Volume 10 | Issue 6 |

 Abstract

There are number of users who purchase products online and make payment through various websites. There are multiple websites who ask user to provide sensitive data such as username, password or credit card details etc. often for malicious reasons. This type of websites is known as phishing website. Phishing attacks are becoming more common and sophisticated, putting Internet users at risk. While these assaults have shown robust to a wide number of countermeasures presented by academia, business, and research groups, machine learning algorithms look to be a viable option for discriminating between phishing and authentic websites. Existing machine learning algorithms for phishing detection have three major drawbacks. The first issue is that there is neither a framework for extracting features and maintaining the dataset up to date, nor an updated collection of phishing and genuine websites. The second point of concern is the vast number of features employed, as well as the absence of supporting evidence for the characteristics used to train the machine learning classifier. The final point of concern is the sort of datasets utilised in the research, which appear to be unwittingly skewed in terms of URL or content-based attributes. The development of our open-source and extendable system to extract features and produce up-to-date phishing dataset is described in this thesis. We integrated 29 distinct characteristics into our framework, dubbed Fresh-Phish, to determine whether a particular website is authentic or phishing. We constructed a dataset of 6,000 websites with these qualities, 3,000 of which were malicious and 3,000 of which were legitimate, and evaluated our technique using 26 features published in previous work and three novel features. We concentrate on this aspect of phishing websites and design features that investigate the domain name's relationship to the website's key elements. Our study varies from the previous state-of-the-art in that our feature set assures that a dataset has low or no bias. On a sample dataset, our learning model achieves a true positive rate of 98 percent and a classification accuracy of 97 percent using only seven features. Our per data instance processing and classification is 4 times quicker for authentic websites and 10 times faster for phishing websites when compared to state-of-the-art work. We also show the drawbacks of utilising URL-based characteristics, since they are likely to be skewed towards dataset acquisition and consumption.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Detection of Phishing Websites using an Efficient Deep Learning Framework

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Slabs are a major component of the structural element for building foundations and there is also a great demand for the use of concrete in most constructions. These are the reasons for the creative development of reinforced concrete concepts that reduce weight and give a longer duration. U boot technology is proposed to obtain large-span slabs or to accommodate heavy loads without beams. This technique is used where the U-boot baton can be placed in slabs with concrete and steel with proper arrangement. U-Boot Baton is a container like formwork structure produced using reused polypropylene, a result of the business for building lightweight wide chunks and pontoon establishments in built up concrete.. One solution is to build a slab with a wide span with more bearing power. The utilization of the U-boot structure assists with diminishing how much concrete and steel expected for laying sections.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

U Boot, Polypropylene, Slab, Weight Reduction, Voided Slab, Concrete.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In order to cure lung cancer early detection of cancer is necessary. Computer aided diagnosis (CAD) technology is used for detection in which CT image is segmented for lung nodules and then after further processing, detection will be done. Machine learning classifiers (KNN, SVM, etc) are used for classification and detection. Noise is induced in the image during acquisition or transmission; there is reduction in performance of detection because it may alter the coefficients which are required for classification. The proposed method is used to filter the image and then subject it to detection, So that performance can be improved compared to detection without filtering.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

specificity, segmentation, feature extraction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Image, Text ,Recognition, correlation,Object

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Empowerment, Women, society, Indian Constitution, judiciary, Women rights.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Extremism has become a subject of serious concern in the Northeast India in the last few decades. Assam, being a part of it, has also been known for extremism for quite some time. In the year 2007, 29 major incidents of violence had taken place in the state which involved the extremist outfits. The history of extremism in Assam can be traced back to the early days of freedom struggle. In the post 1930s a section of youth being dissatisfied with the Congress leadership, preferred to adopt violence and militancy to pacifism. The activities of the extremists during freedom struggle did not seem to affect the life of the common man very much. However, today the activities of the extremist organizations seem to affect the lives of the people in various ways.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Extremism, ULFA

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Marriage is regarded as one of life's most important aspects. And, in a nation like India, it is not just significant but also sacrosanct. In our nation, religious rites and rituals play a significant part in marriage, and because of this religious component, marriage is still seen as a sacred institution. As a result, the notion of sanctity that comes with marriage makes the concept of divorce exceedingly foreign to the religion's mandate. Hindu marriage unites two people for all eternity, allowing them to seek dharma, arth, and karma. It is a union of two people who have been married for a long time and have a sustainable relationship. Marriage in Hinduism is followed by customary consummation rites. Until 1955, divorce was completely unknown in the Hindu marriage. Manu announced that a spouse can't be delivered by her significant other either by deal or by deserting, suggesting that the conjugal tie can't be cut off in any case . According to the traditional belief, a marriage is considered not only as a relationship or a bond that exists for the existing world but it is a bond which also continues beyond. Thus, the essence of staying together was so imbibed in the Hindu society that a divorced person was stigmatized and prejudiced in the existing world. In Hindu communities particularly in the so-called lower social strata, the practice of divorce prevailed as a custom. However, with the changing needs of society, the Hindu Marriage Act was considered and ultimately the divorce aspect also found a place in the Hindu Marriage Act .

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

family, statutory, divorce, customary, hindu, marriage, act,

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

People are careful once they are attempting to shop for a replacement house with their budgets and market ways. the target of the paper is to forecast the coherent house costs for non-house holders supported their money provisions and their aspirations. By analyzing the preceding merchandise, fare ranges and conjointly forewarns developments, speculated costs are calculable. The paper involves predictions mistreatment completely different Regression techniques like Multiple linear, Ridge, LASSO, Elastic web, Gradient boosting and adenosine deaminase Boost Regression. House worth prediction on a data set has been done by mistreatment all the higher than mentioned techniques to seek out out the simplest among them. The motive of this paper is to assist the vendor to estimate the merchandising price of a house perfectly and to assist individuals to predict the precise time slap to accumulate a house. a number of the connected factors that impact the cost were conjointly taken into issues like physical conditions, construct and placement etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, Random Forest ,ANN,XGBoost,Rate Prediction,Python.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The number of injuries, as well as worries regarding driver and passenger safety, is rising on a regular basis. Countries that have effectively reduced road traffic danger have taken a "systems approach" to road safety. The problem of speed lies at the heart of the road safety debate.Speed and the amount of accidents, as well as the severity of the crash's repercussions, are clearly linked. This framework presents a speed limit camera monitoring/tracking system that makes use of the Global Positioning System (GPS) and cloud computing, as well as a Software-as-a-Service (SaaS) module, to deliver useful information about roads in order to improve safety. It also warns the driver about signs, breaks, and prospective connections to other roadways.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

GPS, Software-as-a-Service (SaaS), Cloud computing

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Creative Commons Attribution 4.0 and The Open Definition