The biggest threat to our
digital systems

The rise of quantum computing and the relentless advancement of artificial intelligence (AI) present immediate challenges to the integrity of our encrypted systems. These technologies disrupt the status quo, exposing the vulnerabilities of current encryption methods that hinge on the computational limitations of classical computers. Compounding these concerns are the rapid

proliferation of these technologies and the

parallel advancements in classical

computing, exemplified by the presence of

Exascale computing that can do

quadrillions of error corrected, floating

point, calculations per second.

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America faces a profound challenge in

safeguarding its data amidst this

technological upheaval. The threat lies in

the obliteration of the bedrock

upon which our digital protections are built. Quantum computing, with its promise of exponentially faster computation, threatens to dismantle the very algorithms we rely on to secure our communications and transactions. Meanwhile, AI, equipped with its learning capabilities, is poised to revolutionize the landscape of cyber threats, augmenting traditional attacks with unprecedented sophistication and adaptability. In fact, new Generative Large Language Multi-Modal Model's (GLLMM) that can do advance mathematics can solve incredibly difficult problems used in encryption with ease, speed and at incredible scale. 

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During this time of unprecedented technological convergence, the imperative to modernize our digital defenses has never been more urgent. The stakes are high, and the ramifications of inaction are dire. It is imperative that we immediately move to a new standard that moves beyond math-based security where quantum and AI systems excel at subverting. We must move to a 'physical' process that protects data by a function of physical binary alteration like Secured2's QuantaMorphic® protection. Failure to do so risks exposing our most sensitive data to unprecedented levels of vulnerability, with far-reaching consequences for national security, privacy, and economic stability.

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So what is the threat, and how close are we to a crypto-apacalypse? 

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• Quantum Computing: Quantum computers have the ability to perform certain types of calculations much faster than classical computers by leveraging the principles of quantum mechanics. One of the most concerning aspects for encryption is their ability to efficiently solve problems such as integer factorization and discrete logarithms, upon which many commonly used encryption algorithms, like RSA and ECC, rely.

  • Shor's Algorithm: Shor's algorithm, proposed by mathematician Peter Shor, demonstrates how a quantum computer could factor large numbers exponentially faster than classical computers. This would render widely used public-key cryptography schemes vulnerable to attacks, as the security of these systems relies on the difficulty of factoring large numbers.

  • New Algorithms: There are a number of new encryption breaking algorithms targeting different ways to break traditional encryption. Such as calculating the number sequence of the pseudo random number generator that creates encryption keys and also algorithms targeting weaknesses in new post-quantum algorithms based on algebraic math or solving very difficult math-problems.  

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• Artificial Intelligence: AI is being used to break encryption by solving difficult problems and through pattern recognition within data streams. AI presents an incredible existential threat to our encryption systems as a new tool that allows attackers a way to find new weaknesses and advanced methods of breaking encryption. You will see AI as a preferred hacking tool as we move into post-quantum algorithms that will be exploited by solving very complex mathematical problems. The ability of the AI to learn, and find new ways of breaking into systems present an incredible threat.   

  • Machine Learning-Assisted Attacks: AI algorithms, particularly machine learning techniques, can be used to analyze large datasets and identify patterns in encrypted communications. This can aid in the development of more sophisticated attacks, such as cryptanalysis and brute-force attacks, which could compromise encrypted data faster than traditional methods.

  • Adversarial Machine Learning: Adversarial machine learning involves training AI algorithms to find weaknesses or vulnerabilities in encryption systems. These algorithms can adapt and evolve to overcome defensive measures, potentially leading to the discovery of new attack vectors or the optimization of existing ones.

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To confront these challenges, Secured2 has emerged as a pioneering force, fundamentally reshaping the approach to data protection. Rather than relying solely on math-based encryption vulnerable to quantum computing, we've shifted towards physical protection methods. By doing so, we circumvent the threats posed by mathematical manipulation and the solving of complex equations.

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Furthermore, ongoing efforts in AI-driven security seek to reinforce our defenses against attacks leveraging artificial intelligence. The collaboration between experts in quantum computing, cryptography, and AI will prove indispensable in crafting encryption solutions that are both robust and resilient in the face of emerging threats. Secured2 is at the forefront of AI research in adding new and additional layers of security protection.