Abstract:
Automated fraud and criminal detection systems assist data mining. Banks, finance businesses, large corporations, insurance agencies, clubs, and others are mining customer data to avoid disruption. Many organizations identify intruders by appearance or sensitive qualities like gender, race, or religion. This will not identify the intruder.
Using sensitive features to identify intruders will discriminate against them and not help find the right one. Using sensitive attributes to identify intruders is improper. Our technology will identify possible intruders by their objective misconduct, not by gender, color, or religion. Based on legal facts in the database, intruders will be detected, not sensitive attributes.
Legal data contains intruder crime history. If it detects an intruder, system will mine database data. These data will be matched to the suspect’s behavior. The system will flag the person as a criminal or intruder if these details match. Thus, genuine classification rules can be retrieved but sensitive attribute discriminating rules cannot.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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