Patent Publication Number: US-6910077-B2

Title: System and method for identifying cloaked web servers

Description:
The present invention relates generally to a system and method for detecting cloaked web servers, and more particularly to identifying web servers that provide a first object to a client and a second object to a search engine (i.e., web crawler) in response to an identical request from each. 
     BACKGROUND OF THE INVENTION 
     Cloaking is the process by which a web server delivers a first version of an object, such as a web page or HTML document, to a user and a second version of the object to a search engine (or more specifically, a web crawler affiliated with the search engine) in response to essentially identical requests. A web crawler is a process that accesses a plurality of web servers to index the contents of the web servers. More specifically, the web crawler downloads objects from the web servers and stores the objects and their corresponding URLs (i.e., the network addresses of the objects) in a database. A search engine affiliated with the web crawler subsequently accesses the database to select zero or more objects that correspond to a search request received from a client (i.e., a user operating a personal computer). 
     Web servers are able to identify the program (i.e., a web crawler/search engine or a user&#39;s web browser) that emitted a request (e.g., an HTTP request) for a particular object by reference to content of the request. Table 1 illustrates the contents of a typical HTTP request: 
     
       
         
           
               
               
             
               
                   
                 TABLE 1 
               
               
                   
                   
               
             
            
               
                   
                 GET /index.html HTTP/1.0 
               
               
                   
                 HOST: www.domain_name.com 
               
               
                   
                 USER_AGENT: Mozilla/4.71 
               
               
                   
                 REFERER: http://search_engine.com 
               
               
                   
                   
               
            
           
         
       
     
     The first line of Table 1 identifies the object sought and the location of the object on a corresponding web server. In this example, the object is an HTML document entitled “index.html” and is located in the root directory. Additionally, the first line includes a protocol identifier. In this example, the protocol is version 1.0 of HTTP, which is used to request and transmit files, especially web pages and web page components, over the Internet or other computer network. 
     The second line of Table 1 identifies the hostname, which can be translated into an Internet address, of a web server. In this example, the hostname is “www.domain_name.com”. The URL corresponding to the object of this request is, therefore, “http://www.domain_name.com/index.html”. 
     The third line of Table 1 is the USER_AGENT field, which identifies the program that emitted the request. In this example, “Mozilla/4.71” and the remaining text identifies the program as a Netscape® web browser. Note that web browsers are typically associated with users, not search engines. 
     The fourth line of Table 1 identifies the hostname of the entity that referred the requester to the identified web server. In this example, the referrer is a fictional search engine. 
     With respect to the present invention, line three of Table 1 is the most important. This line can indicate whether the request was sent by a web browser or a web crawler/search engine. More specifically, most web browsers set the USER_AGENT field to a string that is easily recognizable by a web server as corresponding to a web browser, and thus not a search engine/web crawler. Additionally, most web crawlers/search engines have well known names, which are typically included in the USER_AGENT field. For example, a web crawler associated with the search engine Alta Vista® is named “Scooter.” A request for an object from this web crawler would, therefore, typically include the string “Scooter” in the USER_AGENT field. This field can, however, be arbitrarily set before being sent by a web browser or a web crawler/search engine to a web server. The USER_AGENT field does not provide, therefore, a foolproof means for identifying the program that emitted the request. 
     However, an IP-address typically included with a request can also be used to identify the program that emitted the request. Persons skilled in the art recognize that HTTP is a protocol that operates in conjunction with but on a higher level than TCP/IP, which is a packet based protocol, and that an IP-address is a 32-bit number that identifies each sender or receiver of TCP/IP packets. HTTP requests are included in TCP/IP packets, so HTTP requests are accompanied by the IP-address of the requestor. 
     Importantly, web server operators who engage in cloaking typically have lists of IP-addresses associated with web crawlers/search engines. So when, for example, an HTTP request is received by a web server, the IP-address is checked to determine whether the requester is, or is associated with, a web crawler/search engine. The IP-address of the requestor is thus another means for identifying the program that emitted the request. 
     Proponents of web cloaking claim a number of benefits from cloaking—including code (i.e., the design of a given object) and copyright protection. The importance of protecting code stems largely from financial gain made possible by a large number of referrals induced by the code. 
     Whether a search engine refers a given web server to a user (i.e., returns a URL corresponding to the given web server in response to a query from a user) depends upon the relevance of objects available from the web server to a given query. Relevance is, in turn, determined in part by, for example, an analysis of keyword combinations, keyword density, or keyword positioning found in a given object. If a search engine determines that an object is highly relevant to a particular keyword or set of keywords submitted with a query, the object may become desirable to other web server operators, which may copy or emulate the object. In particular, a duplicate of the object can be placed on another web server, which has the effect of devaluing the original object, or the object&#39;s keyword combinations, keyword density, and/or keyword positioning can be emulated to achieve the same level of relevance for another object. The comparative relevance of a given object can be determined by conducting searches designed to result in a referral of the object. 
     There is, however, a darker side to cloaking. Some web server operators seek to deceive search engines, and thus users, in order to increase the number of referrals to their web server. For example, an operator could supply an object that is highly relevant to common searches to search engines, but supply an unrelated page to a user in response to object queries. This action compromises search engine integrity and wastes user time. 
     There is needed in the art, therefore, a system and method for identifying cloaked web servers. 
     SUMMARY OF THE INVENTION 
     In summary, a method of the present invention includes a search engine receiving from a client a representation of a first object that was returned by a web server to the client in response to a request from the client. The search engine receives from the web server a second object in response to an identical request from the search engine, and then compares the representation of the first object to a representation of the second object. The web server is determined to be a cloaked web server if the representation of the first object does not match (i.e., exactly match or, preferably substantially match) the representation of the second object. The representations of the first object and the second object are preferably feature vectors. In some embodiments, the feature vector of the first object is said to match the feature vector of the second object if at least a predetermined number of features in the two feature vectors are the same. 
     In one embodiment, the client receives a URL embedded in a response to a search request submitted to the search engine. A toolbar operating in conjunction with the web browser on the client processes the URL. The processing includes directing the web browser to obtain an object corresponding to the URL from a web server addressed by the URL, converting the object to a feature vector, and delivering the feature vector and the URL back to the search engine. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Additional objects and features of the invention will be more readily apparent from the following detailed description and appended claims when taken in conjunction with the drawings, in which: 
         FIG. 1  illustrates a system including a network, clients, web servers, and a search engine in accordance with a preferred embodiment of the present invention. 
         FIG. 2  is a block diagram of a search engine consistent with a preferred embodiment of the present invention. 
         FIG. 3  is a block diagram of a client consistent with a preferred embodiment of the present invention. 
         FIG. 4  is a block diagram of a web server consistent with a preferred embodiment of the present invention. 
         FIG. 5  illustrates steps used to implement a preferred embodiment of the present invention. 
         FIG. 6  illustrates steps used to generate a feature vector. 
     
