#decentralized database

What becomes of encryption today when quantum computers are capable of cracking it? As we race toward a future driven by the next generation of technology, one urgent question hangs over cybersecurity. The solution is to use Post Quantum Security, a new generation of cryptography capable of resisting the brute power of quantum computing.

In a world where sensitive information — from personal identities to national secrets — is increasingly vulnerable, Post Quantum Security is not just an upgrade, but a necessity. This article explores how to future-proof your data and systems against quantum threats.

Understanding the Quantum Threat Landscape

The Birth of Quantum Computing

Quantum computing seems to quickly evolve from a new scientific theory into a change- and results-driven technology. Old computers use the binary digit as 0 or 1, whereas quantum computers operate using qubits, which can occupy several states simultaneously owing to superposition and entanglement. As a result, such cutting-edge machines provide an exceptional ability for quick, advanced computations.

Quantum computing excels using its capability of handling large data volumes and solving issues too complicated for existing best classical supercomputers. In particular, quantum computers can effectively address complex logistics tasks, analyze the structure of molecules to invent new medicines, and enhance the approach undertaken in financial forecasting.

But with that potential comes a warning: quantum computing puts modern cryptographic systems at serious risk. The same computational benefits that make quantum computers a breakthrough for scientific research are the ability to compromise classical encryption methods used in our online security.

Implications for Current Cryptography

The dominant modalities of the modern digital infrastructure are based on the use of public key cryptography, and such systems as RSA and ECC are among the most widespread representations that people use. These encryption systems are based on mathematically difficult problems for conventional systems — factorizing huge numbers or solving discrete logarithm problems. These are exactly the sorts of problems a quantum computer is designed to demolish with impunity using expert algorithms.

Shor’s Algorithm, created in 1994, is likely the most famous quantum algorithm that targets RSA and ECC directly. It can factor big numbers exponentially quicker than the best-known classical algorithms. When quantum computers are ready — usually called “quantum supremacy” — they will be able to decrypt secure communications, financial transactions, and private information that are now thought to be secure.

Another significant algorithm, Grover’s Algorithm, doesn’t shatter symmetric crypto systems but narrows down their security levels significantly. It indeed cuts a symmetric key’s bits in half, so 256-bit keys would provide only 128-bit security in the quantum age. Less devastating than Shor’s impact on asymmetric crypto, though, Grover’s Algorithm does mean a reconsideration of the dominant symmetric encryption algorithms.

This new threat brings to the forefront the need for post quantum security solutions in an immediate manner. Unlike conventional cryptographic practices, post quantum security is about designing and deploying algorithms that are secure even when quantum computing resources are available. These algorithms are based on challenging mathematical problems for which quantum computers are not yet known to solve efficiently.

The Urgency for Transition

Post quantum security is not a theoretical concept; it’s an urgent, real-life issue. RSA- or ECC-breaking large-scale quantum computers don’t exist yet, but breakthroughs are on the move. The collaborative efforts of governments, corporations, and research bodies across the globe to create quantum technology imply that these machines will soon become real.

There is a dire need to secure the digital infrastructure of organizations, for when quantum technology is available. Transitioning to post quantum security protocols is difficult and time-consuming, not only swapping cryptographic algorithms but also rewriting software, hardware, and communication protocols. Waiting for fully functional quantum computers may expose systems and data to attacks.

Further, hacked encrypted data today can be stored and decoded at a later date after computers develop the capability — the “harvest now, decrypt later” attack. As a countermeasure post quantum security ensures valuable information is safeguarded both today and in the foreseeable future.

The U.S. National Institute of Standards and Technology (NIST) has already started standardizing quantum-resistant algorithms with its Post-Quantum Cryptography Standardization Project. Organizations can standardize their security approach with international best practices for post quantum security using NIST-recommended solutions.

What Is Post Quantum Security?

