Honeypots have been studied in the network domain for detection and information collection against external threats in the past few years. They lure a potential attacker by simulating resources having vulnerabilities and observing the behavior of a potential attacker to identify him before a damaging attack takes place. A lot of work has been done in the area of privacy and security in databases. Though the number of attacks and complexity for database attacks are increasing day by day, there has been no attempt to design honeypots for privacy enforcing databases. The use of honeypots for databases would help in confirming the suspicion (malafide intention) of a suspicious user without leaking the target information (information which would fulfill the malafide intention) to the attacker. We propose a framework for database honeypots for certain types of attacks in privacy context. The proposed honeypots for databases are termed as context honeypots.
['Shyam K. Gupta', 'Anand Gupta', 'R. S. Damor', 'Vikram Goyal', 'Sangeeta Sabharwal']
Context Honeypot: A Framework for Anticipatory Privacy Violation