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Referring to  FIG. 1 , there is shown a diagram of a computer system  10  in which an embodiment of the present invention can be implemented. The computer system  10  includes at least one search engine  30 , a plurality of clients  40  (also herein called client computers), a plurality of web servers  50 , and a communications network  20 . The communications network  20 , which interconnects the search engine  30 , the plurality of clients  40 , and the plurality of web servers  50 , is the Internet or other wide area network (WAN), an intranet, a local area network (LAN), metropolitan area network (MAN), or a combination of such networks. 
     As indicated in  FIG. 2 , the search engine  30  includes standard server components such as one or more processing units  202 , an optional user interface  204  (e.g., keyboard, mouse, and a display), memory  206 , a network interface  207  for coupling the search engine  30  to clients  40  and web servers  50  via communications network  20 , and one or more system buses  200  that interconnect these components. Memory  206 , which typically includes high speed random access memory as well as non-volatile storage such as disk storage, stores an operating system  208 , a query processor module  210 , a web crawler module  212 , a feature vector module  214 , a cloak detection module  216 , and a database  218 . 
     The operating system  208  includes procedures for handling various basic system services and for performing hardware dependent tasks. Further, the one or more processing units  202  execute the programs (i.e., the query processor module  210 , the web crawler module  212 , the feature vector module  214 , and the cloak detection module  216 ) under the control of the operating system  208 , which also provides the programs with access to system resources, such as the memory  206  and user interface  204 . 
     The query processor module  210  responds to queries from clients  40  for the URLs of documents stored on the web servers  50 . Each query typically includes one or more search terms, and the response to the query includes zero or more (and preferably one or more) network addresses (e.g., URLs) of objects (e.g., documents maintained by one or more of the web servers  50 ) corresponding to the one or more search terms. More particularly, the query processor module  210  typically selects zero or more URLs for inclusion in a response to the queries by reference to one or more search terms included in the query and to a table of URLs  219  maintained in a database  218 . The particular methodology used for URL selection is not important to the present invention. Many techniques are known in the art, and all are within the scope of the invention. 
     The web crawler module  212  obtains objects from the web servers  50  that correspond to URLs included in the table of URLs  219 . More specifically, the web crawler module  212  updates the list of URLs included in the table of URLs  219  periodically by downloading objects from web servers  50  and determining whether the objects have been modified since the last time a particular object was downloaded. If an object has been modified, information in the table of URLs  219  pertaining to the object is updated. The table of URLs  219  is preferably indexed by the words included in the objects corresponding to the URLs stored in the table of URLs  219 . 
     The web crawler module  212  and query processor module  210  are well known in the art. Except as noted below, with reference to the cloak detection module  216 , these two modules can operate according to any technique without departing from the scope of the present invention. Additionally, the web crawler module  212  and the query processor module  210  can also operate on separate servers. 
     The feature vector module  214  generates a feature vector for an object. A feature vector is a compressed representation of an object, comprising a plurality of discrete features, and is typically much smaller than the object. In preferred embodiments of the present invention, feature vectors are used to compare objects. The likelihood that a first object closely resembles a second object is very high when a feature vector derived from the first object and a feature vector derived from the second object include at least a predetermined number of features in common. For example, in an embodiment where the feature vector for each object contains eight features, two objects whose feature vectors have at least six features in common are assumed to be very similar. The generation of a feature vector is described in more detail below with reference to FIG.  6 . 
     The cloak detection module  216  preferably augments the operation of the query processor module  210  and web crawler module  212  as indicated above. In particular, when the query processor module  210  receives a query from a client  40 , the query processor module  210  notifies the cloak detection module  216 , which responds by selecting, and forwarding to the query processor module  210 , a URL corresponding to a web server  50 . The selected URL returned to the query processor module  210  may be one of the URLs that is responsive to the client query, or it may be a URL that is unrelated to the URLs that are responsive to the client query. 
     In preferred embodiments, the cloak detection module  216  applies a predefined function to the table of web servers  220  to select a URL. As illustrated in  FIG. 1 , the table of web servers  220  preferably includes a plurality of records  222  including fields that store a URL, a date, and a state. 
