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#Introduction
# Principle of Data Protection

Course note for Principle of Data Protection at 20115-2016 Q4, [course website](http://security1.win.tue.nl/~zannone/teaching/CS4080/CS4080-15-16.html)

All rights belong to the professor, here just make some note.

###Contents




* [Introduction](README.md)
* [Discretionary Access Control自主访问控制](discretionary_access_control.md)
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* [eXtensible Access Control Markup Language (XACML) Part 2](extensible_access_control_markup_language_xacml_2.md)
* [Reduction of access control decisions](reduction_of_access_control_decisions.md)
* [Assignment and Exam](assignment_and_exam.md)
* [Summary](SUMMARY.md)


Due to import from GitBook directly, the structure is not well organized.

##About
- Data Protection and Privacy
- Access Control
- Policy Languages, Models, and Standards

##Course Objectives
Understand the relevance of data protection
A detailed understanding of the most important access control models
Knowledge of the well-established privacy principles
Ability to specify access control and privacy policies
Ability to evaluate access control and privacy policies

##Topics covered
- Access Control
- Usage Control
- Privacy-aware Access Control
- eXtensible Access Control Markup Language(XACML)
- A taste of research

##Outline
- Defining Privacy
- Privacy Threatss
- Appliaction
- Location-based services
- RFID
- Social Networks
- Privacy Enhancing Technologies

##Defining Privacy
Abstract and subjective concept, hard to define-->Dependent on cultural issues, study discipline, stakeholder, context

Popular definitions:
- (Privacy as Confidentiality)“The right to be let alone” (Brandeis & Warren, 1890)-->Focus on freedom from intrusion
- (Privacy as Control)“The right of the individual to decide what information about himself should be communicated to others and under what circumstances”(Westin, 1967)-->Focus on control/Focus on information self-determination
- (Privacy as Practice)“The freedom from unreasonable constraints on the construction of one’s own identity” (Agre, 1999)-->Focus on autonomy

###Privacy Paradigms
![Privacy Paradigms](559F56C080793788AE6C795EFF53FE69.jpg)

###What Privacy is About
- Privacy concerns personal information
- Privacy is more than confidentiality (机密性)
- Freedom from intrusion(闯入;打扰;(对某事的)干扰, 干涉)
- Control of informationn about oneself
- Autonomy(自治，自治权)

##Privacy Threats
How much privacy do we have left?
###Data Life Cycle
![Data Life Cycle](20A82DA950ABB5F7F6A702461DDF7F6D.jpg)

###Taxonomy(分类学,分类系统) of Privacy Threats(Solove)
- Information collection
- surveillance(监视)
- interrogation(讯问(审问)的行为实例;讯问(审问)过程，疑问句;问题)
- Information processing
- aggregation(聚集,集成;集结;聚集体,集成体)
- identification
- insecurity
- secondary usage
- exclusion
- Information dissemination(散播;宣传)
- breach(破坏, 违反;破裂, 不和;缺口, 裂口;攻破;破坏, 违反) of confidentiality
- disclosure
- exposure
- increased accessibility
- blackmail
- appropriation(拨付,拨发;拨款;占用,挪用,盗用)
- distortion(曲解;失真)
- Invasion(侵犯；入侵，侵略；侵袭)
- intrusion
- decision interference(干涉, 介入;阻碍, 干扰)

###Secondary Usage
Use information for a purpose other than the one for which it was obtained

- Use of customer information for marketing
- Sale(or trade) of consumer information to other businesses
- Government agencies' use of consumer database

###Aggregation
Combining and comparing information from more than one database

- Why aggregation is a problem? Data already in the system
- Individual pieces of data may be not very telling
- But when combined together, they may reveal(显示; 露出;泄露; 透露) more information about a person
![aggregation](8C07481A0A06E9082FF27EA81B1C5856.png)

- Aggregated information about a person is often used to judge her
- Amazon.com uses aggregated data about book-buying history to recommend other books
- Sharing of government agencies’ databases to detect frauds
- Insurance companies can make decisions based on information of diseases, lifestyles, etc.
- Aggregations of credit reports used to evaluate a person’s financial reputation for granting loans

###Video Surveillance
CCTV monitoring at public places(airports, malls,...)

