Personal data collection has increased quickly. Businesses and governments utilize it to build profiles of individuals, predict their behaviors and attitudes, influence them, and tailor services and experiences based on them. It may lead to personalized experiences and more efficient use of resources; it could even result in misinformation or exploitation by either those collecting it themselves, purchasing it illegally from others, stealing it themselves, or by cybercriminals attempting to access and abuse it for personal gain.
Legislation to safeguard consumer data has been put forth due to increasing cybercrime while costs associated with protecting consumer data are growing for organizations trading personal information - risking misuse by hackers is rising with costs rising costs associated with protecting consumer data being misused.
Blockchain And AI Enable Personal Data Privacy
This chapter delves into how artificial Intelligence and blockchain provide solutions to secure personal data for individuals. Users control what information is shared with whom and when, and can even reduce cyber threats. Furthermore, artificial Intelligence helps enhance blockchain privacy systems so users can manage data better while assuring accurate models derived from that data are created more fairly and accurately than before.
Privacy Of Personal Data
Privacy of personal data is of utmost concern for developers and users alike. Personally identifiable data collected about clients, employees, prospects, and other stakeholders could potentially be collected regularly and stored in shared ledgers; passwords or private information about stakeholders could even remain identifiable unless security processes have been built into data management systems; given frequent cybersecurity incidents and increased regulations, the protection of PPI has now become an imperative for many companies.
Data linked to an individual, such as biometric information or phone numbers, can be considered Personally Identifiable Information. Geolocation data also falls within this classification category, as can data such as birth dates and postal codes, as well as behavioral traits of current customers, employees, or other stakeholders collected and stored by organizations.
Privacy And Cyber Security Breaches
Governments and companies alike have an increasing concern with cybersecurity. One component of cybersecurity, information security, protects data integrity and privacy as it's collected, stored, used, or processed. People, technologies, and data-associated processes create and uphold these safeguards.
Privacy breaches continue to rise despite advances in software and security protocols, according to the Data Breach report, which indicated "37 billion records compromised - this represents 141% growth!" These breaches frequently compromise users' records such as addresses, dates of birth, financial details, email addresses, and names; data breach victims could suffer severe repercussions as their records could include addresses, dates of birth, financial details, etc.
Unauthorized access to databases enables cyber-hackers to gain unauthorized entry and steal sensitive personal data like credit card numbers and passwords as well as social security numbers or banking details, often with damaging outcomes like credit card fraud and identity theft that takes months or even years to repair [2, 3, 4]. One notable breach that affected billions was Yahoo's database breach, which may have been state-sponsored: hackers collected names, email addresses, phone numbers, and dates-of-birth password hashes and answered security questions[3.
Equifax was the victim of a cyberattack that affected an estimated 143,000,000 consumers. Still, system administrators were unaware of suspicious activity for over two months before notifying authorities until one month post-incident discovery. Equifax may have been compromised via state-sponsored Chinese hackers [3], with unknown impact for victims individually and security or strategic damages sustained by China itself; nonetheless, these cases highlight the inherent risk of keeping sensitive personal information stored in centralized databases.
Government and corporate entities essentially control and store most collected and stored data, amassing vast volumes about individuals they must protect. Furthermore, these organizations monetize their datasets either for internal use, improving operations and services, or selling them; data volumes continue to expand exponentially, and this expands user footprint significantly; data consolidators allow connecting elements across various data sources in novel ways and consolidating it all together in new forms.
It can be used to estimate costs associated with creating databases. Statista, an analytics firm conducting statistical research and following cybersecurity trends, recently reported that incidents have increased over recent years, particularly over the recent five. This reaffirms the necessity of improving data security - perhaps one cyber attack thought committed by Russia may bring this figure up further when the exposed records are considered; at the time of publishing; however, its extent still needs to be investigated thoroughly.
Read More: Artificial Intelligence And Blockchain: Trending Intersection
Privacy Regulations
In many nations, privacy has long been considered a fundamental human right. This right can extend to controlling personal data, which affects the relationships and identities of data owners.