     In some embodiments, the URLs include only an access protocol (e.g., http) followed by a hostname (e.g., www.domain_name.com). In these embodiments, therefore, the URLs stored in the table of web servers  220  do not specify a hierarchical description of an object or object location on a web server  50 , which are typically configured to provide a default object when a hierarchical description of an object or object location are not included in an object request. 
     In other embodiments, however, a hierarchical description of an object or object location on a web server  50  is specified in each entry  222  (i.e., URL) of the table of web servers  220 . In these embodiments, the table of web servers  220  can include a plurality of entries  222  that correspond to a single web server  50 . In still other embodiments of the present invention, the table of web servers  220  may actually resemble, or be included in, the table of URLs  219 . 
     The date field included with each entry  222  of the table of web servers  220  identifies the last date, if any, on which a web server  50  corresponding to the entry  222  was checked for cloaking. In preferred embodiments of the present invention, the date is a parameter of the function that selects a URL for inclusion with the response generated by the query processor module  210 . Preferably, the odds of a given entry  222  being selected increase as the corresponding date becomes older. 
     The state field included with each entry  222  of the table of web servers  220  reflects the results of one or more determinations as to whether a corresponding web server  50  is cloaked. In some embodiments, the state is, effectively, either yes or no: “Yes”, the corresponding web server  50  was cloaked as of the last test or “No”, the corresponding web server  50  was not cloaked as of the last test. 
     Preferred embodiments of the present invention compare the feature vector of a page retrieved from a specified URL by a client computer  40  with the feature vector of the page retrieved from the same URL by the search engine  30 , and use the results of this comparison to determine whether the web server  50  corresponding to the specified URL is cloaked. As noted above, a feature vector is a representation comprising a plurality of features. If, for example, all of the features included in two feature vectors match, the corresponding objects almost certainly match. And if none of the features included in two feature vectors match, the corresponding objects almost certainly do not match. But if just half of the features included in two feature vectors match, the corresponding objects are likely to be partially similar, but different in many respects. However, the amount of difference between the objects is somewhat indeterminate, although statistically the odds are very high that the two objects are significantly different. Such a situation may call for one or more states and corresponding policies. In some embodiments, therefore, an indefinite response (e.g., only half of the features match) will not change or set the state of a corresponding web server  50 . In such embodiments, a predefined number of determinations that are consistently biased towards cloaked or not cloaked (e.g., most but not all of the features match) are required before a state is changed in the direction of the bias. Additionally, the state field in some embodiments indicates how consistently a corresponding web server  50  is determined to be cloaked or not cloaked. If, for example, a given web server  50  has, over an extended period of time, consistently been determined to be cloaked, the value of additional tests may decline. Similarly, if a given web server  50  has, over an extended period of time, consistently been determined to not be cloaked, the value of additional tests may decline. In such cases, additional testing of such web servers  50  may be delayed in favor of testing other, less stable or unknown, web servers  50 . The state, therefore, preferably reflects these situations so that such web servers  50  are selected less frequently for testing. Additional states and policies for determining whether a web server is cloaked may be apparent to those skilled in the art and systems and methods of implementing these are within the scope of the present invention. 
     In preferred embodiments of the present invention, feature vector representations of objects are compared to determine if the objects are substantially similar. In some embodiments, the feature vector representation of a first object is said to match the feature vector representation of a second object if at least a predetermined number of features in the two feature vectors are the same. 
     At some point, a feature vector and a corresponding URL are received from a client  40  in response to the same URL being supplied to the client  40  in a query response. The feature vector from the client  40  (i.e., the client feature vector) is generated by the client  40  from an object corresponding to the URL. The cloak detection module  216  stores the feature vector and the corresponding URL from the client  40  in the table of URL and feature vector combinations  224 . More specifically, the cloak detection module  216  creates a new entry  226  in the table of URL and feature vector combinations  224  and stores the feature vector and the corresponding URL in the new entry  226 . 
