[PDF] Top 20 Machine Learning Approach for Detection of Malicious Urls and Spam in Social Network
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Machine Learning Approach for Detection of Malicious Urls and Spam in Social Network
... detect malicious websites by verifying lexical features and host based features of ...in malicious URLs and their features over time can simply be ...efficient detection of malicious ... See full document
5
Review: Efficient Spam Detection on Social Network
... email spam detection and filtering mechan-isms have been widely ...of machine learning approaches [3,4] are implemented for content parsing according to the keywords and patterns that are ... See full document
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Machine Learning Approach For Spam Tweets Detection
... In 2010, although there are few works such as, which uses content and account features such as account age, number of followers and followings, URL ratio and length of tweets to distinguish spammers and non-spammers, ... See full document
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An Approach for Malicious Spam Detection in Email with Comparison of Different Classifiers
... with malicious attachments and Uniform Resource Locators ...Targeted Malicious Email ...popular learning algorithms that have been applied to spam detection include Naïve Bayes [23], ... See full document
5
Supervised machine learning approach for detection of malicious executables
... unseen malicious code. This method has improved the detection accuracy of Portable Executable (PE) based malware on Windows ...of learning machine to construct the ... See full document
25
An Efficient Classifier for Spam Detection in Social Network
... This approach is included in the machine learning, working of this algorithm based on Baye’s theorem. Simply, Naives Bayes believes on the presences of a specific attribute in one class that depends ... See full document
6
Twitter Spam Detection Using Machine Learning Algorithms
... Online social networking sites like Twitter, Facebook, Instagram and some online social networking companies have become extremely popular in recent years ...for spam growth [2]. Twitter spam, ... See full document
10
Protecting Social Network Users from Spam Messages Using Machine Learning Algorithm
... rule-based approach for specifying access control policies on the resources owned by network participants, and where authorized users are denoted in terms of the type, depth, and trust level of ... See full document
5
Twitter Spam Detection by Using Machine Learning Frameworks
... “Social spam guard: A data mining based spam detection system for social media networks” in this paper ,Automatically harvesting spam activities in social network ... See full document
6
An Online Malicious Spam Email Detection System Using Resource Allocating Network with Locality Sensitive Hashing
... the malicious spam emails so that general users can be protected from being re-directed to malicious ...detecting malicious spam emails. In general, it is not easy to collect ... See full document
16
Malicious URL Detection and Identification
... a malicious or ...the malicious URL. An alternative approach has been proposed which uses a Naïve Bayes classifier for an automated classification and detection of malicious ... See full document
7
Efficient Spam Detection on Social Network
... reconstructing spam messages into campaigns rather than examining them indivi-dually (with precision value over ...a machine learning process for classifying users as either spammers or ... See full document
10
A Performance Evaluation of Lfun Algorithm on the Detection of Drifted Spam Tweets
... Online social networking is very vast growing growth today’s world but attacks on it is more common, amongst them one of the attack is twitter attack in this Spammers spread various malicious tweets which ... See full document
6
Machine Learning For Prediction Of Malicious Or SPAM Users On Social Networks
... the spam users very correctly but at the same time if SVM result is calculated for the false positive metrics is quite ...recognizing spam and non spam with more appropriate ... See full document
7
Website Reputation System
... timely detection of paramount importance. Over the recent times Machine learning has emerged as a prominent solution for solving Info Sec problems ,few of the use cases seen over the recent ones ... See full document
6
Email Phishing: An Enhanced Classification Model to Detect Malicious URLs
... Phishing URLs are challenging threat in cyber space which steal the user’s sensitive ...phishing URLs crafting tactics pointing to the same phishing website to bypass the detection ...Enhanced ... See full document
12
Machine Learning Approach for Classifying Malicious URLs
... and malicious activity of program by monitoring HTTP visitors is fitting more difficult when sophisticated malware generate authorized HTTP traffic and having the identical habits with ordinary ...in ... See full document
8
Malicious Domain Detection Based on Machine Learning
... in malicious domain detection, we proposed that traditional detection methods such as content analysis and based on matching or manual determination are low efficiency, and have a high false negative ... See full document
11
A Survey Paper on FRAPPE – Facebook Rigorous Application Evaluator
... many malicious Facebook applications ...is malicious or not? Our key contribution is in developing FRAppE—Facebook’s Rigorous Application Evaluator-the first tool focused on detecting malicious apps ... See full document
5
Detection of Malicious Application on Online Social Network
... A Social networking webpage could be a web site wherever each consumer includes a profile and might keep in reality with companions, share their upgrades, meet new people World Health Organization have identical ... See full document
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