Post Quantum Security is a term that is used to refer to cryptographic methods that are resistant to attacks carried out by entities that can run large quantum computers. Besides, this category includes the quantum-resistant hash algorithms, encryption algorithms, and digital signature algorithms. These systems are being standardized by efforts such as NIST’s Post-Quantum Cryptography Project.

Embracing Post Quantum Security guarantees that long-lived sensitive information, such as medical records or financial contracts, is still protected even when intercepted today and decrypted in the future quantum world.

ncog.earth incorporates Post Quantum Security into its core blockchain protocol. It provides data security for decades in a post-quantum secure environment.

Core Principles of Post Quantum Security

Below are the fundamental principles that constitute this new field and how they interact with each other to protect digital property during the era of quantum computing.

1. Quantum-Resistant Algorithms

Post quantum security is centered around quantum-resistant algorithms, which are designed to stand up to attacks both from traditional attack methodologies as well as attacks performed with a quantum computer. These algorithms don’t depend on the weak assumptions of the classical encryption methods like RSA or ECC, which can be attacked and broken by quantum algorithms like Shor. Post quantum security instead depends on mathematical problems with cryptographically amicable properties that are difficult for an efficient quantum computer to solve.

Among the most promising quantum-resistant solutions are-

Lattice-based cryptography: Lattice-based cryptosystems rely on the computational subtlety of such problems as the Shortest Vector Problem (SVP) and the Learning With Errors (LWE) problem. They are classical and quantum resistant and thus well positioned to protect encryption, digital signatures, and key exchanges.

Hash-based cryptography: Founded on extensively studied hash functions, this method effectively generates secure digital signatures. Because hash functions are one-way functions, they are extremely secure even against quantum attackers.

Code-based cryptography: Founded on error-correcting codes, this method has stood the test of time for more than four decades. It is strong, well-established, and extremely efficient for encryption and digital signatures in a post quantum security scenario.

Multivariate polynomial cryptography: The hardness of these problems is essentially dependent on the intricacies of solving multivariate quadratic systems of equations, which are intractable for quantum and classical systems.

Deployment and selection of these algorithms are being standardized by bodies such as NIST, which is finalizing a suite of post-quantum cryptographic standards for ease of global implementation of post quantum security protocols.

2. Forward Secrecy

Forward secrecy is yet another significant post quantum security parameter. In the conventional crypto paradigm, it might be possible that breaking a private key today can expose attackers to decrypted communications in the past and future, and it is highly risky if, in a quantum paradigm where harvested encrypted data from today can be broken using quantum computers in the future.

Post quantum security addresses this issue by guaranteeing that even when an encryption key is finally breached, past messages cannot be decoded after the fact. The method is to repeatedly generate ephemeral keys that don’t survive and aren’t easily linked up with each other. Forward secrecy is significant not just for private individuals but for protecting business networks, government files, and money networks as well.

Essentially, forward secrecy reconfigures the way we approach long-term data secrecy, particularly considering the danger represented by “harvest now, decrypt later” attacks facilitated by quantum advancements. In post quantum security, it’s a solid pillar of real future-proofing.

3. Hybrid Cryptographic Models

With the indefinite time frame of quantum progress, most organizations are taking a hybrid approach that brings together classical and post-quantum-resistant cryptography. The cryptographic models are created to fill the security gap during the transition phase when the existing traditional algorithms exist side by side with the post quantum security algorithms.

In a hybrid method, two sets of algorithms are run in parallel. One set offers backwards compatibility with current infrastructures, and the other offers immunity to future quantum attacks. As a simple example, an end-to-end communication channel could employ RSA in conjunction with a lattice-based encryption scheme at the same time. This means that even if the classical part is compromised in the future, the post quantum security layer still protects the underlying data.

This method has some advantages-

Gradual roll-out: Businesses can deploy systems gradually without affecting current services.

Redundancy: Having several levels of encryption offers a backup in case one algorithm is compromised.

Testing ground: Testing the deployment of quantum-resilient tools identifies real-world problems and solutions before mass deployment.