     In preferred embodiments, the cloak detection module  216  subsequently directs the web crawler module  212  to obtain an object corresponding to the URL. In other embodiments, the cloak detection module  216  obtains a copy of the object corresponding to the URL from the table of URLs  219 . In still other embodiments, the cloak detection module  216  obtains the object corresponding to the URL without the assistance of the web crawler module  212 . In these embodiments, the cloak detection module  216  preferably runs on the same machine as the web crawler module  212  or on a machine that is known by web server operators to be associated with the web crawler module  212  (i.e., using an IP-address associated with the web crawler module  212 ). Additionally, the USER_AGENT field of requests sent by the cloak detection module  216  is preferably identical to the USER_AGENT field of requests sent by the web crawler module  212 . It is important that a web server  50  receiving a request directly from a cloak detection module  216  is able to determine that the request is associated with the web crawler module  212  (i.e., a web crawler/search engine). 
     The cloak detection module  216  then directs the feature vector module  214  to create a feature vector (herein called the server feature vector) from the object corresponding to the URL obtained by, or under the direction of, the cloak detection module  216 . In an alternate embodiment, the table of URLs  219  stores a copy of the server feature vector for the object corresponding to each URL in the table (or for each URL that has been successfully downloaded by the web crawler module  212 ) and the cloak detection module  216  obtains the server feature vector for the object corresponding to the URL from the table of URLs  219 , without having to compute the server feature vector. In other words, in this alternate embodiment the web crawler module  212 , or another module of the search engine  30 , uses the feature vector module  214  to process the objects downloaded by the web crawler module and to store the resulting feature vector in the table of URLs  219 . 
     The cloak detection module  216  then preferably uses the URL as an index into the table of URL and feature vector combinations  224  to extract the corresponding client feature vector and compare the client feature vector to the server feature vector. Depending on the results of the comparison and the state of the URL as defined by an entry  222  in the table of web servers  220 , the state of the URL is updated as described above. The cloak detection module  216  also updates the date field in the table of web servers  220  and removes the entry  226  in the table of URL and feature vector combinations  224 . 
     In an alternate embodiment, the table of URL and feature vector combinations  224  is not used. Instead, the object corresponding to each URL to be checked by the cloak detection module is downloaded and processed by the search engine to generate a server feature vector prior to sending the URL to a client  40  for downloading. As indicated above, the server feature vector is preferably stored in the table of URLs  219 . When the client feature vector is received back from the client  40 , the cloak detection module compares the client feature vector with the server feature vector for the same URL and then updates a corresponding entry  222  in the table of web servers  220 . 
     If a given web server  50  is determined to be cloaked, several steps can be taken to address this problem without departing from the scope of the invention. For example, the query processor module  210  can exclude from responses to requests from clients  40  information regarding a cloaked web server  50  or a specific URL corresponding to the web server  50  that would otherwise be included. Additionally, a cloaked web server  50  can be “black-listed” so that it is not queried in the future by the web crawler module  212 , thereby preventing the web crawler module  212  from determining what objects are available on the cloaked web server  50  and whether these objects have been modified. Finally, the query processor module  210  can include a warning with a query response indicating that a given URL corresponds to a cloaked web server  50 . 
     As indicated in  FIG. 3 , the clients  40  preferably include standard computer components such as a central processing unit  302 , a user interface  304  (e.g., keyboard, mouse, and a display), a memory  306 , a network interface  307  for coupling the clients  40  to a search engine  30  and various web servers  50  via communications network  20 , and one or more system buses  300  that interconnect these components. Memory  306 , which typically includes high speed random access memory as well as non-volatile storage such as disk storage, stores an operating system  308 , a web browser module  310 , a web-browser assistant module  312 , a feature vector module  314 , and a database  316 . 
     The operating system  308  includes procedures for handling various basic system services and for performing hardware dependent tasks. Further, the central processing unit  302  executes the programs (i.e., the web browser module  310 , the web-browser assistant module  312 , and the feature vector module  314 ) under the control of the operating system  308 , which also provides the programs with access to system resources, such as the memory  306  and user interface  304 . 
     The web browser module  310  is used to access objects (e.g., HTML documents, graphics, etc.) available from web servers  50  and the search engine  30  via the communications network  20 . As indicated above, the clients  40  query the search engine  30  for URLs corresponding to one or more web servers  50 . More specifically, the clients  40  typically request a plurality of hyperlinks to objects available from the web servers  50 . The web browser module  310  is typically the means by which these queries are submitted by the clients  40 . Examples of web browsers known in the art include Microsoft® Internet Explorer and Netscape® Navigator. Either of these web browsers are suitable for the present invention. 
