A World of Cyber Attacks (A Survey)

The massive global network that connects billions of humans and millions of devices and allow them to communicate with each other is known as the internet. Over the last couple of decades, the internet has grown expeditiously and became easier to use and became a great educational tool. Now it can used as a weapon that can steal someone’s identity, expose someone’s financial information, or can destroy your networking devices. Even in the last decade, there have been more cyber attacks and threats destroying major companies by breaching the databases that have millions of personal information that can be sold online. Cyber-attacks can happen numerous ways and can happen when no one is looking. In this paper we survey several cyber-attacks that has been around and the current ones which will give the readers a quick overview of the finding of this survey. We also arrived at a conclusion that education in this field is very important for companies and individuals to stay safe

A Human-Centric Approach to Data Fusion in Post-Disaster Managment: The Development of a Fuzzy Set Theory Based Model

It is critical to provide an efficient and accurate information system in the post-disaster phase for individuals\u27 in order to access and obtain the necessary resources in a timely manner; but current map based post-disaster management systems provide all emergency resource lists without filtering them which usually leads to high levels of energy consumed in calculation. Also an effective post-disaster management system (PDMS) will result in distribution of all emergency resources such as, hospital, storage and transportation much more reasonably and be more beneficial to the individuals in the post disaster period. In this Dissertation, firstly, semi-supervised learning (SSL) based graph systems was constructed for PDMS. A Graph-based PDMS\u27 resource map was converted to a directed graph that presented by adjacent matrix and then the decision information will be conducted from the PDMS by two ways, one is clustering operation, and another is graph-based semi-supervised optimization process. In this study, PDMS was applied for emergency resource distribution in post-disaster (responses phase), a path optimization algorithm based ant colony optimization (ACO) was used for minimizing the cost in post-disaster, simulation results show the effectiveness of the proposed methodology. This analysis was done by comparing it with clustering based algorithms under improvement ACO of tour improvement algorithm (TIA) and Min-Max Ant System (MMAS) and the results also show that the SSL based graph will be more effective for calculating the optimization path in PDMS. This research improved the map by combining the disaster map with the initial GIS based map which located the target area considering the influence of disaster. First, all initial map and disaster map will be under Gaussian transformation while we acquired the histogram of all map pictures. And then all pictures will be under discrete wavelet transform (DWT), a Gaussian fusion algorithm was applied in the DWT pictures. Second, inverse DWT (iDWT) was applied to generate a new map for a post-disaster management system. Finally, simulation works were proposed and the results showed the effectiveness of the proposed method by comparing it to other fusion algorithms, such as mean-mean fusion and max-UD fusion through the evaluation indices including entropy, spatial frequency (SF) and image quality index (IQI). Fuzzy set model were proposed to improve the presentation capacity of nodes in this GIS based PDMS

Gaussian Shaped Fuzzy Similarity Inference For Semantic Cell: An Affective Computing In Valence-Arousal Space

Fuzzy similarity computing under semantic network inference was proposed by using a special formalized semantic cell model. Valence-Arousal affective space under such semantic cell model was regarded as more effectiveness in knowledge presentations particular in IT-THEN rule fuzzy inference system. The fuzzy Implication inference also was addressed to resolve the problem in joint density calculation by Gaussian probability density function and fuzzy Mamndini type implication. The case studies in semantic network using proposed method shows the effectiveness and in difference inputs have been discussed. © 2013 IEEE

Fuzzy Analysis And Simulations For Emergency Hospital Performance In Post-Disaster

In order to establish an effective collaboration between post-disaster management systems (PDMS) and individuals for data sharing, appropriate agreements with a timely response for the need of these individuals must be adopted. Such agreements will increase their willingness to participate in this process. Additionally establishing an appropriate relationship between governments, private and academic sectors will lead to better utilization of their capabilities (e.g. national mapping agencies) and allow PDMS to acquire plenty of data from the disaster response. Fuzzy factors analysis on matrix type dataset is to conduct a subdataset indexing by some indices using fuzzy transformation; the survey dataset in this paper were processed by fuzzy factors analysis, In order to conduct sub-dataset indexing by some indices using fuzzy transformation, it is necessary to use fuzzy factor analyst on matrix type dataset

Improving Map-Based Post-Disaster Management Systems A Guassian Fusion Approach

Providing full and accurate information is crucial to the post-disaster management to enable the affected people access and obtain the resources needed, in a timely manner; but, the current map-based postdisaster management system lack of providing the emergency resource lists without filtering them, as a result the post-disaster management system consumes high levels of time and energy in calculation. An effective post-disaster management system (PDMS) has to ensure distribution of emergency resources, such as hospital, storage and transportation in a reasonable time so that affected papulation are properly benefited from it during the post-disaster period. In the method proposed in this paper, first, initial mapping and disaster mapping was proposed under Gaussian transformation and the maps image acquired as histogram. And then, all the maps, which are under discrete wavelet transform (DWT), were converted as DWT images by applying Gaussian fusion algorithm. Second, inverse DWT (iDWT) is applied to generate a new map for post-disaster management system. Finally, simulations were carried out and the results evaluated in terms of the indices, namely entropy, spatial frequency (SF) and image quality index (IQI). The evaluation results show that the proposed method is more effective than the other fusion algorithms, such as mean-mean fusion and max-UD fusion