Advancements in genetic engineering have brought revolutionary tools to the forefront of biotechnology, with CRISPR leading as one of the most precise and cost-effective methods of gene editing. CRISPR, which stands for Clustered Regularly Interspaced Short Palindromic Repeats, allows scientists to alter DNA sequences by targeting specific sections of the genome. Originally discovered as part of a bacterial immune system, CRISPR systems have now been adapted to serve as programmable gene-editing platforms. This paper explores how CRISPR works, its current uses, its future potential, and the ethical considerations surrounding its application in both human and non-human systems.
How CRISPR System Works
The CRISPR-Cas system operates by combining a specially designed RNA molecule with a CRISPR-associated protein, such as Cas9 or Cas12a. The RNA guides the protein to a specific sequence in the genome, where the protein then cuts the DNA. Once the strand is cut, natural repair mechanisms within the cell are activated. Researchers can either allow the cell to disable the gene or insert a new gene into the gap. As described by researchers at Stanford University,
“The system is remarkably versatile, allowing scientists to silence genes, replace defective segments, or even insert entirely new sequences.” (CRISPR Gene Editing and Beyond)
This mechanism has been compared to a pair of molecular scissors that can cut with precision. For example, the Cas9 protein is programmed with a guide RNA to recognize a DNA sequence of about 20 nucleotides. Once it finds the target, it makes a double-stranded cut. The repair process that follows enables gene knockouts, insertions, or corrections. This technology has dramatically reduced the time and cost associated with gene editing, making previously complex tasks achievable in weeks rather than months. According to a 2020 review,
“CRISPR/Cas9 offers researchers a user-friendly, relatively inexpensive, and highly efficient method for editing the genome.” (Computational Tools and Resources Supporting CRISPR-Cas Experiments)
CRISPR’s influence extends across many fields, but its role in medicine has attracted the most attention. Scientists are using CRISPR to treat genetic diseases such as sickle cell anemia by editing patients’ own stem cells outside the body and then reinserting them. In 2023, researchers published results showing that a single treatment could permanently alleviate symptoms for some patients with these genetic diseases (Zhang 4.) Another area of exploration includes its potential for treating cancers by modifying immune cells to better recognize and destroy cancerous tissue. According to Molecular Cancer,
“Gene editing technologies have successfully demonstrated the correction of mutations in hematopoietic stem cells, offering hope for long-term cures.” (Zhang 3)
Beyond human health, CRISPR has transformed agricultural practices. Scientists are using it to develop crops that resist pests, drought, or disease without the need for traditional genetic modification methods that insert foreign DNA. One of the longer processes of traditional modifications in DNA could include conjugation. This is moving genetic material through bacterial cells in a direct contact. Conjugation is just one example of many of the traditional genetic modification methods.
CRISPR has been used to produce tomatoes with longer shelf lives and rice varieties that can survive in low-water environments. According to the World Economic Forum,
“CRISPR can help build food security by making crops more resilient and nutritious.” (CRISPR Gene Editing for a Better World)
Such developments are increasingly critical in addressing global food demands and climate challenges.
Research is also underway to apply CRISPR in animal breeding and disease control. In mosquitoes, scientists are testing ways to spread genes that reduce malaria transmission. In livestock, researchers are working to produce animals that are more resistant to disease. These experiments, while promising, require cautious monitoring to ensure ecosystem stability and safety.
Future Potential
Looking ahead, new techniques are refining CRISPR’s capabilities. Base editing allows researchers to change a single letter of DNA without cutting the strand entirely, reducing the off-targeting effect such as prime editing, a newer method that uses an engineered protein to insert new genetic material without causing double-stranded breaks. These tools provide even more control. According to the Stanford report,
“Prime editing may become the preferred approach for correcting single-point mutations, which are responsible for many inherited diseases.” (CRISPR Gene Editing and Beyond)
Possible Concerns
Despite its potential, CRISPR also raises important ethical concerns. One of the most debated topics is germline editing, or the modification of genes in human embryos or reproductive cells. Changes made at this level can be passed down to future generations, leading to unknown consequences. In 2018, the birth of twin girls in China following germline editing sparked international outrage and led to widespread calls for stricter regulation. The scientific community responded swiftly, with many organizations calling for a global prohibition on clinical germline editing. As CRISPR & Ethics – Innovative Genomics Institute (IGI) states,
“Without clear guidelines, genome editing can rapidly veer into ethically gray areas, particularly in germline applications.”