     In the preferred embodiment, the web-browser assistant module  312  comprises a plug-in that works in conjunction with the web browser module  310 . In the preferred embodiment, the web browser module  310  loads the web-browser assistant module  312  each time the web browser module  310  is loaded (i.e., becomes an active, running program on a client  40 ). The web-browser assistant module  312  preferably manifests visually as a tool bar that is accessible when operating the web browser module  310 . Users of clients  40  can, furthermore, preferably enter search terms (also herein called keywords) and submit the search terms as a query to the search engine  30  directly from the web-browser assistant module  312 . 
     In alternate embodiments, the web-browser assistant module  312  is not visible to users of the clients  40 . In these embodiments, users of a client  40  submit queries to search engines  30  from the web browser module  310 . The operation of the web-browser assistant module  312  is, therefore, largely invisible to users of the clients  40  in these embodiments. 
     As is known in the art, plug-ins and tool bars are able to communicate with, and control, web browsers using an application programming interface (“API”) that corresponds to the particular web browser used. In preferred embodiments, the web browser module  310  and the web-browser assistant module  312  interact in this way. 
     For example, in embodiments of the present invention in which the web browser module  310  comprises Netscape® Navigator, the web-browser assistant module  312  can use what is currently known as the Netscape.Network.1 automation object to access web servers  50  and the search engine  30  using mechanisms of Netscape® Navigator such as the SSL security protocol, proxy support, SOCKS support, cache support, and numerous Internet protocols. In particular, the web-browser assistant module  312  can use the Open ( ) function, which is included in the Netscape.Network.1 automation object, to direct the web browser module  310  to submit a query to the search engine  30  and to download an object corresponding to a URL from a web server  50 . Use of the Netscape.Network.1 automation object does not necessarily result in the display, on user interface  304 , of an object downloaded from a web server  50 . 
     Similarly, the web-browser assistant module  312  can request notification each time the web-browser module  310  goes through an object transition (e.g., displays or loads a new HTML document). For example, in embodiments of the present invention in which the web browser module  310  comprises Netscape® Navigator, the web-browser assistant module  312  can use what is currently known as dynamic data exchange (“DDE”) to control Netscape® Navigator. In particular, the web-browser assistant module  312  registers with Netscape® Navigator using DDE, which has the effect of opening a communications channel between the web browser module  310  and the web-browser assistant module  312 . The communications channel enables the web-browser assistant module  312  to obtain a copy of each search engine query response received by the web browser module  310  and to determine whether that object contains a request for the web-browser assistant to process a URL selected by the cloak detection module  216 . 
     As noted above, the query processor module  210  of the search engine  30  includes a URL selected by the cloak detection module  216  with at least a subset of the responses to queries received from at least a subset of the clients  40 . And as also noted above, the responses include a plurality of hyperlinks (i.e., URLs). Both the URL selected by the cloak detection module  216  and the plurality of hyperlinks are preferably delivered to the clients  40  in an HTML document. As is known in the art, HTML documents can include a header, which is demarcated by the tags “&lt;head&gt;” and “&lt;/head&gt;” and stores a document title and other, optional elements. Each element of the header is typically demarcated by its own pair of complementary tags, such as &lt;title&gt; and &lt;/title&gt;. The contents of the document header are typically not displayed by the web browser module  310 . In some embodiments, therefore, the URL selected by the cloak detection module  216  is preferably inserted into the header of an HTML document comprising a response by the query processor module  210 . For instance, in one embodiment the URL selected by the cloak detection module  216  is stored in an element (also called a field) of the document header demarcated by a pair of complementary tags, such as &lt;cloakchk&gt; and &lt;/cloakchk&gt;, which need be recognizable only by the web-browser assistant module  312 . If the web browser module  310 , and other web browsers known in the art, do not recognize a given tag, which is likely in this case, the contents of the tagged element (i.e., the information between the pair of complementary tags) are ignored. An HTML document returned by the query processor module  210  can, therefore, include a URL selected by the cloak detection module  216  without adversely affecting a client  40  regardless of whether the client is configured in accordance with the present invention. Note that additional instructions need not be included with the URL since the tags recognizable only by the web-browser assistant module  312  effectively comprise an instruction to the web-browser assistant module  312  to take action. Nevertheless, additional information such as operating parameters for the feature vector module  314  or notification of software updates can be included along with the URL. 
     But in some embodiments, a URL selected by the cloak detection module  216  is instead included in the HTTP header of responses to queries received from the clients  40 . 
     Table 2 illustrates the contents of a typical HTTP header modified in accordance with an embodiment of the present invention: 
     
