By I. S. Amiri, O. A. Akanbi, E. Fazeldehkordi
Phishing is among the so much widely-perpetrated types of cyber assault, used to collect delicate info corresponding to bank card numbers, checking account numbers, and person logins and passwords, in addition to different info entered through an internet site. The authors of A Machine-Learning method of Phishing Detetion and protection have carried out examine to illustrate how a computer studying set of rules can be utilized as a good and effective software in detecting phishing web content and designating them as info protection threats. this technique can end up precious to a wide selection of companies and agencies who're looking recommendations to this long-standing hazard. A Machine-Learning method of Phishing Detetion and safety additionally presents details safeguard researchers with a kick off point for leveraging the computing device set of rules method as an answer to different info defense threats.
Discover novel examine into the makes use of of machine-learning ideas and algorithms to observe and forestall phishing attacks
Help your enterprise or association stay away from expensive harm from phishing sources
Gain perception into machine-learning concepts for dealing with numerous details defense threats
About the Author
O.A. Akanbi got his B. Sc. (Hons, details expertise - software program Engineering) from Kuala Lumpur Metropolitan collage, Malaysia, M. Sc. in info safety from collage Teknologi Malaysia (UTM), and he's shortly a graduate pupil in machine technological know-how at Texas Tech college His sector of study is in CyberSecurity.
E. Fazeldehkordi bought her Associate’s measure in desktop from the college of technology and know-how, Tehran, Iran, B. Sc (Electrical Engineering-Electronics) from Azad collage of Tafresh, Iran, and M. Sc. in info safety from Universiti Teknologi Malaysia (UTM). She at the moment conducts learn in info defense and has lately released her learn on cellular advert Hoc community safety utilizing CreateSpace.
Read or Download A Machine-Learning Approach to Phishing Detection and Defense PDF
Similar network security books
What you are going to research from this book
Develop TCP/IP networking client/server applications
Administer neighborhood machines' IPv4/IPv6 community interfaces
Write multi-purpose effective internet consumers for HTTP and HTTPS protocols
Create e mail consumers to paintings with universal e mail protocols equivalent to SMTP, POP3, IMAP, and so on.
Scrape web content and look for important information
Perform distant process management projects over Telnet and SSH connections
Interact with renowned web content through internet prone resembling XML-RPC, cleaning soap, and leisure APIs
Monitor and research significant universal community safeguard vulnerabilities
Python is a superb language to take advantage of to put in writing code and feature enjoyable via prototyping functions quick. The presence of plenty of third-party libraries, often referred to as batteries, makes it much more more straightforward and speedier to prototype an software or to enforce a brand new set of rules. while you are attracted to growing the development blocks for plenty of useful net and networking functions that depend upon networking protocols then this publication is a must-have.
This publication highlights significant facets of community programming in Python ranging from writing uncomplicated networking consumers, to constructing advanced screen-scraping and community safety tracking scripts. It creates the construction blocks for plenty of useful net and networking purposes that depend upon numerous networking protocols. This ebook provides the ability and sweetness of Python in fixing the varied real-world projects within the quarter of community programming, method and community management, community tracking, and web-application development.
This publication develops your skill to resolve a variety of community programming initiatives in Python. we'll begin by way of exploring the Python typical library features to create client/server community and control your neighborhood networking assets to be had lower than either IPv4 and IPv6. the sensible concentration keeps with growing net and e mail consumers, scraping web content, fetching details from quite a few web pages, and looking out for info on the net resembling Amazon, Flickr, and different websites. It additional develops your talents to research your community safety vulnerabilities utilizing complicated community packet seize and research techniques.
An easy-to-follow consultant filled with hands-on examples on real-world networking projects. It covers the complex issues of community programming in Python utilizing a suite of chosen recipes.
For: when you are a community programmer, system/network administrator, or an internet program developer, this ebook is perfect for you. you'll have a uncomplicated familiarity with the Python programming language and TCP/IP networking recommendations. even though while you are a beginner, you'll strengthen an knowing of the options as you move with this ebook. This booklet will function a supplementary fabric for constructing hands-on abilities in any educational direction on community programming.
http://www. packtpub. com/python-network-programming-cookbook/book
Computational Intelligence innovations were broadly explored in a number of domain names together with forensics. research in forensic encompasses the examine of development research that solution the query of curiosity in defense, clinical, criminal, genetic reviews and and so on. even if, forensic research is mostly played via experiments in lab that is pricey either in expense and time.
This ebook constitutes the completely refereed court cases of the eighth foreign convention on details Theoretic safeguard, ICITS 2015, held in Lugano, Switzerland, in might 2015. The 17 complete papers provided during this quantity have been rigorously reviewed and chosen from fifty seven submissions. The papers hide quite a few themes on the intersection of cryptography, info conception, and quantum physics.
This paintings presents guidance for the sensible implementation of safety structure in a specific company cloud. The authors are mathematicians and experts in facts modeling and defense. event of medical collaboration with encouraged the authors to try to conceptualize the typical tactics and techniques in cloud defense, so that it will make protection procedure deployment as basic and obvious as attainable.
- sendmail, 4th Edition
- Security for Wireless Sensor Networks (Advances in Information Security)
- Personal Firewalls for Administrators and Remote Users
- IP Addressing and Subnetting, Including IPv6, 1st Edition
Extra info for A Machine-Learning Approach to Phishing Detection and Defense
The drawback of GoldPhish is the time it takes in the rendering of a webpage. , 2010). 3 Visual Similarity-Based Approach Chen et al. (2009) used screenshot of web pages to identify phishing sites. They used Contrast Context Histogram (CCH) to describe the images of web pages and k-mean algorithm to cluster nearest key points. Lastly, euclidean distance between two descriptors is used to obtain similarity between two sites. 1% false positive. Chen et al. (2009) claimed that screenshot analysis lack efficiency in proper detection of online phishing.
They used Contrast Context Histogram (CCH) to describe the images of web pages and k-mean algorithm to cluster nearest key points. Lastly, euclidean distance between two descriptors is used to obtain similarity between two sites. 1% false positive. Chen et al. (2009) claimed that screenshot analysis lack efficiency in proper detection of online phishing. Fu et al. (2006) utilized Earth Mover’s Distance (EMD) to associate low-resolution screen capture of a web page. Images of web pages are denoted through the aid of image pixel color (alpha, red, green, and blue) and the centroid of its position distribution in the image.
However, blacklists are to contain older fake websites rather than newer ones, which give impostors a better chance of successive attack before being blacklisted. Furthermore, Liu et al. (2006) claimed that 5% of spoof site recipients become victims in spite of the availability of a profusion of web browser integrated lookup systems. , 2006). Several classifier systems have been created over the years to combat phishing. , 2004). Netcraft classifier depends on domain0registration information such as the host name, domain name, host country, and6registration date (Li and Helenius, 2007).