Search

Car parking issue has some problems with how to control the number of the car inside it, how to monitor the movement in/out side of the parking lot, how to check whether there is a place inside for more cars or not and the safety to park. It leads to traffic congestion and also pollution. So we have a need to maintain the vehicle park management in order to reduce the wastage of time. If we see in the larger cities when we visit the shopping malls or tourist places or any other commercial areas there arises a problem for parking of our vehicle. We have so many methods of parking systems such as using WSN, RFID methods. But the major drawback of those systems is they help us to find the available spaces for parking but not the exact location of those spaces. It can be overcome by using Automatic Car Parking System using IR Sensors.

In this work, the authors consider the newly selected Hash Secure (SHA-3) algorithm on FPGA Gateway. The design is logically optimized for zone efficiency by combining the Rho steps and the one-pass algorithm. Logically recording these three steps registers leads to usage 16% of the logical resources for all implementations. This in turn reduces the latency and increases the maximum operating frequency of the project. It uses only 240 sections and has a frequency of 301.02 MHz compared to the design results with the previous FPGA implementation described in SHA3-512, the design shows the Throughput-Per-Slice (TPS) ratio of 30, 1.

This article deals with the clear analysis and experimental simulation results of the modified AES-128-bit algorithm which can be personalized. To improve this technique, we introduced the high-level increased parallelism scheme which will reflect even in Mi columns of the AES architecture. By using this technique, we can increase the throughput efficiency and is implemented on Quartus of FPGA device. With this technique, usage can increase the stack usage for 5% more with a minimum reduction of 30% area.

A bank plays a vital role in people's life. A bank connects customers with deficit assets to customers with surplus assets .Net managing an account alludes to the framework that empowers bank clients to get to records and general data on bank items and administrations through individual computer(PC) or other shrewd gadgets and it also performs virtual banking functions. Bank's first aim is to achieve the trust of customers then customers report their personal details, Security of the customers is the prime concern of the banks and it has its own measures to secure client details and transactions i.e.; both online and offline. The major security measures are confidentiality, integrity, availability and accuracy. Apart from all the security measures, banking is prone to hacking attacks due to open source of public. This paper mainly aims to providesecurity to online banking using graphical passwords authentication techniques like recall and recognition.

Discovering interesting rules has become a basis for proficient decision making from past decades. Numbers of mining techniques are used for generating association rules. Apriori is one of the mining techniques for discovering association rules. Optimization of rules has become an important task as apriori generates plenty of rules. In this paper, Multi Objective Adaptive Weight Firefly (MOAWF) algorithm is proposed for association rule optimization and the proposed algorithm is applied on the rules generated using apriori. Here association rule mining is viewed as a multi-objective problem instead of single objective. Confidence, support and comprehensibility are considered for measuring multi-objective. The performance of proposed algorithm is better when compared to the existing algorithms.

Data mining is gaining importance due to huge amount of data available. Retrieving information from the warehouse is not only tedious but also difficult in some cases. The most important usage of data mining is customer segmentation in marketing, shopping cart analyzes, management of customer relationship, campaign management, Web usage mining, text mining, player tracking and so on. In data mining, association rule mining is one of the important techniques for discovering meaningful patterns from large collection of data. Discovering frequent itemsets play an important role in mining association rules, sequence rules, web log mining and many other interesting patterns among complex data. This paper presents a literature review on different techniques for mining frequent itemsets.

For many organizations, keeping data private and secure has also become a compliance requirement. Cloud providers offering Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) offer a “shared responsibility” model for customer applications and data, so companies that are migrating to the cloud are responsible for finding a solution. This research paper proposes a system, which combines encryption with key management to protect critical data in public, private and hybrid cloud environments.

One of the major tasks of data mining is association rule mining, which is used for finding the interesting relationships among the items in itemsets of huge database. Aproiri is the familiar algorithm of association rule mining for generating frequent itemsets. Apriori uses minimum support threshold to find frequent items. In this paper, an algorithm called hybridization of ABC with BAT algorithm is proposed which is used for optimization of association rules. Instead of onlooker bee phase of ABC, random walk of BAT is used in order to increase the exploration. Hybridized ABC with BAT algorithm is applied on the rules generated from apriori algorithm, for optimizing association rules. The experiments are performed on datasets taken from UCI repository which show the proposed work performance and proposed methodology can effectively optimize association rules when compared to the existing algorithms. In the paper, we also proved that the rules generated using proposed work are simple and comprehensible.

Adopting cloud computing is a complex decision involving many factors. This paper focuses on the central issues of cloud computing security. The Cloud Computing Architectural Framework, provides a conceptual framework to help evaluate initial cloud risks and inform security decisions. It's a quick method for evaluating the tolerance for moving an asset to various cloud computing models. The keys to understanding how cloud architecture impacts security architecture are a common and concise lexicon, coupled with a consistent taxonomy of offerings by which cloud services and architecture can be deconstructed, mapped to a model of compensating security and operational controls, risk assessment and management frameworks, and in turn to compliance standards. Understanding the relationships and dependencies between Cloud computing models is critical to understanding Cloud computing security risks. The purpose of this paper is to provide needed context for assistance in making educated risk management decisions regarding their cloud adoption strategies.

Encryption is the process of converting the data from readable format into unreadable format with help of any mathematical expression or sometimes with the help of key. On the other hand decryption is the reverse process of encryption with help of same key used at encryption or with the help of some other key. The paper presents the different methodology used for encryption and decryption. Several methods presented in the literature are reviewed. The methods- Rivest-Shamir-Adlemen algorithm, Data Encryption Standard, Advanced Encryption Standard and three different Secure Hash Algorithm are reviewed and implemented using various FPGA devices. The power consumption, delay and area are analyzed and compared. From the analyses it is been found that the performance of AES and SHA3 are better when compared to other algorithms. These algorithms provide high security when compared to rest of the methods.

This paper presents a mobile application based on providing Location Based Services (LBS) using Global Positioning System (GPS) as a location provider. The main objective of this work is to design and implement a client server system that helps the system to know the location of their employees and also alerts the employee when they are nearby. The mobile application was implemented using J2ME where the most recent APIs and other older APIs were combined together in order to make the application reliable on all types of mobiles. The server was implemented using J2EE technologies. The type of the Database used in the system was MySQL. The average location accuracy of the application is about couple of meters.

A Wireless Ad hoc Network consists of mobile nodes with energy constrained batteries. In this paper, we have proposed an Optimized Lifetime Multicast Tree (OLMT) algorithm that constructs a minimum energy multicast tree resulting in minimum total transmission power consumption,thereby increasing the lifetime of the network. We observe that, simulations carried on NS2 provides significant improvement in the number of multicast requests realised when compared with earlier works.

Analysis of reflected seismic waves gives the information about the earth and its inner core. This aids in monitoring earthquake, petroleum exploration, determination of the earth’s core structure, etc. Wavelet transforms is an efficient tool for analysis of seismic reflected signals. These transforms helps in complete extraction of the seismic signal buried in noise. In this paper an attempt is made to analyze a synthetic seismic signal by using Klauder wavelets. The synthetic seismic signal is extracted by convoluting with the Klauder wavelet. Noise is completely removed as the wavelet spans a large spectrum of signals.