       
         
           
               
               
             
               
                   
                 TABLE 2 
               
               
                   
                   
               
             
            
               
                   
                 HTTP/1.0 200 OK 
               
               
                   
                 Server: Microsoft-IIS/5.0 
               
               
                   
                 Date: Tue, 18 Dec 2001 06:31:55 GMT 
               
               
                   
                 Content-Length: 10867 
               
               
                   
                 Content-Type: text/html 
               
               
                   
                 X-Check-For-Cloak: http://www.some-site.com/index.html 
               
               
                   
                   
               
            
           
         
       
     
     The first line of Table 2 identifies the protocol used and whether the request was successful from the perspective of the protocol. In this example, the protocol is version 1.0 of HTTP. The second line of Table 2 is an optional aspect of HTTP headers that identifies the web server software run by the search engine  30  that sent the response. The third, fourth, and fifth lines of Table 2 indicate, respectively, the current date and time according to the search engine  30 , the size of the accompanying object in bytes, and the format (i.e., content type) of the accompanying object. The sixth line of Table 2 identifies a URL selected by the cloak detection module  216 . The first five lines of Table 2 are representative of typical HTTP headers. The sixth line is a modification consistent with an embodiment of the present invention. 
     As noted above, unknown tags are ignored by the web browser module  310  and other web browsers known in the art. The same is true of unknown elements, fields, or lines of an HTTP header. An HTTP header returned by the search engine  30  can, therefore, include a URL selected by the cloak detection module  216  without adversely affecting a client  40  regardless of whether the client is configured in accordance with the present invention. Note that additional instructions need not be included with the URL since an HTTP header element identifier (e.g., “X-Check-For-Cloak”) recognizable only by the web-browser assistant module  312  effectively comprises an instruction to the web-browser assistant module  312  to take action. Nevertheless, additional information such as operating parameters for the feature vector module  314  or notification of software updates can be included along with the URL. 
     Additionally, persons skilled in the art recognize that techniques similar to those described above permit the web-browser assistant module  312  to access the HTTP header to obtain information germane to the present invention. 
     The feature vector module  314  generates a feature vector from an object. As noted above, a feature vector is a representation of an object that comprises a plurality of discrete features and is typically much smaller than the object. Typically, the web-browser assistant module  312  directs the feature vector module  314  to create a feature vector from an object that corresponds to the URL selected by the cloak detection module  216 . 
     The database  316 , which comprises a cache of documents downloaded by the web browser module, preferably includes entries  318  for each URL selected by the cloak detection module  216  and received by a particular client  40 . Initially, an entry  318  includes only the URL. But after the web-browser assistant module  312  receives the object corresponding to the URL, the entry  318  is updated to include the object. Furthermore, the entry  318  may also be subsequently updated to include a feature vector created by the feature vector module  314  from the object. In some embodiments, an identifier of the search engine  30  is included in the database  316  for use when the web browser module  310  delivers the URL and the feature vector to the search engine  30 . 
     As indicated in  FIG. 4 , a typical web server  50  preferably includes standard computer components such as one or more central processing units  402 , an optional user interface  404  (e.g., keyboard, mouse, and a display), a memory  406 , a network interface  407  for coupling the web server  50  to a client  40  and a search engine  30  via communications network  20 , and a bus  400  that interconnects these components. Memory  406 , which typically includes high speed random access memory as well as non-volatile storage such as disk storage, stores an operating system  408 , a client interface module  410  (sometimes called a protocol engine), and a database  412  of documents. 
     The operating system  408  includes procedures for handling various basic system services and for performing hardware dependent tasks. Further, the central processing unit  402  executes the programs (i.e., the client interface module  410 ) under the control of the operating system  408 , which also provides the programs with access to system resources, such as the memory  406  and user interface  404 . 
     The client interface module  410  (e.g., Apache and Microsoft® Internet Information Server (IIS)) preferably serves static content (e.g., HTML documents and images) or dynamic content (e.g., content generated using the Common Gateway Interface standard) to a web browser module  310  operating on a client  40  or a web crawler module  212  operating on a search engine  30  via communications network  20  using well known principles. 
     Further, the client interface module  410  may store static content in the database  412  illustrated in FIG.  4 . The database  412  typically includes an entry  414  for each object stored in the database  412 . In other embodiments, the client interface module  410  stores the static content in a directory system instead of, or in addition to, the database  412 . 
     Turning now to  FIG. 5 , there are illustrated steps used to implement a preferred embodiment of the present invention. In a first step, a client  40  issues a request for a search engine service (step  500 ). As indicated above, this typically includes a user of the client  40  entering one or more search terms into the web-browser assistant module  312 . The web-browser assistant module  312  then directs the web browser module  310  to send an HTTP message including the search terms to the search engine  30 . To send the HTTP message, the web-browser assistant module  312  takes advantage of the networking capabilities of the web browser module  310 . At this point, the web-browser assistant module  312  need not take any particular action in anticipation of, or in preparation for, processing a URL selected by the cloak detection module  216 . Instead, the web-browser assistant module  312  preferably waits for notification from the web browser module  310  each time the web browser module  310  loads an object. 
     Once the request is received by the search engine  30 , the query processor module  210  generates a response using techniques known in the art (step  502 ). Briefly, the query processor module  210  scans the table of URLs  219  for zero or more URLs that best match the query. The best matching URLs, if any, are preferably assembled in an HTML document. 
