present in the Cluster. In this paper we will discuss how to transmit the data securely and efficiently over the network.

The collection of sensor nodes by enabling cooperation, coordination and collaboration among sensor nodes is formed Wireless Sensor Network (WSN); the WSN consists of multiple autonomous nodes with a base station.

Generally, the success of wireless sensor network depends on a vital secure data aggregation technique that accomplishes the security goals [8]. However, the security models and protocols of sensor networks are different from those that are used in other types of networks due to their hardware resources and power constraints. Therefore, efficient, secure data aggregation techniques are required to deal with energy efficiency, data accuracy, latency and protecting data.

A Survey Paper On Prevention of Data Aggregation in Wireless Sensor Network By Removing Attacker Impact By Node Recovery