Hybrid deployments are not long-term, but they are essential stepping stones. With increasing trust and confidence in post quantum security technology, hybrid deployments will ultimately make way for fully quantum-resistant architectures.

Why Businesses Must Act Now

In the unfolding digital age, while cyberattacks increase in scale and sophistication, quantum computing’s emergence is at once a dazzling technological advancement and an intrinsic cybersecurity challenge. To companies — particularly those holding sensitive customer data or conducting business in highly regulated industries — the time to prepare is not in the future but today. Post-quantum security is no longer an idealistic aspiration but rather a concrete reality. Forward-thinking companies need to take action today to ensure that they will be able to withstand future cryptographic shocks.

Quantum Threats Are Nearer Than They Seem

The power of quantum computers is that they can use superposition and entanglement to exceed classical machines in certain forms of mathematical operations. The possible advantages that such technology could offer to drug discovery and logistics, as well as machine learning, are substantial, but this danger also undermines the encryption protection that enshrines secure digital communication, financial systems, medical records, and contracts.

Algorithms such as RSA and ECC, the basis of modern public-key cryptography, could be made obsolete by quantum algorithms such as Shor’s. In practical terms, what that would mean is to make information currently encrypted under these systems decrypted within seconds if there existed a sufficiently large quantum computer. The potential effect would be disastrous to companies experiencing huge-scale data breaches, litigations, and erosion of customer confidence.

That’s why post quantum security must be implemented far ahead of the wholesale arrival of quantum computing. Companies that delay are not only taking a risk — they’re deliberately putting their businesses, data, and reputations in long-term jeopardy.

Data Longevity Brings the Risk into the Present

One of the least considered measures of quantum risk is data longevity concern. Whereas real-time data spoils at a fast pace, some forms of data — medical history, legal papers, government agreements, and intellectual property — are priceless for decades or years. If today a cyberattacker got hold of encrypted information, they would be unable to decipher it. But with the advent of quantum power, the same information can be accessed in the foreseeable future. The label is also applicable when talking about attacks referred to as “harvest now, decrypt later”.

On this front, post quantum security plays a twofold role: it safeguards against the threat at hand, but also against potential attempts to decrypt in the future. For businesses tasked with securing data over the long term — insurance providers, banks, and law firms, for example — it is critical that it is pre-emptive. Delaying the implementation of quantum-resistant practices creates a bombshell situation where encrypted files stored could be cracked open at any moment.

Consumer confidence is perhaps the most precious asset of the online marketplace. With high-profile breaches becoming the norm, customers are growing more attuned to where their information lives and how it is secured. Companies that act early to publish quantum security standards communicate that they are serious about leading-edge data protection and customer privacy. This method contributes to the creation and preservation of a reliable brand and earns the loyalty of the clients.

Additionally, regulatory landscapes are changing. Global data privacy legislation like the GDPR, HIPAA, and CCPA demands secure data security procedures, and compliance systems will shortly be following close behind in counteracting quantum-age attacks. Adopting post quantum security today allows organizations to protect themselves against future compliance mandates and sidestep the prohibitively cost-intensive exercise of currency flows.

Smooth Transition Through Strategic Planning

Post quantum migration is not a flip-of-the-switch transition — it requires thoughtful planning, testing, and staged deployment. Businesses must assess their existing cryptographic infrastructure, identify vulnerable endpoints, and decide which quantum-resistant algorithms will best meet their operational needs.

Fortunately, most businesses are not beginning from the ground up. Hybrid crypto designs — blends of conventional and quantum-resistant solutions — permit phased and secure adoption. Post quantum security is viable through hybrid approaches that support organizations in adopting post quantum security without sacrificing current system performance or compatibility. Phase by phase is the way, causing as little disruption as possible while providing security for important information at each stage.

They also must spend on training and awareness programs. Decision-makers, developers, and cybersecurity staff must be made aware of the effects of quantum risk and the pragmatic actions that go into minimizing it. Post quantum security incorporated into cybersecurity roadmaps now will have companies not lag when the quantum era is in full force.

