A Machine-Learning Approach to Phishing Detection and by I. S. Amiri, O. A. Akanbi, E. Fazeldehkordi PDF

By I. S. Amiri, O. A. Akanbi, E. Fazeldehkordi

ISBN-10: 0128029277

ISBN-13: 9780128029275

Phishing is likely one of the so much widely-perpetrated different types of cyber assault, used to collect delicate info comparable to bank card numbers, checking account numbers, and consumer logins and passwords, in addition to different info entered through a website. The authors of A Machine-Learning method of Phishing Detetion and safety have performed examine to illustrate how a computing device studying set of rules can be utilized as an efficient and effective device in detecting phishing web content and designating them as details defense threats. this technique can turn out important to a large choice of companies and agencies who're looking recommendations to this long-standing possibility. A Machine-Learning method of Phishing Detetion and safeguard additionally presents info defense researchers with a place to begin for leveraging the computing device set of rules method as an answer to different details protection threats.

Discover novel study into the makes use of of machine-learning rules and algorithms to notice and forestall phishing attacks
Help your corporation or association stay away from high priced harm from phishing sources
Gain perception into machine-learning suggestions for dealing with numerous details defense threats
About the Author

O.A. Akanbi obtained his B. Sc. (Hons, info know-how - software program Engineering) from Kuala Lumpur Metropolitan collage, Malaysia, M. Sc. in details safety from college Teknologi Malaysia (UTM), and he's shortly a graduate pupil in computing device technological know-how at Texas Tech collage His region of analysis is in CyberSecurity.

E. Fazeldehkordi acquired her Associate’s measure in desktop from the collage of technology and know-how, Tehran, Iran, B. Sc (Electrical Engineering-Electronics) from Azad college of Tafresh, Iran, and M. Sc. in details safeguard from Universiti Teknologi Malaysia (UTM). She presently conducts study in info safety and has lately released her examine on cellular advert Hoc community protection utilizing CreateSpace.

Show description

Read or Download A Machine-Learning Approach to Phishing Detection and Defense PDF

Similar network security books

Download PDF by Johnny Long, Timothy Mullen, Ryan Russell: Stealing the Network: How to Own a Shadow

The best-selling Stealing the community sequence reaches its climactic end as legislation enforcement and arranged crime shape a high-tech net in an try to carry down the shadowy hacker-villain referred to as Knuth within the such a lot technically subtle Stealing ebook but. Stealing the community: easy methods to personal a Shadow is the ultimate publication in Syngress' floor breaking, best-selling, Stealing the community sequence.

Get Biometrics PDF

Because the IT Director of a producing corporation, i have to comprehend the results and makes use of of Biometrics. This ebook basically explains what Biometrics is, in an esay to appreciate layout with no it over simplifying the topic. i might (and have) suggest this ebook to a person.

New PDF release: Cybercrime Risks and Responses: Eastern and Western

This publication examines the newest and contentious matters when it comes to cybercrime dealing with the area at the present time, and the way top to deal with them. The members convey how jap and Western countries are responding to the demanding situations of cybercrime, and the newest developments and concerns in cybercrime prevention and regulate.

Download e-book for iPad: Handbook of research on security considerations in cloud by Kashif Munir

Cloud computing has fast develop into the following tremendous step in safeguard improvement for firms and associations around the world. With the know-how altering so speedily, it's important that companies rigorously give some thought to the on hand developments and possibilities sooner than imposing cloud computing of their companies.

Extra info for A Machine-Learning Approach to Phishing Detection and Defense

Sample text

Y! (Pc)y(Pe)x. 3) δk is always positive. Thus when x and y δ Pc are given, as Pc increases k increases continuously from zero to unity. This demonstrates that the success of the majority voting scheme (like most decision combination schemes) directly depends on the reliability of the decision confidences delivered by the participating experts. It is also clear that as the confidences of the delivered decisions increase, the quality of the combined decision increases. Since (x − y − 1 ≥ 0), Recently, it has been demonstrated that although majority vote is by far the simplest of the variety of strategies used to combine multiple experts, if properly applied it can also be very effective.

Artificial neural network (ANN) consists of a collection of processing elements that are highly interconnected and transform a set of inputs to a set of desired outputs. The result of the transformation is determined by the characteristics of the elements and the weights associated with the interconnections among them. Since neural network gains experience over a period as it is being trained on the data related to the problem, the major disadvantage is in the time it takes for parameter selection and network learning.

The major disadvantage of this classifier is that the accuracy falls with increase in the size of the training set. In addition, previous researches have shown that KNN can achieve very accurate results, that are sometimes more accurate than those of the symbolic classifiers. It was shown in a study carried out by Kim and Huh, 2011 that KNN classifier achieved the best result compared to other classifier such as linear discriminate analysis (LDA), naıve Bayesian (NB), and support vector machine (SVM).

Download PDF sample

A Machine-Learning Approach to Phishing Detection and Defense by I. S. Amiri, O. A. Akanbi, E. Fazeldehkordi

by Thomas

Rated 4.54 of 5 – based on 21 votes