‘E-SPY’: DETECTION AND PREDICTION OF WEBSITE ATTACKS

Abstract

While making the world smaller, internet is
experiencing an increase in cyber crimes like hacking, identity
and data theft and people fall prey to malicious attacks because
of lack of knowledge. SQLIA enables unauthorized users to make
use of loopholes within any system to gain access to its databases
and phish data, using tautologies, piggybacking, and union.
These intrusions can be handled by an IDS which involves
monitoring and analyzing: user activities, system activities,
configurations and vulnerabilities, abnormal activity patterns,
user policy violations, etc. IDS transforms the captured packets
to a predefined data structure. Our proposed system's slow
detection link combats the drawback of using a Snort plug-in
which obtains only the port information of the source IP-address.
An IDS can be integrated with a honeypot which allows the user
to attack to learn the pattern of various attacks and prevent such
attacks on the main system.