Effective algorithm for frequent pattern mining

Aditya, S P; Hemanth, M; Lakshmikanth, C K; Suneetha, K R

doi:10.1109/icecds.2017.8389527

Cited by 2 publications

(2 citation statements)

References 17 publications

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“…For the websites requiring high performance, we use a Bloom Filter [16] to query rapidly and memory-efficiently whether the hash of incoming HTTP request presents in the existing hash patterns. Other matching methods can be found at [17], [18].…”

Section: Attack Preventionmentioning

confidence: 99%

Preventing the attempts of abusing cheap-hosting Web-servers for monetization attacks

Nguyen¹,

Lin²,

Hwang³

2019

Preprint

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Over the past decades, the web is always one of the most popular targets of hackers. Today, along with the popular usage of open sources such as Wordpress and Joomla, the explosion of the vulnerabilities in such frameworks causes the websites using them to face numerous security threats. Unfortunately, many clients and small companies may not be aware of these serious security threats and call a rescuer only when the website is hacked, compromised, or blocked by the search engines. In this paper, we present an effective counter against such threats, including monetization attempts in the less valuable targets such as small websites.

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Section: Attack Preventionmentioning

confidence: 99%

Preventing the attempts of abusing cheap-hosting Web-servers for monetization attacks

Nguyen¹,

Lin²,

Hwang³

2019

Preprint

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“…According to Aditya, S. P et al [8], apriori algorithm uses more memory and time to generate frequent pattern. Improved Apriori Algorithm takes less time to generate frequent patterns.…”

Section: According To S G Langhnoja Et Al [4]mentioning

confidence: 99%

A Systematic Review on Data Preprocessing and Pattern Discovery of Web Usage Mining

Neeru¹,

Nandal²

2018

ijarcs

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To find valuable knowledge from web data is known as web mining. The growth of World Wide Web exceeded all expectations with the development of internet technology. Rapid growth of World Wide Web has affected a lot of both visitors and web site owners. Retrieving different information in different format has become a very difficult task. To solve this problem, one positive approach is web usage mining (WUM).Web mining that extracts patterns from user weblogs is known as web usage mining, that is an implementation part of data mining. The goal of web usage mining is to understand the behaviour of web site users by processing the data mining of web access data. The success of web usage mining depends upon efficient knowledge extracted from large amount of raw log data. Knowledge obtained from web usage mining does the task of finding the hidden important information about user behaviour, and facilitate more effective browsing, to enhance web design, its page surfing pattern and other valuable information which is used for various purposes. In this paper, we provide detailed review of work done for different phases of web usage mining.

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Effective algorithm for frequent pattern mining

Cited by 2 publications

References 17 publications

Preventing the attempts of abusing cheap-hosting Web-servers for monetization attacks

Preventing the attempts of abusing cheap-hosting Web-servers for monetization attacks

A Systematic Review on Data Preprocessing and Pattern Discovery of Web Usage Mining

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