Building Quantum-Resilient Ecosystems

The truth is, cybersecurity is not an isolated practice. A majority of businesses employ third-party suppliers, cloud computing providers, and digital platforms that touch or have access to sensitive information. Having a secure digital environment is a matter of discussing post quantum security with partners and suppliers.

Leading organizations are now starting to measure their supply chains and expect quantum-readiness from their partners. Organizations can minimize systemic vulnerabilities and foster increased collective resilience by establishing post-quantum security as an expectation within ecosystems.

Integrating Post Quantum Security into Your Infrastructure

With continued advances in quantum computing, the danger that it poses to classical cryptographic schemes is more dire. Companies and enterprises cannot afford to wait. There is a need for a transparent and systematic adoption of post quantum security protocols into existing IT infrastructures so that data confidentiality, integrity, and availability are preserved under quantum computing. This has to be done with a strategic roadmap of action covering technology and operations transformation across the digital landscape.

For this transition to be made possible, organizations can utilize a multi-step process that will establish quantum resilience without disrupting essential services. Below, we outline the four main steps of incorporating post-quantum security in your infrastructure.

Audit Your Current Cryptographic Inventory

Before any change is implemented by companies, they must start by defining the scope and utilization of current cryptographic assets. Any effective post quantum security project is based on a thorough cryptographic inventory. This process entails determining where and how cryptographic algorithms are utilized — on SSL/TLS certificates, database encryption, secure email, authentication protocols, digital signatures, API gateways, mobile applications, VPNs, and IoT devices.

This audit must encompass-

Encryption Algorithms Used: Assess if systems are using RSA, ECC, or other vulnerable algorithm-based encryption.

Key Sizes and Expiration Policies: Document existing key sizes and assess how often they are being replaced.

Cryptographic Libraries and APIs: Check for dependencies and assess compatibility with quantum-resistant alternatives.

Certificate Authorities and Issuance Policies: Examine methods of distributing, retaining, and withdrawing digital certificates.

When such data is analyzed, it is possible to identify weak points and establish priorities for strategic transition to post-quantum security. Notably, the process helps organizations to review the data lifecycle and determine long-term sensitive data that needs to be secured today against tomorrow’s quantum decryption power.

Select Quantum-Resistant Algorithms

After identifying your cryptographic footprint, the next step is to select quantum-resistant alternatives. NIST has worked with others to initiate multi-year standardization efforts that will evaluate and promote post-quantum cryptography algorithm recommendations. These algorithms are designed so that they can resist attack by both classical and quantum computers and include key encapsulation processes and digital signature protocols.

Among the most promising contributions to come out of the NIST project are-

CRYSTALS-Kyber (for public-key cryptography and KEM)

CRYSTALS-Dilithium (for digital signatures)

FALCON and SPHINCS+ (signature schemes with performance profiles of differing types)

In choosing algorithms, implementations must consider performance, resource efficiency, complexity to implement, and the extent to which the solution they choose fits their infrastructure. For instance, IoT devices that have little power may need lightweight algorithms, but high performance servers are more than capable of handling complex computing activities.

Selection of the best algorithms is immensely important for effective post quantum security integration. Future-proofing should also be a consideration for security teams as quantum-resistant cryptography develops. Modular architecture solutions for cryptography allow for a seamless switch or upgrade of algorithms as new standards become available.

Use Hybrid Cryptographic Systems

It is not necessary to move away from classical to quantum-resistant cryptography completely. One of the most recommended practices while transitioning to post quantum security is the use of hybrid cryptographic systems. These use current (classical) cryptographic algorithms and couple them with quantum-safe algorithms to provide a multi-layered defense.

In a hybrid system, data is encrypted with both RSA (or ECC) and a quantum-resistant algorithm. It makes the system both backward compatible as well as future-proof against attacks based on quantum. Although quantum computers are unable to break today’s classical encryption now, hybrid encryption protects the data from being exposed in the future, most beneficial for long-shelf-life sensitive data.