Another concern is the potential for unintended consequences, known as off-target effects. These are accidental changes to parts of the genome that were not intended to be edited, which could lead to harmful mutations or unforeseen health problems. I will expand on this later in the article. Researchers are actively developing tools to better predict and detect such errors, but long-term safety remains a topic of study. The possibility of using CRISPR for non-therapeutic purposes, such as enhancing physical or cognitive traits.
Cost and accessibility are also significant factors. Although the CRISPR tools themselves are affordable for research institutions, the cost of CRISPR-based therapies remains high. According to Integrated DNA Technologies,
“Therapies based on CRISPR currently cost hundreds of thousands of dollars per patient, limiting their availability.” (CRISPR-Cas9: Pros and Cons)
Bridging this gap requires investments in infrastructure, policy development, and global partnerships to ensure that developing countries are not left behind.
In conclusion, CRISPR is reshaping the landscape of genetics and biotechnology. It has already brought major advances to medicine, agriculture, and environmental science. While the technology is still evolving, its precision offers a glimpse into the future of human health. CRISPR the potential to unlock solutions to some of humanity’s most pressing challenges.
Lino, Cathryn A., et al. “Delivering CRISPR: A Review of Methods and Applications.” Drug Delivery and Translational Research, vol. 8, no. 1, 2020, pp. 1–14. PubMed Central, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427626/. Accessed 31 July 2025.
Imagine a world where every surface—the walls, the roof of your car—harnesses the sun to power your surroundings. Not with stiff, bulky solar panels, but with something as simple and inconspicuous as paint.
Thanks to new and evolving technology, this vision inches closer and closer to reality. Perovskite-based photovoltaic paint is a developing technology with the potential to turn any paintable surface into a solar panel.
What are Perovskites?
Perovskites are a class of crystalline materials with the structural formula ABX₃. ABX₃ means that perovskites have a Large Cation(A), a Smaller Cation(B), and an Anion(X₃, often a halide). Their unique structure makes them incredibly efficient at converting sunlight into electricity, with recent developments reaching over 25% efficiency (25% of energy from the sun was converted into electricity), while traditional solar panels usually have 15-25% efficiency.
The Parts of Perovskite Solar Paint:
Perovskite-based solar paint must be applied in multiple layers. The six main layers, in order, are: the transparent conductive layer (front/top electrode), electron transport layer, perovskite absorber layer, hole transport layer, back electrode, and substrate.
The transparent conductive layer functions as the front electrode. It must be transparent, to allow sunlight to pass through, and conductive, to carry the extracted electrons.
Next is the electron transport layer, which extracts and transports electrons from the perovskite layer to the electrode and prevents holes from moving in the wrong direction.
The perovskite absorber layer is located at the center and is made of a perovskite compound that absorbs sunlight to create electron-hole pairs (excitons). It acts as the photoactive layer where sunlight is converted into electricity.
The hole transport layer lies below, which extracts and transports holes (the positive charges) to the back electrode and blocks electrons from going backward, aiding in charge separation.
The back electrode then collects the holes and completes the electrical circuit, allowing current to flow through an external device.
Finally, the substrate is the surface being painted (can be glass, plastic, metal, etc.) and provides structural support.
How Perovskite Solar Paint Works:
Sunlight first hits a perovskite layer, and the perovskite material absorbs photons. This excites electrons from the valence band to the conduction band, creating electron-hole pairs (excitons). In perovskites, excitons require little energy to separate into electrons and holes, which improves efficiency. Electrons are pushed toward the electron transport layer and holes toward the hole transport layer. The front and back electrodes collect the charges, and because oppositely-charged electrons and holes are separated and collected on different sides, a voltage builds up between the two electrodes. When the painted solar surface is connected to a circuit, the voltage drives electrons through the wire, powering a device or charging a battery.
A Game-Changer for Clean Energy
Perovskite-based photovoltaic paint could radically transform the solar energy industry. Unlike traditional silicon, which requires high temperatures and vacuum conditions for production, perovskite materials are cheap and efficient. Perovskite paint can also be applied to a wide variety of surfaces, allowing homeowners to harness solar power in places where solar panels are impossible.
The Challenges to Implementation
As promising as perovskite solar paint is, several significant challenges stand in the way of widespread implementation. Current perovskite materials are highly sensitive to moisture, heat, and UV light, meaning they degrade quickly outdoors. While silicon panels can last 25 years or more, early perovskite prototypes can lose efficiency after months or just weeks. Researchers are working on protective coatings and new formulations to address this, but achieving long-term durability remains a hurdle. Most high-efficiency perovskite formulas also contain lead or other toxic heavy metals, raising concerns about environmental contamination and safe handling.