###Other Threats
- Invisible Information Gathering
- Satellite surveillance
- Loyalty cards(e.g., supermarket club cards)
- Web-tracking data; cookies
- ISPmonitoring
- Your ISP "knows" every site you visit
- Google stores your search history
- Profiling 例子17页
- Use of customer preferences to predict behaviors of people
- Profiling customers to determine their propensity(倾向;习性) toward a product/service
- Government agencies create descriptions of possible terrorists
- Identity Theft
- Discrimination (propensity)

###Why now?
Computers not needed for the invasion of privacy

Digitization of information make it possible to
- collect and store massive amout of personal information
- correlate information from different sources
- access information on the network locally or remotely

Computers simply make new threats possilbe and old threats more powerful

##Applications
- Location-based services
- RFID
- Social Networks

###How many ways can we be located today?

- cell phone (turned on?)
- laptop
- credit card at the gas station
- bank card in the ATM machine
- driving through a monitored intersection
- security camera at the supermarket
- scan badge to enter a building
- ...

###Location Based Service
- location-based traffic monitoring and emergency services
- e-Call, traffic congestion control
- location/service finder:
- where is the nearest restaurants, gas station,..
- variable pricing applications
- congestion pricing
- pay-as-you-drive
- social applications
- Geotagged Twitter
- Google Latitude

####Why is this a problem?
- do you want to be seen at certain location (abortion clinic, AIDS clinic, business
competitor, or political headquarters)
- what can be automatically inferred about a person based on location?
- any important location...
- desk in a building
- home location
- future locations
- and even identification!

###RFID Technology
- Radio Frequency Identification
- A micro-chip transmitting data when exposed to radio waves
- Conceptually similar to bar code-->used to identify and track objects of interest

###RFID Data Collection Process
![01-Intro-2.jpg](7870E50E4AC8C684032666E0B769CE26.jpg)

###RFID Application
![01-Intro-2.jpg](730195BBCBAC8FAD789CE44F23A0F300.jpg)

###RFID From the news
2006: President of Colombia agreed to require Colombian
citizens to be implanted with RFID chips before they could gain
entry into the US for seasonal work.

2008: UK jails considering RFID implants for prisoners.

2015: Tenants of a hi-tech office block in Sweden implanted with
RFID chips in order to gain access to the office and operate
photocopiers.

###RFID-Privacy Issues

- Traceability
- Disclosure of embarrassing information
- Discrimination
- Target by muggers
- ...

##Social Networks
Many people publish their personal information on social networks

###Social Networks--Privacy Issues 见30,31,32

- Used by professors, parents, and employers
- Used by law enforcement and college administrators for disciplinary action
- Used for surveillance and data mining
- Used by merchants for marketing
- Use by other members for criminal purposes (e.g., stalking, invasion of privacy)

##Privacy Enhancing Technologies
How can we protect privacy?

###Scenario
![01-Intro-2.jpg](B093076E9293A72127E41F48D3478DA3.jpg)
![01-Intro-2.jpg](D8F94E33F98CC22027FB06219A84FDC0.jpg)

###Privacy as Control: Assumptions
- Collection and Processing of personal information is useful and necessary
- Search engines: historical search data helps improve search algorithms
- Hospital: health records
- Organizations have an interest in protecting user privacy
- Organization trusted to enforce user privacy preferences
- Privacy problems arise when personal information is misused

###Privacy as Control: Threats
- Database of queries can be breached
- information made public
- information abused by malicious insider and sold for profit
- Query data used for illegitimate purposes
- Query data shared with other parites without user consent(e.g.,advertisers)
- Time queries are stored("right to be forgotten")

###Privacy as Control: Goals
- Focus on:
- control over personal data
- compliance(服从,听从,顺从) with data protection regulations
- Providing individuals with means to control use of their information
- Information consent, privacy settings
- Providing organizations with means to
- define and enforce security and privacy policy
- prevent/detect misuse of personal information

###Privacy Settings
- Allow users to specify their privacy preferences
- Make it easier for users to configure their privacy setting
- privacy preference languages, e.g., APPEL, XPref
- default suites of privacy settings
- privacy wizard that automate configuration of settings

NOTE: Enforcement of privacy settings is done by the organizationn

###Purpose-based Access Control
- Regulate access to data
- Privacy-aware Access Control languages
- Specify which action a user can perform on a given objects
- Specify the allowed usage of data
- Policy enforcement
- Ensure the purpose of data access is complaint with intended purpose