Hybrid deployments also enable companies to pilot the in-the-wild usage of post-quantum-safe algorithms without removing trusted current defenses. Phase-in of post quantum security in this manner prevents service disruption, lowers operational risk, and enables incremental testing and tightening.

Key libraries and frameworks increasingly start to include hybrid support. For example-

OpenSSL (with quantum-safe branches)

Cloudflare and Amazon Web Services, which have begun to experiment with post-quantum TLS deployments

Mozilla and Google, pioneering early hybrid deployments in their browsers

These initial hybrid adoption attempts show the growing traction for post-quantum security and offer in-the-wild blueprints for companies willing to make the transition.

Upgrade Key Management Systems (KMS)

What if the computer of the future could help alleviate some of the problems facing us today in seconds? It would take a traditional computer millions of years. That is what quantum computing promises to deliver: a revolution that can revolutionize all the sectors it comes into contact with. From science and medicine to finance and cybersecurity, quantum computing is spearheading the next technology revolution.

This article explores the fundamentals, current progress, and real-world applications of this innovation. We’ll uncover how it’s changing the rules of computation and setting the stage for a faster, smarter, and more efficient future.

Understanding Quantum Computing

Scientists have rebranded how computers calculate information by producing qubits, unbound by the binary constraints of traditional bits. Unlike traditional bits, which are 0 or 1, qubits can appear everywhere in a quantum superposition due to superposition and entanglement. This allows machines to solve several calculations at once, not one after the other, significantly heightening their ability to solve certain problems.

By superposition, the engineers enable a qubit to hold more than one state. By entanglement, they connect qubits in a way that a manipulation of one immediately affects the rest no matter where they are physically located. These operations permit quantum computing-based systems to be superior to classical systems in cryptography, molecular modeling, and optimization of data. As researchers improve the stability of qubits and system precision, they are bringing us closer to a solution deemed intractable.

The Evolution of Quantum Computing

Back in the early 1980s, physicists such as Richard Feynman talked about using quantum mechanics for computing. It took scientists several decades to work on the idea, but the technology was not ready yet to make it a reality. During the 21st century, scientists and engineers started surmounting such challenges by improving quantum hardware, sophisticated algorithms, and superior error correction methods.

In the past two years, companies such as IBM, Google, Intel, Rigetti and IonQ have invested a lot in creating reliable and large quantum machines. In 2019, Google achieved quantum supremacy when its machine solved an exact problem in just three minutes, while the fastest standard computer would have taken many days to do this.

Today, this rivalry continues intensifying with groups pushing the limits of innovation. What they do lays the foundation for a future when quantum computing upends areas such as cryptography, optimization, and materials science.

Quantum Computers in Practice

Quantum computers are starting to surpass themselves in real, applied applications in numerous sectors. In medicine, they are utilized by researchers to model and simulate intricate molecular interactions, which accelerate the discovery of new drugs and decrease costs of development. Crunching computations, slowing down traditional machines, quantum computers enable scientists to simulate compounds virtually before proceeding to actual experiments.

Logistics engineers use quantum-inspired techniques to tackle routing optimization, inventory optimization, and supply chain optimization. These systems are efficient at solving complex combinatorial problems at unparalleled speeds, enabling firms to save time and money.

Quantum algorithms are employed by financial companies to better model risk scenarios and identify fraud more appropriately. These innovations assist decision-making and possess a greater security feature.

Data scientists also incorporate quantum systems in machine learning pipelines, which reduces the time to train large models. Meteorologists look forward to more accurate weather predictions by more accurately modeling atmospheric systems. Cryptography and materials science advances also continue.

With quantum computing continuing to advance at a tremendous pace, its application is beginning to leave theory behind and head towards transformational uses. With more organizations turning to technology, quantum computers will help solve some of the globe’s most complicated and most critical challenges.