Efforts to develop lead-free perovskites are ongoing (tin being a promising alternative), though they currently offer lower efficiency and a shorter lifespan. While perovskite solar paint and panels work well in laboratory settings, scaling up to commercial production is complex. A uniform coating that ensures proper perovskite crystallization must be applied over large areas, and surfaces must be treated to ensure adhesion and conductivity. In addition, regulatory bodies are still developing safety and performance standards for perovskite technologies. Gray areas remain about how these materials will be certified/recycled at the end of their lifespan.
Global Progress and Investment
In the U.S., the Department of Energy recently allocated over $40 million to perovskite R&D, focusing on improving durability and scaling up production methods. Startups like SolarPaint, Oxford PV, and Saule Technologies compete to bring the first market-ready products to consumers, while well-known companies like Mercedes-Benz seek to implement solar paint in their newest vehicles.
Conclusion
Perovskite-based photovoltaic paint is still in the early stages, but it represents one of the most exciting frontiers in renewable energy. If challenges like stability and toxicity can be solved, any painted surface could soon become a power source. Keep an eye on your walls—they might power the world someday.
Glossary
Valence Band:
The highest range of electron energies where electrons are normally present at low energy (ground state)
Valence electrons reside in the valence shell of atoms
In any given material, atoms are packed closely together so their valence shells overlap and form the valence band
Electrons here are bound to their atoms and don’t move freely.
Band Gap:
The energy gap between the valence band and conduction band.
Electrons must absorb enough energy (like from sunlight) to jump across this gap.
The larger the gap, the more energy it takes to jump across, and the less conductive a material is
Semiconductors like perovskites have a small gap(1-2 electron volts) and can conduct electricity if energy is added(sunlight)
Conduction Band:
The higher energy band where electrons are free to move through the material.
Electrons in this band can carry electricity.
Electron-hole pairs:
When a photon(light) hits the perovskite, it transfers energy to an electron, exciting it from the valence band to the conduction band.
The excited electron in the conduction band moves freely and can conduct electricity.
The “hole” is the spot the electron left behind—a positive charge in the valence band.
There is now an electron-hole pair
Exciton:
An exciton is the state where an electron and a hole are bound together, still attracted to each other by opposing charges
Formed right after light absorption, before the electron fully separates from the hole/jumps to the conduction band.
Neutral overall, so they don’t conduct electricity until they break apart.
Common in some perovskites
Front and Back Electrode:
They collect and transport electrical charges (electrons and holes) generated by sunlight.
They’re like the “wires” of the solar paint that let electricity flow out into a usable circuit.
Front electrode: Lets light in and collects electrons or holes(depends on design, usually electrons)
Back electrode: Collects the opposite of what the front electrode does(back electrode usually collects holes) and helps drive current through an external circuit
Electron transport layer:
Extracts and transports electrons to the correct electrode
Hole transport layer:
Extracts and transports holes to the correct electrode
The transport layers guide the charges(electrons(-) and holes(+)) to the correct electrodes, helping to prevent recombination (when electrons and holes meet and cancel each other out).
Voltage:
Voltage is defined as the electric potential difference between two points.
It tells you how much “push” electrons are getting.
Measured in volts (V)
Voltage is like water pressure in a pipe. The higher the pressure, the more push the water (electrons) is getting
Current:
Definition: Current is the rate at which electric charge flows past a point.
Measured in amperes (A), or amps
More current = more electrons moving through the wire per second
Current is like the amount of water flowing through the pipe. The wider or faster the flow, the higher the current.
Power:
Definition: Power is the rate at which electrical energy is used or produced
Measured in watts
Formula: Power (P) = Voltage (V) × Current (I)
Power is like how much water pressure × amount of water is turning a waterwheel—how much work is being done.
