Abstract: Systems and methods for filtering fraudulent email messages are described. In one embodiment, a method includes receiving an email message, determining whether the email message is indicative of fraud, and creating a fraud filter based on the email message if the email message is fraudulent.

Abstract: Systems and methods for filtering spam messages utilizing a URL filtering module are described. In one embodiment, the method includes detecting, in an incoming message, data indicative of a URL and comparing the URL from the incoming message with URLs characterizing spam. The method further includes determining whether the incoming message is spam based on the comparison of the URL from the incoming message with the URLs characterizing spam.

Abstract: A method and system for creating bulk filters are described. In one embodiment, the method includes receiving probe email messages indicative of spam, grouping similar probe email messages, and creating a bulk filter for each group having at least a predefined number of probe email messages without human interaction. The method further includes distributing the resulting bulk filters to clients for detection of bulk email messages at the clients.

Abstract: A method and system to maintain lists of IP addresses for detection of email spam are described. In one embodiment, the method includes receiving email messages from senders associated with Internet Protocol (IP) addresses, filtering the email messages to identify spam, and sending statistics pertaining to the email messages and the identified spam to a server. The method further includes receiving, from the server, IP address lists generated based on the statistics, and filtering new email messages using the IP address lists. The IP address lists received from the server may include a list of safe IP addresses, a list of suspect IP addresses and a list of open proxy IP addresses.

Abstract: Systems and methods for filtering spam messages utilizing a URL filtering module are described. In one embodiment, the method includes detecting, in an incoming message, data indicative of a URL and comparing the URL from the incoming message with URLs characterizing spam. The method further includes determining whether the incoming message is spam based on the comparison of the URL from the incoming message with the URLs characterizing spam.

Abstract: Systems and methods are provided for facilitating the discovery of items, individuals, locations and business services that are relevant to the context of an individual (including, e.g., who an individual is, what an individual is looking for, where an individual is, the current time and/or date), facilitating post-discovery notifications (such as notifying the user or users), and executing post-discovery actions (such as making an offer to buy a product or prompting to add the user to an individual's personal network). Accordingly, in implementations of the present invention, agents are configured by the individual and deployed to or by the individual's computerized device (e.g., a mobile device, desktop computer, laptop computer, Internet appliance and/or server).

Abstract: A method and system to maintain lists of IP addresses for detection of email spam are described. In one embodiment, the method includes receiving email messages from senders associated with Internet Protocol (IP) addresses, filtering the email messages to identify spam, and sending statistics pertaining to the email messages and the identified spam to a server. The method further includes receiving, from the server, IP address lists generated based on the statistics, and filtering new email messages using the IP address lists. The IP address lists received from the server may include a list of safe IP addresses, a list of suspect IP addresses and a list of open proxy IP addresses.