NCATCSIT 2016- National Conference on Advanced Trends in Computer Science & Information Technology

"NCATCSIT 2016 Conference Papers "

FINDING A NEAREST NODE BY CIRCULATING SAMPLE SACHET[ ]


Within this paper, motivated through the growing prevalence of multipack reception (MPR) technologies for example CDMA and MIMO, we study neighbor discovery in MPR systems that permit packets from multiple synchronized transmitters to become received effectively in a receiver. Neighbor discovery is among the steps in configuring and controlling a radio network.

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SCABLE AND SECURE TRUTHFUL DETECTION OF PACKET DROPPING ATTACKS IN WIRELESS AD HOC NETWORKS[ ]


Link error and malicious packet dropping are two sources for packet losses in multi-hop wireless ad hoc network. While observing a sequence of packet losses in the network, whether the losses are caused by link errors only, or by the combined effect of link errors and malicious drop is to be identified. In the insider-attack case, whereby malicious nodes that are part of the route exploit their knowledge of the communication context to selectively drop a small amount of packets critical to the network performance. Because the packet dropping rate in this case is comparable to the channel error rate, conventional algorithms that are based on detecting the packet loss rate cannot achieve satisfactory detection accuracy.

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SCALABLE AND SECURE DATA AGGREGATION TECHNIQUE FOR W S N IN THE OCCURRENCE OF CONSPIRACY ATTACKS[ ]


Due to limited computational power and energy resources, aggregation of data from multiple sensor nodes done at the aggregating node is usually accomplished by simple methods such as averaging. However such aggregation is known to be highly vulnerable to node compromising attacks. Since WSN are usually unattended and without tamper resistant hardware, they are highly susceptible to such attacks. Thus, ascertaining trustworthiness of data and reputation of sensor nodes is crucial for WSN. As the performance of very low power processors dramatically improves, future aggregator nodes will be capable of performing more sophisticated data aggregation algorithms, thus making WSN less vulnerable. Iterative filtering algorithms hold great promise for such a purpose. Such algorithms simultaneously aggregate data from multiple sources and provide trust assessment of these sources, usually in a form of corresponding weight factors assigned to data provided by each source. To address security issue, an improvement for iterative filtering techniques is proposed by providing an initial approximation for such algorithms which makes them not only collusion robust, but also more accurate and faster converging.

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THE LOCATIONS OF IP SPOOFERS FROM PATHWAY BACKSCATTER IN PASSIVE IP TRACEBACK[ ]


It isvery long known attackers may use forged source IP address to obscure their real locations. To capture the spoofers, a number of IP traceback mechanisms have been proposed. However, due to the challenges of deployment, there has been not a widely adopted IP traceback solution, at least at the Internet level. As a result, the mist on the locations of spoofers has never been dissipated till now. This paper proposes passive IP traceback (PIT) that bypasses the deployment difficulties of IP traceback techniques. PIT investigates Internet Control Message Protocol error messages (named path backscatter) triggered by spoofing traffic, and tracks the spoofers based on public available information (e.g., topology). In this way, PIT can find the spoofers without any deployment requirement. This paper illustrates the causes, collection, and the statistical results on path backscatter, demonstrates the processes and effectiveness of PIT, and shows the captured locations of spoofers through applying PIT on the path backscatter data set. These results can help further reveal IP spoofing, which has been studied for long but never well understood. Though PIT cannot work in all the spoofing attacks, it may be the most useful mechanism to trace spoofers before an Internet-level traceback system has been deployed in real.

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A DATA-COLLECTOR METHOD FOR INFORMATION GENERATION IN OPEN NETS[ ]


This paper presents three novel schemes for customers to identify fake spatial snapshot and moving top-k query results being an effort to promote the sensible deployment and utilization of the suggested system. The effectiveness and efficiency in our schemes are completely examined and evaluated. This paper views a manuscript distributed system for collaborative location-based information generation and discussing which become more and more popular because of the explosive development of Internet-capable and placement-aware mobile products. The information collector gathers result about points-of-interest (POIs) from data contributing factors, while LBSPs purchase POI data many techniques from the information collector and permit customers to do spatial top-k queries which request the POIs inside a certain region along with the greatest k ratings to have an interested POI attribute. Used, LBSPs are entrusted and could return fake query recent results for various bad motives, e.g., in support of POIs prepared to pay. The machine is having a data collector, data contributing factors, location-based providers (LBSPs), and system customers.

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