Alanazi, T. I. (2023). Current spray-coating approaches to manufacture perovskite solar cells. Results in Physics, 44, 106144. https://doi.org/10.1016/j.rinp.2022.106144
Bishop, J. E., Smith, J. A., & Lidzey, D. G. (2020). Development of Spray-Coated Perovskite Solar Cells. ACS Applied Materials & Interfaces, 12(43), 48237–48245. https://doi.org/10.1021/acsami.0c14540
Chowdhury, T. A., Bin Zafar, Md. A., Sajjad-Ul Islam, Md., Shahinuzzaman, M., Islam, M. A., & Khandaker, M. U. (2023). Stability of perovskite solar cells: issues and prospects. RSC Advances, 13(3), 1787–1810. https://doi.org/10.1039/d2ra05903g
Khatoon, S., Kumar Yadav, S., Chakravorty, V., Singh, J., Bahadur Singh, R., Hasnain, M. S., & Hasnain, S. M. M. (2023). Perovskite solar cell’s efficiency, stability and scalability: A review. Materials Science for Energy Technologies, 6, 437–459. https://doi.org/10.1016/j.mset.2023.04.007
“Some experts in the field predict that the first quantum computer capable of breaking current encryption methods could be developed within the next decade. Encryption is used to prevent unauthorized access to sensitive data, from government communications to online transactions, and if encryption can be defeated, the privacy and security of individuals, organizations, and entire nations would be under threat.” – The HIPAA Journal
Introduction
The cybersecurity landscape is facing a drastic shift as the increasing power of quantum computers threatens modern encryption. Experts predict a quantum D-day (Q-day) in the next 5-10 years, when quantum computers will be sufficiently powerful to break through even the strongest of cybersecurity mechanisms. Meanwhile, few companies have begun to prepare against the threat, developing quantum resistant cybersecurity methods. However, to fully combat the threat, we need to act now.
Encryption Today
Modern cryptography is dominated by two major algorithms that transform ordinary text into ciphertext:
1. Rivest-Shamir-Adleman (RSA)
Dating back to 1977, the RSA algorithm relies on the factoring of large numbers. RSA can be separated into two parts, a private and public key. The public key, used for encoding, is a pair of numbers (n, e)where n is the product of 2 large prime numbers (p•q=n). The value of e can be any number that is co-prime to (p-1)(q-1), meaning that the GCF of (p-1)(q-1) and e is 1. The private key (d), used for decoding, is the reciprocal of the least common multiple of (p-1)(q-1) and e and can also be found by solving the equation 1= d • e • (p-1)(q-1) for d.
For decades, RSA has provided security for digital data because large scale of (n, e) numbers in addition to the variability of e means that it is nearly impossible to decipher (p, q) from (n, e). However, quantum computing brings forth the ability to quickly factor large numbers, allowing (p, q) to be determined from just the public key.
2. Elliptic Curve Cryptography (ECC):
Since 1985, ECC algorithms have been favored over RSA’s due to their greater complexity and faster encryption, with ECC’s capabilities proving to be up to ten times faster. ECC algorithms use an elliptical curve of the form y2=x3+ax+b over a finite field of not necessarily real numbers (Fp). A field Fp includes numbers from 0 to p-1, where p is prime.
Figure 1: The elliptic curve
Figure 2: The elliptic curve over F11
For the purpose of illustration, let us take the elliptical equation y2=x3+13 and a field F11. Figure 1 shows the elliptical curve while figure 2 shows the solutions to y2 =x3+13 (mod 11). The order of the curve is the number of points, including the arbitrary one at infinity, that satisfy the equation over a specific field (12 points in figure 2). The private key is some value k between 1 and the order of the curve. The public key can be calculated by taking one of the points, called the generator point (G), and multiplying it by k (kG). This system then encrypts the information using the public key (kG) and can only be decrypted by those who know k.
For example, let us take a value of k=5 and the point (9,4) as the generator point (G). When we multiply 5G, we are given the point (9,7), which would be the public key. However, just given the 2 points, it is extremely difficult to find the value of k.
ECC algorithms have long been considered nearly unbreakable due to the elliptic curve discrete logarithm problem , or the ‘ECDLP’. The ECDLP is a mathematical problem that asks: Given two points (P, Q) on an elliptic curve, what operation or algorithms could be used to find the specific constant k such that k multiplied by P equals Q?
The key issue in solving this lies in point multiplication, where a tangent line is drawn to a point on the elliptical curve (P) as part of the operation. Wherever that line intersects the elliptical curve again is point Q’. When Q’ is reflected across the x-axis of the equation (not necessarily y=0), the result is Q which equates to 2P. This process is continued until KP is reached. While it is straightforward to find Q given P and K, it is nearly impossible to find K given P and Q because there is currently no known inverse operation to undo, or solve for the coefficient in point multiplication.
Ultimately, RSA and ECC algorithms are what encrypt all of digital data and communication. They keep everything secure from classified government data to something as simple as a text message. Encryption allows private information to remain private and large national or international systems to continue functioning. It acts as a barrier against bad actors looking to hack or exploit this private data. Without encryption, there would be no safeguard for any data. Imagine if everything you ever put on a device, whether private photos or bank information, suddenly became public. You would no longer be able to trust digital privacy and safety if these algorithms were to fail.