Regulations surrounding the collection and management of personal data are rapidly progressing, the European Union passed the General Data Protection Regulation, or GDPR - an innovative privacy legislation. Under its provisions, organizations that collect the personal information of EU citizens to conduct business transactions within these member states must protect this data by complying with data protection law requirements.
GDPR was adopted into US law through California Privacy Rights Act (CPRA), an extension to California Consumer Privacy(CCPA). Californians enjoy several rights under CPPR:
- Know what data about you is collected
- Know whether the product is sold, disclosed to whom, and for what purpose
- Refusing to sell their data
- You can access your data
- Requesting that an organization deletes any data about you
- Not to be mistreated for exercising your privacy rights.
Maria Cantwell, a Democratic Senator from Washington state, proposed the Consumer Online Privacy Rights Act. However, its fate is yet to be decided; previous federal privacy bills had failed before this. Meanwhile, government initiatives continue to push for stricter data protection regulations.
Privacy laws will have an immense effect on businesses that collect consumer data. Businesses collecting this consumer data must implement operations and system practices to adhere to privacy legislation and comply with existing or upcoming privacy regulations regarding data privacy and personal property ownership. Blockchain and Distributed Ledger Technologies make an excellent way for firms to comply with current or pending privacy legislation relating to consumer privacy or ownership issues.
Cryptography And Privacy
Blockchain solutions allow organizations to collaborate more efficiently, improve operational efficiencies, and boost revenue growth. However, privacy risks arise because multiple blockchain participants could access shared ledger data.
A blockchain solutions provider, asserts when discussing privacy that "privacy isn't a feature of any blockchain; multiple layers can be added for complete protection. When designing their blockchain solution, designers must carefully consider which parties have permission to read/write transactions and storage methods, including broadcast and validation processes; enforce and update security/permission systems accordingly and decide how their data ownership might be distributed.
Decentralized Identity
Blockchain, self-sovereignty should allow individuals the power and autonomy over how their identities are shared with others. Decentralized Identity (DID), one manifestation of self-sovereignty enabled by blockchain, can increase privacy and security.
DID stands for Digital Identity Document, or digital personal data, which relates to aspects of one's identity and belongs solely to them. Microsoft takes into consideration individuals when setting standards for DID. When setting these standards, Microsoft considers this and takes their perspective when setting DID standards.
Anyone can create an electronic identification (DID) number; initially, it does not contain any data; over time, it might become associated with a driver's license or some other document. A third party could then use similar techniques to validate who owns their DID identity as they would for verifying ownership of email accounts - for instance, an online game account could use email to connect itself directly to its password holder's DID number for verification.
Unlike email accounts, DIDs would belong solely and securely stored by its owner rather than being managed by email providers. Owners would also be responsible for protecting passwords or private keys themselves. Identity hubs provide encrypted storage outside the blockchain, including smartphones, PCs, cloud storage accounts, or offline devices. They allow individuals to control how their information is shared using one such hub.
DIDs help prevent correlation problems created by using standard identifiers across websites - like email addresses. Correlation refers to entities' ability, without user consent, to link information from multiple systems with one identity - for instance, most websites store user data using email addresses as storage units. Users who provide their email addresses on multiple websites, together with personal details like phone numbers or physical addresses, unwittingly expose themselves to correlation by entities, who can then correlate data across sites using tracking cookies and clicks, thus giving outsiders an in-depth picture of users based on identity, gender, age, interest, etc.
Blockchain-Enabled Federated Identities
DIDs enable users to protect and safeguard their data and decide who has access. Decentralized identities also increase blockchains' security when used across various internet platforms or services, giving the user more peace of mind when interacting with these services.
Blockchain allows entities to protect users' privacy, an essential feature for self-sovereign identities. Users enrolled across multiple systems or sets of them have what is known as "federated identities." SSO allows users to utilize services and platforms provided by different parties by authenticating one identity. SSO user authentication allows only seamless use across platforms and services provided. Imagine an entire network of health care providers, including multiple organizations like hospitals, insurance providers, and urgent care clinics, which allow their users to log on using single sign-on credentials or federated digital identities - yet the security of such credentials is compromised due to being stored centralized with service providers.