NOTE: No control after disclosure of data

####Purpose Control

- Verify whether data have been used for the intended purpose
- Auditing(查账, 审计, 审核; 审计学) Mechanism
- log data access and processing operations
- analyze logs to detect policy violations

###Privacy as Control: Main characteristics
- Privacy is defined as the ability to specify acceptable data usage through
- policies defined by users(settings)
- policies defined by the organization
- Organizations are trusted to enforce policies

###Privacy as Confidentiality: Assumptions
- Lack of transparency and data protection enforcement
- once data are under the control of an organization it is very difficult to verify how they are actually used
- abuse of personal information may not be evident to individuals
- Organizations that collect and process user data are not necessarily competent and honest, security is expensive
- Incentive to collect and use personal data for financial gain(without regard for user privacy)
- Large number of reported privacy breaches(Due to the lack of appropriate security practices)
- Placing high trust in organizations makes individual vulnerable(易受伤的, 脆弱的, 敏感的)

###Privacy as Confidentiality: Threats
- Queries themselves are sensitive
- Inferred profiles(aggregated data)
- Linkability of user information across different contexts
- Identifiability: queries are hard to anonymize
- Massive collection of user information is considered in itself a privacy threat
- allow a variety of privacy violations: discrimination, manipulation, opportunistic abuse
- information asymmetries(不对称) reinforce power asymmetries: surveillance society

###Privacy as Confidentiality: Goals
- Focus on minimal information disclosure
- Create an individual autonomous sphere free from intrusion
- Disclosure of information is BY DEFAULT prevented, or informaiton is minimally disclosed in a way that cannot be linked back to the individual
- individuals may still disclose information voluntarily

###Anonymous credentials
- Based on zero-knowledge
- Prover can prove:
- he holds a credential with certain attributes, or
- any experession on them(simple arithmetic, boolean)e.g., age>18, gender=female
- Verifier gains no more information
- Applicaiton: E-cash

###Steganography and Covert Communications
- Encryption: hide data content
- Anoymity/unlinkability: hide identities/relations
- Unobservability: hide existence
- Communications:
- Hide the fact that there is any communications
- Embed a communication within another
- Covert channels: hide secrets within public informationn
- Storage:
- Hide the existence of files
- Under coercion(强迫；强制；高压政治；威压) can deny there are any files to decrypt
![01-Intro-2.jpg](8995275BEE68C2277B2D4FB2F2FAD318.jpg)

###Privacy as Confidentiality: Main Characteristics
- Privacy is defined as properities hard-coded in the technology itself
- Goal of technology is to ensure privacy properties hold
- Preventing data disclosure
- Minimize the need to trust others for handing sensitive data

###Privacy as Practice: Assumptions
Transparency provide users with an understanding of the system
- Transparency produces awareness
- Awareness evokes actions

###Privacy as Practice: Threats
Users has no means to know:
- which data are collected
- for which purpose his data are used
- how data are aggregated into profiles
- which decisions are made based on these profiles

###Privacy as Practice: Goals

- Focus on user awareness
- Data collection is made transparent
- how, why, which data are collected
- users can intervene in the collection and use of data
- Data processing is made transparent
- discover undesirable privacy practices of organizations

###P3P:Platform for Privacy Perferences
- Allow websites to communicate their privacy policies
- Provides a standard XML format to encode privacy policies
- Help users understand privacy policies

NOTE: No enforcement!

###Transparency Tools

- Give users a better understanding of information flow, state and history
- Become aware of how they (and others) participate in the socio-technical system
- Verify whether their personal privacy level fits within the current working of the system
- How they can take actions to change their own behavior as well as teh socio-technical environment
- Tools
- Google dashboard: see which info is associated to your account
- Fackbook: view how others see your profile

###Privacy as Practice: Main characteristics
- Main objective is to support users in decision making
- Potential to uncover malicious behavior by organizations

##Summary
| | Control | Confidentiality | Practice |
| ---------------------------------------- | ---------------------------------------- | ---------------------------------------- | ---------------------------------------- |
| Privacy definition:who fills the term privacy with meaning? | Organization-centric | Techno-centric | User-centric |
| Data Lifecycle | Information usage | Information disclosure/collection | Transparency in data disclosure, collection and use |
| Trust/adversary model | Organization trusted, individual untrusted | Powerful threat model, rigorous security analysis | No threat model |
Due to import from GitBook directly, the structure is not well organized.
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