Quantum and Neural Cryptography

Driven by the increasing trend in Data, threats and attacks on Cybersecurity have rapidly escalated, creating a need for high-security measures in infrastructure and data privacy. At this point, analyzing data to secure it and derive logical insights has become one of the most sought-after topics today. Encryption measures implemented against emerging and growing security issues have been examined, revealing that encryption approaches are primarily carried out in neural and quantum cryptography domains.

Neural Cryptography

Neural Cryptography is a multilayered system that operates similarly to LINK[f478ba20fc044652] systems in machine learning using brain cells. Fundamentally, it establishes a mathematical relationship between a set of inputs and their corresponding outputs using an Artificial Neural Network (ANN) and classifies them. This cryptographic technique occurs in three stages: the first is linking, the second is learning, and the last is the activation phase. In the connection stage, the first layer, relationships between neurons are established based on correlation, and data is transferred to the second layer through synapses that evaluate information using various parameters. In the learning stage, the second layer, evaluation of the data is controlled and stored parameters are reviewed. In the activation stage, the third layer, outputs are generated from the reviewed inputs.

Quantum Cryptography

Quantum cryptography is constructed based on Heisenberg’s Uncertainty Principle, photon polarization, and entanglement principles. It performs data transmission and encryption primarily through Quantum Entanglement and Key Distribution Protocol techniques. The BB84 protocol, also known as the Quantum Key Distribution (QKD) protocol, emerged in 1984 and is grounded in Heisenberg’s Uncertainty Principle, photon polarization, and entanglement. The most preferred protocol, “Quantum Key Distribution” (QKD), does not directly encrypt user data but enables secure access to data requiring confidentiality. The most preferred protocol, “Quantum Key Distribution” (QKD), relies on superposition, entanglement, and the no-cloning theorem; thus, an attacker cannot copy or interfere with the database. Quantum cryptography uses encrypted fiber networks. In these networks, photons in superposition states are sent to determine binary and zero qubits until the key is generated and decrypted. Transmitting qubits sent via the BB84 protocol through a quantum channel and searching in NoSQL databases using Grover’s Algorithm in a quantum environment significantly enhances big data security. According to Heisenberg, it is impossible to simultaneously know certain physical properties with perfect precision; as the accuracy of one property increases, the accuracy of the other must decrease. Thus, the Uncertainty Principle demonstrates that measuring a quantum state is impossible without collapsing the entire system. In the BB84 protocol, message transmission occurs in two ways: photon transmission and classical data transmission. In photon transmission, the sender uses a prearranged sequence to determine the states of photons. Simultaneously, the receiver prepares another sequence of the same length to measure photons and establish the basis. The critical point of this transmission is the sending of two entangled messages. When defining two entangled photons, it is impossible to define one without the other; their qualitative properties are intertwined. If you are not faster than the speed of light, it is impossible to intercept and read the photon transmission message. Therefore, when two messages are sent, the only way to prevent communication collapse is for both messages to be opened simultaneously. Today, particularly in the United Kingdom, like, many large companies requiring highly secure communication have begun using quantum cryptography for message transmission.

Although both cryptographic techniques converge at a point due to their high security capabilities, they differ in that quantum cryptography has a limited operational scope while neural cryptography faces challenges in encrypting and decrypting secret keys. Another accepted point in the literature is that due to the high volume, heterogeneity, and rapid growth of big data, potential conflicts may arise between data quality and security.