     Additionally, the query processor module  210  solicits a URL from the cloak detection module  216  upon receiving the query from the client  40 . In response, the cloak detection module  216  selects a URL from the table of web servers  220  (step  504 ). The particular function used to select the URL is not critical to the present invention. But the table of web servers  220  preferably includes information such as the date on which the corresponding web server  50  was last selected and the current state of the corresponding web server  50  in the selection process. For example, the cloak detection module  216  in some embodiments of the invention selects the URL with the oldest date, i.e., the longest amount of time since the last test. In another embodiment, the cloak detection module  216  selects one of the URLs in the response to the query if any of the URLs in the response correspond to a web server whose cloak status needs to be checked, and otherwise selects a URL from the URLs stored in the table of web servers  220 . In still another embodiment, the URLs in the table of web servers  220  are selected sequentially, in round robin fashion. In yet another embodiment, the cloak detection module  216  maintains a list of URLs previously selected from the table of web servers  220 , but for which no response has been obtained from the client computer to which the URL was sent. URLs in this list that were last sent to a client computer more than a predefined amount of time ago (e.g., one minute) are re-selected by the cloak detection module  216 . 
     After selecting a URL, the cloak detection module  216  forwards the URL to the query processor module  210 , which inserts the URL into its query response and sends the response to the client  40  from which the query originated (step  506 ). 
     Upon receiving the response at the client  40 , the web browser module  310  preferably loads the HTML document included therein. The web browser module  310  also notifies the web-browser assistant module  312 , which scans the HTML document, or alternatively the accompanying HTTP header, to extract the URL selected by the cloak detection module  216  (step  508 ) and preferably stores the URL in a new entry  318  in the database  316 . 
     The web-browser assistant module  312  then directs the web browser module  310  to download an object corresponding to the URL selected by the cloak detection module  216  from the web server  50  identified by a hostname included with the URL (step  510 ). 
     After directing the web browser module  310  to download the object, the web-browser assistant module  312  typically requests status updates from the web browser module  310  to determine when the object is available to the web-browser assistant module  312 . But in some embodiments, the web browser module  310  notifies the web-browser assistant module  312  when the object is available to the web-browser assistant module  312 , so no action need be taken by the web-browser assistant module  312  with respect to this object until such notification is received. 
     Upon receiving the object request (e.g., HTTP request for an HTML document) at the web server  50 , the client interface module  410  creates the object dynamically or locates the object in an entry  414  of the database  412  or on the disk storage of the memory  406  (step  512 ). After locating or creating the object, the client interface module  410  sends the object to the client  40  (step  514 ). As noted above, aside from engaging in cloaking, the operation of the web server  50  is not critical to the present invention. 
     Once the object is available to the web-browser assistant module  312 , the web-browser assistant module  312  stores the object in a corresponding entry  318  of the database  316 . The web-browser assistant module  312  then directs the feature vector module  314  to generate a feature vector from the object (step  516 ). 
       FIG. 6  illustrates the operation of the feature vector module  314  (and  214 ) in more detail. First, a set of canonicalization rules are applied to the object to generate a set of tokens (step  610 ), wherein each token represents an aspect of the object (e.g., a word). One canonicalization rule, for example, includes expanding the object to include common variations of one or more of the tokens. A set of tiles are then generated from the set of tokens (step  620 ), wherein each tile comprises a sequence of two or more of the tokens that form the set of tokens. Next, the feature vector module  314  assigns an identification element to each tile in the set of tiles to create a set of identification elements (step  630 ). An identification element is typically a short tag for a larger or relatively large item such as a tile. In a preferred embodiment, the identification elements are generated in step  630  by applying a hash function or fingerprint function to each tile in the set of tiles generated in step  620 . 
     The feature vector module  314  then creates a set of permuted identification elements (step  640 ). Each set preferably consists of a permuted version of each of the identification elements assigned in step  630 . Further, each permuted identification element in a given set of permuted identification elements is the result of a common permutation process. Further, a different permutation process is preferably used for each of the sets of permuted identification elements. The feature vector module  314  then selects a predetermined number of permuted identification elements, which the feature vector module  314  partitions into a plurality of groups (step  650 ). The selected permuted identification elements are selected using a selection function. In some embodiments the selection function selects the identification elements with the lowest or highest value in each set of permuted identification elements. Other selection functions can be used without departing from the scope of the present invention. 
     Finally, the feature vector module  314  produces a feature value from each of the plurality of groups (step  660 ). Each feature value is the result of applying a function (e.g., a hash function or a fingerprint function) to a corresponding group of permuted identification elements. The set of resulting feature values comprises the feature vector for the object. The result of this process is a representation (i.e., a feature vector) that is both accurate with respect to determining whether two objects match (i.e., exactly match or, preferably, substantially match) and compact in comparison to the object from which it is derived. 
     Methods for generating feature vectors for specified documents are disclosed in U.S. Pat. No. 6,119,124 entitled “Method For Clustering Closely Resembling Data Objects” and U.S. Pat. Nos. 5,909,677 and 6,230,155 both entitled “Method For Determining The Resemblance Of Documents”. Each of these patents is incorporated herein by reference as background information. 
     The feature vector comprises a plurality of feature values, and is preferably stored in a corresponding entry  318  of the database  316 , which now includes the URL selected by the cloak detection module  216 , an object corresponding to the URL, and a feature vector generated from the object. Referring once again to  FIG. 5 , the web-browser assistant module  312  directs the web browser module  310  to send the URL and the feature vector to the search engine  30  (step  518 ). 
