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Many classification algorithms have been successfully deployed in security-sensitive applications including spam filters and intrusion detection systems. Under such adversarial environments, adversaries can generate exploratory attacks against the defender such as evasion and reverse engineering. In this paper, we discuss why reverse engineering attacks can be carried out quite efficiently against fixed classifiers, and investigate the use of randomization as a suitable strategy for mitigatingdoi:10.1145/2661829.2662047 dblp:conf/cikm/AlabdulmohsinGZ14 fatcat:qpqg6oddvrdh5hxdrvjl66c67m