|dc.contributor.author||Ourahman, Mohammad Rashid||
|dc.description.abstract||Maintaining Cyber Security has been one of the biggest challenges of a modern era
which has seen the extensive emergence of internet advertisers, and in which some
promote their malicious contents through rogue websites.
Internet rogue advertisers penetrate through cybercrime in various forms of
advertisement banners which are displayed within any parts of a website. Tracking these
rogue advertisers is important to the Cyber Security cause, where in an ideal scenario
individuals are exposed to correct information as is their basic right, along with their
reaction toward the sensitivity of any content.
In the past manual tracking has been the commonest method of checking but in some
cases manual tracking could fail, other than time parameters the accuracy is also
questionable, the solution to this the concept of Automatic URL Tracking.
This thesis represents an analytical method of Automatic URL Tracking, according to
this approach, where various pages are checked for advertising banners, these are
clicked until the final URL or its destination is reached.
To achieve various concrete results a significant work has been done to develop an
Automatic URL Tracking Software which is run when connected through internet while
holding the reported URLs databases where each of these are tracked to its final
The Automatic URL Tracking Software was run for the total of 2500 URL samples, upon
manually tracking these URLs the two processes showed 87.7 % agreement which can be
reliable result considering the presence of various blocking techniques adopted by
hosting sites and site developers but there are chances for further development where
the application is enhanced specifically to overcome these obstacles.
Automatic URL Tracking overcomes the difficulties and challenges of manual tracking,
allowing larger data volumes to be tested, identified and verified, but having said that it
also comes with the challenges of rapidly changing internet technologies, in which more
comprehensive strategies need to be built to overcome this challenge.||en_US
|dc.subject||Uniform Resource Identifiers||en_US
|dc.title||AutoURL : automatic URL tracking to identify rogue advertising : this thesis is submitted in fulfillment of the requirements for the degree of Master of Information Sciences in Software Engineering, School of Engineering and Advanced Technology (S.E.A.T.) at Massey University, Albany, New Zealand||en_US
|thesis.degree.name||Master of Information Sciences (M.Inf.Sc.)||en_US