A system and method are provided for identifying inappropriate content in websites on a network. Unrecognized uniform resource locators (URLs) or other web content are accessed by workstations and are identified as possibly having malicious content. The URLs or web content may be preprocessed within a gateway server module or some other software module to collect additional information related to the URLs. The URLs may be scanned for known attack signatures, and if any are found, they may be tagged as candidate URLs in need of further analysis by a classification module.

System and method of analyzing web content

Spam filters often use the reputation of an IP address (or IP address range) to classify email senders. This approach worked well when most spam originated from senders with fixed IP addresses, but spam today is also sent from IP addresses for which blacklist maintainers have outdated or inaccurate information (or no information at all). Spam campaigns also involve many senders, reducing the amount of spam any particular IP address sends to a single domain; this method allows spammers to stay "under the radar". The dynamism of any particular IP address begs for blacklisting techniques that automatically adapt as the senders of spam change.This paper presents SpamTracker, a spam filtering system that uses a new technique called behavioral blacklisting to classify email senders based on their sending behavior rather than their identity. Spammers cannot evade SpamTracker merely by using "fresh" IP addresses because blacklisting decisions are based on sending patterns, which tend to remain more invariant. SpamTracker uses fast clustering algorithms that react quickly to changes in sending patterns. We evaluate SpamTracker's ability to classify spammers using email logs for over 115 email domains; we find that SpamTracker can correctly classify many spammers missed by current filtering techniques. Although our current datasets prevent us from confirming SpamTracker's ability to completely distinguish spammers from legitimate senders, our evaluation shows that SpamTracker can identify a significant fraction of spammers that current IP-based blacklists miss. SpamTracker's ability to identify spammers before existing blacklists suggests that it can be used in conjunction with existing techniques (e.g., as an input to greylisting). SpamTracker is inherently distributed and can be easily replicated; incorporating it into existing email filtering infrastructures requires only small modifications to mail server configurations.

/pdf/filtering-spam-with-behavioral-blacklisting-4q37e5g43y.pdf

Filtering spam with behavioral blacklisting

An individual's social network is used to authorize information flow to the individual and to authenticate the individual for access to certain information or services. Information flow to the individual is authorized if the source of the information is a member of the individual's social network who is connected to the individual along a path that does not traverse through anyone on a gray list of the individual. The black list identifies those members who previously sent unwanted communication to the individual or posted content that was deemed offensive by the individual. The gray list identifies those members who are one degree separated from any black list member. The individual is authenticated for access to certain information or services if a member of the individual's social network already has access and this member is connected to the individual along a path that does not traverse through anyone on a gray list of the individual, or if members of the individual's social network who are connected to the individual along a path that does not traverse through anyone on a gray list of the individual have an average authentication rating that is at least a minimum value.

Authorization and authentication based on an individual's social network

Various embodiments of the invention provide methods, systems and software for analyzing data. In particular embodiments, for example, a set of data about a web site may be analyzed to determine whether the web site is likely to be illegitimate (e.g., to be involved in a fraudulent scheme, such as a phishing scheme, the sale of gray market goods, etc.). In an exemplary embodiment, a set of data may be divided into a plurality of components (each of which, in some cases, may be considered a separate data set). Merely by way of example, a set of data may comprise data gathered from a plurality of data sources, and/or each component may comprise data gathered from one of the plurality of data sources. As another example, a set of data may comprise a document with a plurality of sections, and each component may comprise one of the plurality of sections. Those skilled in the art will appreciate that the analysis of a particular component may comprise certain tests and/or evaluations, and that the analysis of another component may comprise different tests and/or evaluations. In other cases, the analysis of each component may comprise similar tests and/or evaluations. The variety of tests and/or evaluations generally will be implementation specific.

Methods and systems for analyzing data related to possible online fraud

Methods and systems are provided for allocating network resources of a distributed virtual system to support managed, network-based services. According to one embodiment, a VR-based switch having multiple processing elements is configured for operation at an Internet POP. An NOS is provided on each of the processing elements. Resources of the VR-based switch are segmented between a first and second subscriber by mapping VRs assigned to the first and second subscriber onto appropriate processing elements. Then, a first and second set of customized services are configured, each including two or more of firewalling, virtual private networking, encryption, traffic shaping, routing and network address translation (NAT), to be provided by the VR-based switch. Customized services are configured by allocating appropriate service object groups to the VRs, which can be dynamically distributed by the NOS to customized processors of the processing elements to achieve desired computational support.

Distributed virtual system to support managed, network-based services

DomainKeys Identified Mail (DKIM) defines a domain-level
authentication framework for email using public-key cryptography and
key server technology to permit verification of the source and
contents of messages by either Mail Transfer Agents (MTAs) or Mail
User Agents (MUAs). The ultimate goal of this framework is to permit a
signing domain to assert responsibility for a message, thus proving
and protecting message sender identity and the integrity of the
messages they convey while retaining the functionality of Internet
email as it is known today. Proof and protection of email identity,
including repudiation and non-repudiation, may assist in the global
control of "spam" and "phishing".

DomainKeys Identified Mail (DKIM) Signatures

The invention is directed to a system and method for determining if a “spam” message is originating from a messaging account by challenging a particular client's outbound email usage with a test that requires verification of content that is easily understood by a human being, not an automated computer program such as those used by “spammers.” If a limit on the number of recipients for outbound messages has been exceeded, a test is presented the next time a client attempts to send a message. The client must successfully answer the test within a relatively short period of time or else the ability to send messages will be disabled. Once disabled, the client can reinstate the ability to send messages by contacting a representative of the message system out of band, e.g., a telephone call to confirm legitimate outbound email use.

Method and system for image verification to prevent messaging abuse

A phishing detection agent is provided. In one embodiment, a user's browser includes a plug-in application or agent that may capture a visual record of a webpage and, with a cached copy of known, authentic websites provided to it via periodic updates, perform a series of image comparison functions to determine if the suspected website is attempting to deceive the user. The phishing detection agent is capable of performing an image recognition algorithm, such as logo recognition algorithm, optical character recognition, an image similarity algorithm, or combination of two or more of the above. If the suspected webpage corresponds to one of the authentic web pages, but the domain name of the suspected web page does not match the domain name of one of the authentic web pages, the suspected web page is flagged as a phishing web site.

Anti-phishing agent

A method and system directed to the communication of the trust characteristics of electronic messages using visual and audio postmarks. The postmarks may represent a particular trust level on a continuum that can range from suspicious to trusted. A message system may determine the baseline trust level of a message and assign a postmark to the message. The postmark can communicate the trust level of the message to a user without requiring the message to be opened or read. In one embodiment of the invention the user can create rules and filters to classify messages by trust level.

Associating a postmark with a message to indicate trust

The invention relates to determining electronic text communication distributed in bulk is likely solicited. In one step, a first electronic and a second electronic submission are received. It is determined that the first electronic submission is likely solicited. A first portion is extracted from the first electronic submission and a second portion from the second electronic submission. The content of the first electronic submission influences extraction of the first portion, and the content of the second electronic submission influences extraction of the second portion. A first code is determined for the first portion and a second code is determined for the second portion, where the first code is indicative of the first portion and the second code is indicative of the second portion. The first code is compared to the second code. It is determined that the second electronic submission is likely solicited, at least in part, in response to comparing the first code to the second code.

Automated solicited message detection

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