Blockchain's decentralized nature enables networks to provide single sign-on or federated identity more securely. A blockchain federated identities framework where providers manage their systems and identify users instead of depending on a central third party is proposed; any entity can verify credentials before issuing identity cards to users utilizing its secure, immutable, unalterable properties for verification and issue. A BFID takes full advantage of the blockchain's secure, immutable, unalterable properties.
Frameworks for federated identities that use blockchain can be implemented privately and publicly, using smart contracts to respond to any changes to rules within an environment. Furthermore, such frameworks enable users to monitor how their identity is utilized and allow network businesses to gain insight into which services users are making the most out of.
Proofs Of Zero Knowledge
Zero-knowledge methods provide convenient access to personal information while protecting privacy and control over property. A zero-knowledge method is a cryptographic technique that enables one person to persuade another, known as their "verifier," that they say something without providing that information voluntarily - for instance, when ordering alcoholic beverages at bars that demand proof of age by showing drivers licenses as proof containing the full date of birth, height, eye color and address details that could potentially be exploited and stolen by criminals.
Zero-knowledge proof uses cryptographic algorithms that permit proponents of any statement mathematically to demonstrate to its verifier that this statement is true without divulging any details of their statement or their verifier's information. In practice, drivers 21 and over may provide their license number and an unknown nickname when applying for a driver's license - both will then be hashed together and stored as valid drivers above 21 by state authorities on lists compiled of valid drivers over 21. When entering their information at bars, they could combine both elements into generators to ensure they knew if the legal age had been reached or otherwise!
Interactive and non-interactive proofs of zero knowledge exist. Zero-knowledge protocols tend to be interactive, where both the prover and verifier (usually humans or computers) exchange questions and challenges with one another.
An example of Interactive Proof of Zero Knowledge using Two identical colored balls can be an ideal demonstration. Assume the verifier cannot distinguish the colors between the balls; and wants to prove both balls have distinct colors by showing it, asking which it was, showing another ball again while they indicate its color change, repeating this cycle until finally asking whether you had switched your balls - when looking closely you will easily be able to tell when one has switched because its different hues become apparent to all observers, so guessing correctly becomes almost nonexistent after repeated rounds!
Zero-knowledge proofs can be an excellent way of protecting privacy and managing property for those who may need to share some personal data but only as necessary.
Read More: Blockchain Revolutionizing Banks For Efficiency And Security
Artificial Intelligence And Privacy
Artificial Intelligence, also called cognitive computing and machine learning, refers to computers being programmed to emulate human cognitive processes such as learning, problem-solving, and reasoning more efficiently and accurately than humans [14]. AI applications span various areas, such as medical diagnosis, financial forecasts, disease tracking systems, and speech/facial recognition software systems, allowing computing systems to make rational decisions toward reaching specific goals.
AI can increase user and stakeholder safety through tools that use blockchain technology to provide new ways of accessing and learning without controlling or owning the data, protecting organizations and stakeholders who provide it from risks. Blockchain processes and networks may benefit by quickly adding privacy-related AI functions - something which would benefit individual participants and groups responsible for setting governance rules and procedures.
Companies have implemented AI technology to gain a comprehensive view of their customers. This can be accomplished by merging all transactions across customer touchpoints into integrated datasets on blockchain partners; participants in such networks are then rewarded for pulling these together into integrated datasets that create integrated datasets from customer accounts across several chains; however, this practice could potentially affect customers and stakeholders privacy as a whole.
AI can combine with decentralization options that protect identity from combining blockchain participants' and their stakeholders' data to maintain information security while keeping privacy intact, thus increasing user and stakeholder safety and expanding data sets and AI models.
An organization's implementation of its data transparency and privacy process may affect four distinct stakeholder groups: 1) participants from whom data is directly or indirectly collected; 2) victims impacted by decisions taken using participant data; 3) users working with participant data and 4) custodians responsible for protecting it. All stakeholders will gain when AI technology is employed to secure access and create analytical models from this data [15].
Computational intelligence (CI), one subfield of AI, can increase Blockchain resilience against attack, thus improving both security and privacy for data stored there. Traditional brutal computing methods AI uses cannot adapt quickly enough to changing variables; conversely, CI uses soft computing techniques to adapt swiftly.
