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Identity and storage in Web 3.0. Web 1.0. 1993 - 2004. Tens of kb. Success stories. Amazon Ebay Yahoo. Web 1.0. High cost to entry and play Compared with before you could have relatively easy a national and an international presence Several publishers Few services - PowerPoint PPT Presentation
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Secure Systems Research Group - FAU
Identity and storage in Web 3.0
Secure Systems Research Group - FAU
Web 1.0
Secure Systems Research Group - FAU
1993 - 2004
Secure Systems Research Group - FAU
Tens of kb
Secure Systems Research Group - FAU
Success stories
Amazon Ebay Yahoo
Secure Systems Research Group - FAU
Web 1.0
High cost to entry and play
– Compared with before you could have relatively easy a national and an international presence
Several publishers Few services Limited customer feedback
Customers had to choose between services offered by others
Secure Systems Research Group - FAU
Web 1.0 Identity
Customers had to prove they are legitimate clients
Companies had to protect account's information Identity would usually contain:
Username Password Address , billing and shipping Credit Card
Secure Systems Research Group - FAU
Web 1.0 Identity
Secure Systems Research Group - FAU
Web 1.0 Data storage
Relational databases Relation database design using entity relation
diagrams Oracle , Sql Server Large databases Transactions The data stored was more text, especially data
related with order processing
Secure Systems Research Group - FAU
Web 1.0 Technologies
Java and .Net N Tier Architecture Web Browser,Web Server,
Application Server, Database J2EE, Servlets, Jsp
Secure Systems Research Group - FAU
Web 2.0
Secure Systems Research Group - FAU
2004 - 2015?
Secure Systems Research Group - FAU
Mb bandwidth
Secure Systems Research Group - FAU
Web 2.0
Low cost to have your own website hosted. Many publishers Major number of services Multiple customer feedback
Customers can create content and be part of services
Customers can give great feedback
– Chats, blogs, pictures, movies integrated into commercial web pages
Secure Systems Research Group - FAU
Success stories
Google Popularity success stories
Wikipedia , emergency of the collective Facebook Youtube My Space World Net
Secure Systems Research Group - FAU
Emergency of collective products
Secure Systems Research Group - FAU
Web 2.0 Identity
In web 2.0 a lot of information identity is disclosed by people
Beside name, shipping address, billing address we have birth date, friends , friend of a friend , interests, pictures, movies and blogs
Identity in Web 2.0 is spread across many websites like Facebook, My Space, You Tube, Blogger
People need to be careful in building their web 2.0 identity since it can affect decisions like employment
Secure Systems Research Group - FAU
Identity
Secure Systems Research Group - FAU
Web 2.0 Data storage
The data storage is supported by the normal relational databases
We have virtual object databases by using persistence frameworks like Hybernate
Since we have movies and pictures we have big databases at around tens of terabytes
In web 2.0 we have bigger databases because of multimedia documents managed
Secure Systems Research Group - FAU
Web 2.0 Data storage
A new type of database is emerging, cloud based databases . Beside the relational databases, blogs, pictures and other items across Internet can be managed. http://www.itworld.com/saas/69183/watch-out-oracle-google-tests-cloud-based-database
Secure Systems Research Group - FAU
Web 2.0 technologies
Web services, Soap Rest Rich client interfaces Java Script, Ajax , Json Cloud computing Mash ups Software as a service
Secure Systems Research Group - FAU
Web 3.0
Secure Systems Research Group - FAU
2016? - 2025?
Secure Systems Research Group - FAU
Tens of Mb of bandwidth
Bandwidth influences directly the user interface Web 1.0 means text + pictures only interface Web 2.0 means flash, video interface. It means
Java Script, Ajax, Json interface, Scalable Vector Graphics. Mobile Web
Web 3.0 means new technologies will be developed to bring an even richer interface . 2D will move to 3D. Example car looking from inside. From 2D floor plan to 3D apartment visualization .
Secure Systems Research Group - FAU
Success stories
Amazon gives the people the possibility to find products of interest by displaying what other people bought after buying a similar product
Scientific Publishing task force - > group that tries to revolutionize scientific publishing
– That means what you publish will be understood by computers
Secure Systems Research Group - FAU
Web 3.0
Web is going to be open to machine processing Machines can operate as agents. Semantic web. Information is going to be
organized as knowledge. Will this impact data storage? Are we going to have knowledge databases? How are they going to look? How about virtual knowledge databases?
Secure Systems Research Group - FAU
Web 3.0 data storage
RDF database. www.guha.com Manages 3 value types (verb source target) or
(arc source target) Example likes Mike pizza. In Rdf every object has an URI, unique
resource locator Example: (http://abc.org/rdf#likes
http://abc.org/Persons/Mikes http://abc.org/Food/pizza)
Secure Systems Research Group - FAU
Rdf database creation
Syntax Create database database_name
Example Create database test
Secure Systems Research Group - FAU
Rdf file load or unload
Syntax Load [file_type] [url] into database file_type can be RDF_XML , RSS ,
RDF.DMOZ_RDF Unload file [url] from database [database]
Example Load DMOZ_RDF file http://abc.org/rdf/abc.rdf into
database
Secure Systems Research Group - FAU
Rdf database insert
Syntax Insert into [database_name] (arc1 source1 target1)
(arc2 source2 target2) ….(arcn sourcen targetn)
Example Insert into test (http://abc.org/rdf#likes
http://abc.org/Person/Mike http://abc.org/Food/pizza)
Secure Systems Research Group - FAU
Rdf Database delete
Syntax Delete from [database_name] (arc source target)
Secure Systems Research Group - FAU
Rdf Database Select
Syntax Select [variable1 variable2 …. variablen] from
{database} where [constraint1,constraint2,...]</>
Example Select ?x,?y from test where (likes ?x ?y)
Secure Systems Research Group - FAU
Data storage in web 3.0
If we would look at lessons learned in Web 2.0 , maybe not a rdf database will be the answer, but a semantic relational mapping framework.
virtual semantic database.
Secure Systems Research Group - FAU
Ontology
Is a representation of knowledge Contains:
Individuals Classes Attributes Relations Function terms Restrictions Rules Axioms Events
Secure Systems Research Group - FAU
Ontology
Ontology can be expressed through languages like OWL or Web Ontology Language
OWL extends RDF so it can be stored in a rdf database
Protege is an open source ontology editor Jena = semantic web framework for java
Secure Systems Research Group - FAU
Identity in web 3.0
Identity can be reconstructed by software agents from social networks
Can an user build the identity he wants? Contains name, address, birth date, picture,
photos, friends, interests, movies Will contain the identity of software agents that
will be probably the identity of the person they represent
Secure Systems Research Group - FAU
Can an user control its identity ?
In Web 2.0 this is hard since many web sites are not interconnected
Maybe in web 3.0 this will be easier Putting the identity in the hands of people is
desired
Secure Systems Research Group - FAU
Identity can be processed by software computers
Return all java programmers that like science fiction and have camped on Andes , will become a possibility
Return all papers concerning identity and storage in web 3.0 will become something feasible
Secure Systems Research Group - FAU
Identity in web 3.0
Secure Systems Research Group - FAU
Questions?