Quantum Algorithms: Solving the Unsolvable

Quantum algorithms propel the transformative potential of computation to be. Computer scientists and mathematicians created the algorithms to bypass challenges that in essence are insurmountable for traditional systems. Shor’s algorithm, for instance, breaks large numbers exponentially more quickly than any standard process — a development that threatens modern-day encryption standards. Security professionals everywhere now reassess cryptography systems in preparation for such disruptive capacity.

Grover’s algorithm optimizes searching by greatly decreasing the amount of time needed to find a particular item within unordered databases. Rather than going through each entry individually, Grover’s algorithm enables users to learn outcomes with considerably fewer steps, providing a quadratic speedup.

In contrast to conventional algorithms that simulate existing computing paradigms, quantum algorithms rework problem-solving solutions altogether. They function on new foundations of principles, using entanglement and superposition to produce outcomes that are outside classical bounds. Designers must now work on creating new logic and architecture that leverages this style of computing.

Ang mga teknolohiya ng Artipisyal na Katalinuhan (AI) ay kumalat upang baguhin ang maraming aspeto ng awtomasyon, pagproseso ng datos, paggawa ng desisyon, at mga pamamaraan ng paglutas ng problema. Ang pagpapatupad ng AI ay nagpalakas ng maraming industriya sa pamamagitan ng kakayahang gumawa ng mga nakaakmang mungkahi at agarang mga sistema ng pagtuklas ng pandaraya. Ang tumataas na antas ng pag-aalala ng publiko ay nagmumula sa mga pag-unlad ng AI sa iba’t ibang aspeto ng pang-araw-araw na buhay. Ang publiko ay nagpapahayag ng malawak na pag-aalala tungkol sa pagkawala ng trabaho at kontrol ng artipisyal na intelihensiya sa mga empleyadong tao pati na rin ang teknolohiya ng deepfake dahil madalas na lumalabas ang mga paksang ito sa mga nobelang science fiction at iba pang media. Ang publiko ay labis na nag-aalala tungkol sa pagkawala ng trabaho at ang kontrol ng artipisyal na intelihensiya sa mga empleyadong tao pati na rin ang teknolohiya ng deepfake dahil ang mga paksang ito ay madalas na lumalabas sa mga nobelang pang-agham na pantasya at iba pang media. Ang paglalarawan sa mga pelikulang pang-agham na pantasya ay karaniwang nagpapakita ng AI bilang isang sistemang may ultimate na dominasyon na kayang ganap na palitan ang mga tao.

Abstract: Artificial Intelligence (AI) is rapidly transforming industries, automating repetitive tasks, and introducing efficiencies that were previously unattainable. However, the acceleration of AI adoption raises societal concerns, including job displacement, ethical dilemmas, and potential misuse. This paper explores the dual nature of AI—its promises and perils—and proposes measures to ensure AI remains a beneficial tool without posing existential risks. Emphasis is placed on data security, responsible AI training, and the need for decentralized, encrypted data storage to prevent malicious exploitation.

 Keywords: Artificial Intelligence, quantum computer, Data Security, Decentralized Systems, Ethical AI, Post-Quantum Cryptography, Generative AI, Blockchain Technology. 

I. INTRODUCTION 

The proliferation of AI technologies has brought unprecedented advancements in automation, decision-making, and problem-solving. Yet, the same technologies evoke fears of job loss, societal disruption, and even existential threats to humanity. Popular media often dramatizes AI’s potential to dominate or replace humans, amplifying these concerns. This paper aims to distinguish between speculative fears and actionable risks, proposing a framework to ensure AI’s safe and ethical integration into society. 

II. PROBLEM STATEMENT

 The rapid adoption of AI-based solutions has raised concerns about job displacement and the potential for AI to become a threat to humanity. Many people believe that AI may capture the world and make humans their slaves. The speculation surrounding AI's ability to take over the world has been fueled by movies and media portrayals of AI-based robots and systems. While these innovations increase efficiency and reduce costs, they also introduce risks:

A. Job Displacement

 AI automates repetitive and time-consuming tasks, reducing demand for certain roles. 