Combining computational Intelligence and blockchain can produce more secure cryptography and ciphers that make it harder for hackers to compromise systems as computing power increases and attempts at hacking increase over time. The intersection between blockchain and AI is known as "blockchain Intelligence. Furthermore, AI algorithms may also be implemented on blockchains to monitor blocks and activities to detect attacks against them; further strengthening trust beyond what its native architecture provides.
AI datasets collection purposes - especially from those collecting from participants before collecting personal data about them may become standard practice among companies looking at this step before collecting personal data about participants rather than opt-out as users themselves can opt-in rather than opt-out when collecting participant personal data may come in exchange. Depending on who receives personal data, companies wishing to make traditional or AI decisions with it companies wanting to use this personal data may compensate. However, so-called decentralized identity solutions become standard practice.
Users are more frequently compensated as companies use personal data collected about them to make traditional or AI decisions made with it by companies seeking data that needs it for decision-making processes or AI decision-based decision-based on these participant's data collected themselves from them when giving it for decision making using it when giving it for such decisions made by companies interested in giving companies needing data used from participants for creating AI data to make conventional or AI decisions using it!
Smart contracts provide users with the capability of protecting their privacy with complex rules-driven contracts that enable users to grant and revoke permission based on smart contract logic. Artificial Intelligence scans contracts for participants who might possess data or provide it to desired users.
Blockchain ledgers provide organizations with more precise and cleaner data collection. Since they feature validation, timestamped entries, and append-only capabilities, data gathered and stored will be more precise and clean than conventional databases that don't permit changes once entered.
Model developers and users will gain greater assurance in the ethical quality of their data and compliance with regulations. Multidimensional permissions can be granted and documented--even enforced via smart contracts--so organizations can utilize this data with reduced risks of privacy breaches. As user data collection occurs without knowledge, complex analyses requiring user data collection can occur without needing to access personally identifiable information (PII).
Smart contracts can help enforce usage agreements and ensure no personally identifiable information (PII) is ever collected, thus providing more ethical data management and collection practices. AI models using ethically collected data that adhere to ethical standards may produce results within acceptable ethical and regulatory boundaries.
Use Cases For Blockchain And Ai In Emerging Industries
Researchers and technologists are investigating ways of quickly gathering information on viral transmission and exposure to combat the Covid 19 Pandemic while protecting user privacy. Rapid testing using point-of-care diagnosis on those suspected to have been infected is an efficient and cost-effective method to monitor virus spread and limit its effects. Pharmacy AG in Germany has created its Covid 19 rapid test, which delivers results within 20 minutes for point-of-care testing on potential infection cases. This test can be integrated with point-of-care systems using blockchain and AI for faster diagnosis while providing statistics regarding positive and negative results while keeping user information private and safe. Blockchain can collect data quickly while AI expedites this process to form a unified platform to analyze disparate sources of information, offering critical Intelligence that could combat diseases spread quickly by human hosts, ease care provider workload, and ultimately save lives.
Blockchain technology can be seamlessly woven into innovative home systems to maintain privacy while collecting usage data for analysis. As manufacturers make devices increasingly connected to each other, smart home systems have become popular, providing valuable consumer behavior data.
AI-enabled blockchain systems enable users to send machine learning processes directly onto mobile phones as consumers train locally on smartphones or servers located near consumers - users then submit locally trained models for further examination or add noise so that it becomes hard for others to track shared information back to individuals if shared data becomes public knowledge; additionally, decentralized technologies allow analysis without sending information directly back out central servers - helping manufacturers increase connectivity among devices while collecting valuable consumer behavioral information that provides valuable consumer behavior data on consumer behavior data from individual consumers themselves as a result. Decentralized technologies also allow local data analysis without sending it to centralized servers like those found elsewhere (i.e., from devices connected by connecting all sorts of ways).
Last Thought
This article describes several AI applications within a blockchain environment to increase or protect users' personal data privacy. Together AI and blockchain provide increased system security; increase user security via smart contracts/permissions sharing; allow for identity enhancement services/privacy-enhanced uses; while at the same time increasing AI models by including more diverse, ethical data; as well as improving AI models through more diverse, ethical data usage patterns.
