Abstract: Techniques are described for determining reorder commands for updating policy rules in a managed network device based on a longest common subsequence between two lists of policy rules. For example, as described herein, a network management device determines a longest common subsequence of a source list comprising a plurality of policy rules in a first ordering that corresponds to a current policy configuration of a managed network device and of a destination list comprising the plurality of policy rules in a second ordering that corresponds to an updated ordering for the policy configuration. The network management device then iterates through the destination list to generate commands that, when executed by the managed network device, move policy rules in the destination list that are not members of the longest common subsequence to positions in the policy configuration relative to policy rules that are members of the longest common subsequence.

Abstract: Systems and methods are disclosed to detect fraud by displaying on a buyer's computer a high value item next to one or more commonly purchased items to attract a fraudster; analyzing customer purchasing behavior on the high value item for an indication of fraud; and indicating fraud if the buyer buys the high value item without prior history.

Abstract: Systems and methods are disclosed to detect fraud by displaying on a buyer's computer a high value item next to one or more commonly purchased items to attract a fraudster; analyzing customer purchasing behavior on the high value item for an indication of fraud; and indicating fraud if the buyer buys the high value item without prior history.

Abstract: Systems and methods are disclosed to detect fraud by displaying on a buyer's computer a high value item next to one or more commonly purchased items to attract a fraudster; analyzing customer purchasing behavior on the high value item for an indication of fraud; and indicating fraud if the buyer buys the high value item without prior history.

Abstract: Systems and methods are disclosed to detect fraud by analyzing customer purchasing behavior for a high value item intentionally placed next to commonly purchased items, payment information for an address verification system (AVS), customer behavioral information, password sharing between two accounts, unique identification for a hardware component of a client computer used to purchase items on line, administrative information associated with a customer account; and Internet Protocol (IP) address.

Abstract: Systems and methods are disclosed to detect fraud by analyzing customer purchasing behavior for a high value item intentionally placed next to commonly purchased items, payment information for an address verification system (AVS), customer behavioral information, password sharing between two accounts, unique identification for a hardware component of a client computer used to purchase items on line, administrative information associated with a customer account; and Internet Protocol (IP) address.