B. Identity Fraud 

AI-generated avatars and voice cloning can impersonate individuals, enabling malicious actions. 

C. Weaponization Autonomous 

AI-powered robots can become tools for harm if fed malicious instructions. 

D. Data Exploitation

 Centralized data storage systems are vulnerable to breaches, enabling AI misuse.

 Speculations of AI gaining sentience and dominating humanity often overshadow these tangible risks, diverting focus from practical solutions. 

III. EXPLANATIONS 

Artificial intelligence is not a new technology that is taking over jobs and performing tasks smarter. It is an old technology that has been performing well for decades. AI-based systems are designed to perform tasks by making decisions based on the data or inputs they receive. The output of an AI-based system is determined by the input data and instructions provided to it. 

IV. THE DANGER OF AI 

AI-based systems can be proved to be dangerous if they are fed with malicious instructions or data. AI based robots and machines can learn on their own and perform actions that can harm humans and other animals. However, the data and instructions that these systems receive are provided by humans. Therefore, humans are responsible for any bad outcomes that may result from the use of AI-based systems. 

V. EXISTING AI CAPABILITIES AND CHALLENGES

AI has long existed as a tool for automating tasks and making data-driven decisions. Early systems, such as IBM Watson [1] and household assistants like Amazon Echo, showcased AI’s potential but faced barriers to mass adoption due to cost and accessibility. Recent advancements in generative AI have democratized access, with tools like ChatGPT [2], Claude, and Google Bard offering affordable, high-quality services. However, the rapid expansion of AI usage has surfaced critical challenges:

 A. Bias and Ethical Concerns 

Outputs are influenced by input data and prompts, risking biased or harmful responses. 

B. Security Vulnerabilities 

AI systems trained on centralized data are susceptible to breaches and misuse. 

C. Autonomous Learning 

Risks Self-learning robots and systems could act unpredictably if exposed to harmful inputs. 

VI. METHODOLOGY: SAFEGUARDING AI’S ROLE 

To safeguard humanity and data integrity, we need to secure our data and information. With security, AI-based systems will not be able to replicate our identity and harm people. Securing our data is the most important part of preventing the bad use of AI with our data and on us. We propose the use of postquantum security and decentralized data storage solutions to secure our data. To mitigate risks and establish AI as a "second-class citizen," the following measures are proposed: 

A. Data Security

 Decentralized, encrypted data storage using postquantum cryptography [3], as explored by projects like NCOG [4], is crucial. This empowers individuals with data ownership and prevents its misuse. Post-quantum cryptography standards must be adopted to counteract threats posed by quantum computing. 

B. Responsible Input Management 

AI output is directly dependent on input quality. Promoting responsible data input and mitigating malicious or biased training data is critical for ensuring ethical and safe AI applications. 

VII. QUANTUM COMPUTING THREAT 

The advent of quantum computing poses a significant threat to existing cryptographic systems. Quantum computers have the potential to break widely used encryption algorithms, exposing sensitive data. This vulnerability underscores the urgency of transitioning to post-quantum cryptography, which is designed to withstand attacks from quantum computers. The harvesting of data today with the intent of decrypting it later with quantum computers is a serious concern. 

Fig 1. Illustrates a basic AI system 

VIII. RESULTS AND DISCUSSION 

Figure 1 illustrates a simplified AI-based system model, showcasing how input data and feedback loops influence output. The system’s behavior is dictated by the quality of input, underscoring the importance of responsible training and data management. Love, peace and kindness as input will give a similar output from the system rather than the abusive outputs. When AI systems operate on encrypted, decentralized data, their ability to harm is significantly reduced. For instance, a decentralized AI system cannot impersonate an individual without access to their private data. Moreover, post quantum secure data storage mitigates risks associated with quantum computing’s potential to breach traditional encryption. 