     Upon receiving the URL and the feature vector at the search engine  30 , the cloak detection module  216  directs the web crawler module  216  to request the object corresponding to the URL received from the client  40  from the web server  50  identified by the URL (step  520 ). In a preferred embodiment, the cloak detection module  216  stores the URL and feature vector received from the client  40  in an entry  226  of the table of URL and feature vector combinations  224  for subsequent processing. 
     Upon receiving the object request at the web server  50 , the client interface module either creates the object dynamically or locates the object in an entry  414  of the database  412  or on the disk storage of the memory  406  (step  522 ). If the web server  50  is cloaked, the client interface module  410  will probably detect that the request originated from a search engine  30  and create or locate an object specifically for that search engine  30 . After locating or creating the object, the client interface module  410  sends the object to the search engine  30  (step  524 ). 
     Once the object is received from the web server  50  at the search engine  30 , the cloak detection module  216  directs the feature vector module  214  to create a feature vector (i.e., the server feature vector) from the object (step  526 ), which preferably operates as described above with reference to FIG.  6 . The cloak detection module  216  then compares the two feature vectors—one created by the client  40  and the other created by the search engine  30  (step  528 ). 
     As described above, in an alternate embodiment, steps  520 ,  522 ,  524 ,  526  for downloading the object at the specified URL and generating a server feature vector for the object are performed prior to sending the specified URL to a client (at step  506 ) for downloading. 
     As stated above, a feature vector comprises a plurality of feature values. The likelihood that a first object closely resembles (i.e., is substantially similar to) a second object is very high when a feature vector of the first object shares at least a predetermined number of features with a feature vector of the second object. If the first object closely resembles (or is substantially similar to) the second object (i.e., at least the predetermined number of features match), then it is unlikely that the web server  50  is cloaked. An exact match is not required because objects (i.e., web pages) may change in minor ways from time to time due to advertising content and other non-substantive changes. A web page at the specified URL may also vary slightly from one download to the next because it contains dynamically generated contact, such as the date and time of day, or the name of a user associated with the requesting computer. Additionally, a feature vector is only a representation and does not capture all of the features of a given object. It is therefore possible (but very unlikely), that non-matching objects may produce identical feature vectors. In addition, it is possible (but once again unlikely) that two objects that are different but substantially similar in all important respects may have feature vectors that do not have at least the predetermined number of features in common. 
     Depending on the result of the comparison, the cloak detection module  216  takes one or more predetermined steps (step  530 ). For example, the cloak detection module  216  preferably updates the state of the URL in the table of web servers  220 . Additionally, if the web server  50  is cloaked, the cloak detection module can modify the table of URLs  219  so that the query processor module  210  does not include URLs corresponding to this web server  50  in query responses until after subsequent testing indicates that the web server  50  is no longer cloaked. 
     The present invention can be implemented as a computer program product that includes a computer program mechanism embedded in a computer readable storage medium. For instance, the computer program product could contain the program modules shown in  FIG. 2  or  FIG. 3  or both. These program modules may be stored on a CD-ROM, magnetic disk storage product, or any other computer readable data or program storage product. The program modules may also be distributed electronically, via the Internet or otherwise, by transmission of a computer data signal (in which the program modules are embedded) on a carrier wave. 
     While the present invention has been described with reference to a few specific embodiments, the description is illustrative of the invention and is not to be construed as limiting the invention. Various modifications may occur to those skilled in the art without departing from the scope of the invention as defined by the appended claims. 
     For example, in alternate embodiments, the web-browser assistant module  312  operates independently of the web browser module  310 . In these embodiments, the web-browser assistant module  312  includes functionality typically found in web browser, i.e., the ability to interact with web servers  50  and search engines  30  to send and receive objects. 
     In other embodiments, the web-browser assistant module  312  is not passive as described above. In these embodiments, the web-browser assistant module  312  requests the selection of a URL by the cloak detection module  216  periodically or according to some other schedule. 
     In still other embodiments, the cloak detection module  216  does not wait for requests for search engine  30  services to select a URL for cloak detection. Instead, the cloak detection module  216  selects such URLs on an on-going basis. The selected URLs are subsequently distributed to one or more clients  40  that are configured to receive unsolicited URLs from the cloak detection module  216  and that are known to the cloak detection module  216 . 
     In some embodiments, the web-browser assistant module  312  monitors the web browser module  310  to determine whether a user operating the client  40  selects one of the URLs selected by the query processor module  210 . If so, the web-browser assistant module  312  generates a feature vector from the object corresponding to the selected URL, and sends the selected URL and corresponding feature vector to the search engine  30 . In these embodiments, therefore, network resource requirements of the present invention are reduced. And in some of these embodiments, the cloak detection module  216  selects a URL from among the zero or more URLs selected by the query processor module  210 . So if a user operating the client  40  does not select one of the URLs selected by the query processor module  210 , the web-browser assistant module  312  will instead process the URL selected by the cloak detection module  216 . 
     Finally, some embodiments are designed for systems that have relatively large amounts of bandwidth available for use by the present invention. In these systems, feature vectors, which as noted above are compressed representations of objects, are not used. Instead, the client  40  forwards the object, a portion of the object, or an object representation dissimilar to the feature vector described above, to the search engine  30 . Like the client  40 , the search engine  30  does not use feature vectors and compares objects, portions of objects, or object representations dissimilar to the feature vector described above to determine whether the objects match.