Enhancing Cloud Security Using Secured Binary-DNA Approach with Impingement Resolution and Complex Key Generation
Abstract
Cloud computing is used by the mass community. Categories of users using cloud resources are indifferent. Cloud security is thus the area of concern. This paper focuses on the security aspect by modifying the BDNA procedure. Although DNA-based encryption is considered one of the safest mechanisms for managing data within the cloud, it has a flaw of a Key Clash that is rectified using a random number generator and hashing mechanism within BDNA. The impingement occurs when the key generated with DNA has the same location as the earlier key location. The employed mechanism is termed as chain-based BDNA to improve security further also with impingement handling. It considered chaining-based BDNA and BDNA approach to tackling the problem of impingement with keys. The parameters considered are execution time in key formation, reliability, number of impingements. BDNA is based on binary encryption and to enhance the security further, excess three codes are merged within the proposed mechanism. The proposed system is implemented using Netbeans8.1 java-based platform along with cloudsim4.0. The overall result of encryption is least as time consumption is reduced and highest in terms of reliability as compared to the BDNA approach.
The proposed paper presents the implementation of cloud for online election system. Cloud technology is becoming more popular day by day and evolving very rapidly. Firstly in the paper we discussed what cloud is, it's types and services offered .The main focus is to make feasible of online E-voting for citizen and increasing the experience of voter through online .A facial recognition system is used for security purpose and Hadoop's HDFS to implement distributed file system. And at last we talked about the advantaged of using cloud for E-voting system over others scenario.
In this paper, a design of mattress for patients suffering from pressure ulcer has been proposed. When patients are lying in the bed due to their disability or disorder, the body cells do not function properly and leads to decaying because the body is pressurized and there is no circulation of air. This design helps in lifting the patient body in a periodic manner in order to prevent decay and hence the formation of ulcers is prevented. The most important is that patient does not feel any discomfort in the body when the movement is made. The proposed system helps the patient with moving disability by preventing them from becoming victims of bed sores.
In any heterogeneous multicore system, there are numerous amount of processors with different platform and all the processing units are fabricated on a common single unit preferably on a System on Chip. As there is a tremendous amount of parallelism encompassed in a multicore system, proper utilization of the cores is a big challenge in the current era. Hence a more automated software approach is required like an agent based graph coloring algorithm to find the free processor and schedule the tasks on the respective cores. Predominantly the entire process of scheduling the tasks on multicore system is based on arrival time of process. This paper incorporates the scheduling on the linux 2.6.11 kernel and GEMS simulator for multicore implementation. The core utilization in this type of agent scheduling is 50% more than the existing scheduling mechanism.
The increased of consumer concern on the originality of rice variety and the quality of rice leads to originality certification of rice by existing institutions. Technology helps human to perform evaluations of food grains using images of objects. This study developed a system used as a tool to identify rice varieties. Identification process was performed by analyzing rice images using image processing. The analyzed features for identification consisted of six color features, four morphological features, and two texture features. Classifier used LVQ neural network algorithm. Identification results using a combination of all features gave average accuracy of 70,3% with the highest classification accuracy level of 96,6% for Mentik Wangi and the lowest classification accuracy of 30% for Cilosari.
In the present work 8 dry samples have taken for quality analysis parboiled and non-parboiled rice variation type has been chosen here. And dimensional parameters have been measured in dry condition and after I determine treatment for preparing it as food image processing and machine learning have been applied successfully to analyze the experiment data in graduation of the right sample and accuracy of the gradation in this work is quite good. Experimental results have been validated with respect to the market price and customer choice.
The electrical signals in the brain can be analysed by performing spectral topographic brain mapping via Power Spectral Density. This brain mapping analysis can show the brain's different parts. Knowing dominant part(s) of the brain during reading activities enable to describe their attention levels when reading various books. The higher their attention levels are, the more information they receive during reading. The researchers used a qualitative approach with laboratory research using a small-group study of random behavior analysis method. The researchers recorded EEG data from 16 respondents (aged 18-22 years; eight males and eight females). EEG recordings took 15 minutes via a Simblee-based brain computer interface. The highest sampling rate was 200Hz, and the largest impedance was limited to 10Ω. EEG data with Power Spectral Density were analysed by using EEGLab Matlab-based software. Power Spectral Density was exploited to determine the high and low amplitude. The amplitude of this research was measured for the frequency range 15-18Hz (Beta1) showing the attention span. This study performed EEG recordings for reading tasks with different genres of books (academic science nonfiction book, general science nonfiction book, and science fiction book) to identify various attention cases. Attention measurement in reading can be used to detect students' reading skills in understanding science. The recording results showed that different genres of the books produced distinctive brain activities. The differences were based on the dominant part of the brain, amplitudes, and frequency patterns.
Internet of things (IOT) made the world connected to each other through Internet. These gadgets are important to store data, to exchange data and to collect data from other sources. These devices are not perfectly capable to cooperate with data centers directly based on some parameters such as latency, resource availability, load balancing, scheduling and security. Fog computing (FC) paradigm is introduced to overcome the problems of these parameters. As it cooperate with centralized data centers. This paper presents a survey on Fog computing terminology. Here, the term fog computing has been discussed. Further its architecture, its challenges are highlighted. An overview of further research work related to dynamic job scheduling has been discussed.