IX. CONCLUSION 

Artificial Intelligence holds immense potential to improve lives and revolutionize industries. However, its benefits must be harnessed responsibly to avoid unintended consequences. By prioritizing data security, especially through post-quantum cryptography, and promoting responsible data input, we can ensure AI remains a valuable tool while safeguarding humanity and preventing its misuse. Establishing AI as a "second-class citizen" a tool under human control—is essential to maintaining its alignment with societal values.

REFERENCES :

[1] IBM Watson. "Artificial Intelligence Solutions." IBM Corporation. 

[2] OpenAI. "ChatGPT: Generative Pre-trained Transformer." OpenAI Inc. 

[3] National Institute of Standards and Technology (NIST). "Post-Quantum Cryptography Standards". 

[4] NCOG. “NCOG Earth Chain & Decentralized Application Ecosystem”.

Decentralized Database Management

  The Architecture for Modern Database Infrastructure

We produce a vast amount of data everyday. About 4.9 billion people use the internet for an average of seven hours per day and produce at least 2.5 quintillion bytes of data every day. Putting things into better perspective, that figure is 2.5 followed by 18 zeros.

It is no longer a debate that data is one of the most important resources available today. It continues to be the most important and a growing innovation driver for both large enterprises and small startups. From providing insights to grow a business to automating operational tasks — data has become the center point for decision making in organizations of any and all sizes.

Evolution of architecture for database infrastructure

To manage this large package of information and keep it relevant in order for organizations to scale and grow, we require a robust architecture for big data infrastructure. Over the years, the architecture for database management has evolved.

In the early 80’s business leaders would manage their data directly from a data warehouse that stored their basic files and documents. But as the many forms of data including music and videos evolved, it was no longer possible to store it in a central data warehouse. To navigate these issues, database management evolved into a cloud-based architecture.

However, even with the evolution of design for database management, it is not capable of supporting the needs of big data management. The architecture for modern database infrastructure requires the best-in class tools, stacks and application that sustains the foundation of the next-gen internet.

A modern database infrastructure architecture

Considering the value of data, its significance for any enterprise and the challenges in the current design of conventional database management systems, IneryDB offers the following value-propositions taking the lead towards building the architecture for today’s database infrastructure.

Paramount security

With the new level of sophistication of bad actors and new stringent data protection standards, security and privacy have become fundamental to the survival of a business. IneryDB allows any enterprise to build its own permissioned architecture with pre-defined permission to access, share, manage and own data. It allows data security and governance to work hand-in-hand to protect organizations alongside giving the space for innovation.

Decentralization at its core

In the last decade or so, we have repeatedly seen the side-effects of organizations controlling users’ data. The web2 iteration has allowed a few social media giants to capitalize on users’ information. Moving away from this infrastructure, IneryDB enables decentralization as its very core. This allows owners to be in control of their data assets.

Cost efficacy

Enterprises require cost-effective data administrators and maintenance alongside customizable settings that targets their workloads. Whether its high throughput applications or specialized dataset of an enterprise — IneryDB delivers optimal performance at lower costs.

Query and processing

Any modern database architecture needs to encompass query and processing technology to access, aggregate, and compute data. This allows organizations to easily access their specialized datasets using complex query functions in a fairly efficient manner. Inery’s database management solution offers the best functions of a distributed database including complex search queries coupled with the blockchain innovation.

An age of exponential growth

We are amidst the age of exponential innovation that is hard to track. The next version of the internet, web3, demands data to break from its fences and carry its own verification and trust for everyone to innovate.

Similar to those who adopted the web2 data-driven architecture early on, the ones who adopt the blockchain-based database will find a wide-playing field that drives innovation.

About Inery

Inery is the first-ever layer-0 blockchain offering the solution of decentralized database management with the vision to enable a new paradigm for data. Inery is designed to enable cross-chain communication of data, greater speed and better security. It specifically addresses database management integrated with blockchain functionalities and distributed database management properties.