To understand the momentous advancements in quantum computing, it is important to take a step back and examine the field’s origins as well as how quantum mechanics have evolved over time. Written in 1900 by Max Planck, the ‘Quantum Hypothesis’ explored the idea that rather than the conventionally accepted continuously flowing energy, energy was actually emitted in non-connected packets called quanta. His work laid the foundation for an exploration into what has become the field of quantum mechanics. Both Einstein’s 1905 work on the Photoelectric effect and Niels Bohr’s 1913 work on the atom further supported this claim by suggesting quantum leaps and the particle-like behaviors of a photon.
In 1927, Heisenberg formulated his uncertainty principle, which stated that it is impossible to simultaneously know the position and the speed of a particle with perfect accuracy. Einstein, Podolsky, and Rosen each published various works in 1935, questioning quantum mechanics via entanglement, or the influence of the state of one particle on the state of another simultaneously over great distances. Recent works have shown that entanglement can connect particles even between a satellite and the Earth. John Bell later proved entanglement by conducting experiments in search of violations of the Bell inequalities in 1964.
In 1926 Schrodinger created a system of wave equations that accurately predicted the energy levels of electrons in atoms. Neumann built on this alongside Hilbert’s work to create the mathematical framework for quantum mechanics, formalizing quantum states and creating a method to understand the behavior of quantum systems. In the 1940s Feynman, Schwinger, and Tomonaga developed their theory of Quantum Electrodynamics (QED) which described the interactions of light and matter.
The 1980 conference of physicists, mathematicians, and computer scientists was the turning point from quantum theories into quantum applications, laying the foundation for all of quantum computing. While the first working laser was created in the 1950s, quantum mechanics was not explored much further untilPaul Benioff’s 1980 description of a quantum computer,the first step towards quantum computing.
Quantum Computing: What is it and how does it work?
Superposition: The state of being in multiple states or places at once. Superposition is mostly commonly seen with overlaps of waves, but at a quantum level can be understood as a particle being in both state 1 and state 0 at the same time. However, when measured these particles must settle at either state 1 or state 0. The most commonly known analogy to explain this is the Schrodinger’s cat analogy: If you were to put a cat inside of a box with a substance that has an equal chance of killing or not killing the cat within an hour, then after one hour you could say that the cat is both dead and alive until you measure it, at which point it must be either dead or alive.
Entanglement: A phenomenon by which two particles become connected such that the fate of one affects the other, irrespective of the distance between the two. Prior to any measurement, two particles will always be in a state of superposition, meaning that the particles can be in both state 0 and state 1 at the same time. However, when measured, the state of one particle will directly affect the state of the other. This principle was proven by John Bell via the Bell inequalities.
Quantum computing allows storage of more information and more efficient processes, creating opportunities to infinitely increase the rate at which many modern machines work. While they face setbacks in these developing stages, they make it possible to perform multiple simultaneous operations rather than being limited by the tunnel effect that limits most modern machines to straightforward operations.
Quantum systems use qubits as the fundamental unit of information transfer instead of the traditional bit. Qubits allow for the superposition of ones and zeros making it possible for quantum computers with very few qubits to perform billions of operations per second, over a million times faster than the best computers on the market today. In addition, the entanglement of multiple qubits means that information capacity grows exponentially rather than linearly.
Compare and Contrast: Quantum Computers vs. Traditional Computers
The Quantum Threat to Cryptography
While current computers may not be strong enough to carry out an attack on cryptography, the emerging field of quantum computing poses a risk to all of modern encryption.
Is the threat just theoretical?
Even as an emerging technology, quantum computing poses a very real threat to cryptography. While many people would be more than willing to write it off as a threat of the future, that future may be closer than you believe. Quantum computing has shown its strength through many algorithms which could potentially result in the compromisation of sensitive data.
The most prominent algorithm in regards to cryptography is Shor’s ‘Factoring Algorithm’ from 1994. Specifically, Shor’s Factoring Algorithm (SFA) is a major threat to RSA cryptography systems. As I mentioned earlier, RSA systems rely on the creation of large numbers as the product of two prime numbers, basing security over the inability to efficiently factor those numbers.
According to Thorsten Kleinjung of the University of Bonn, it would take around two years to factor N = 135066410865995223349603216278805969938881475605667027524485 14385152651060485953383394028715057190944179820728216447155137368041970396419174 304649658927425623934102086438320211037295872576235850964311056407350150818751067 6594629205563685529 475213500852879416377328533906109750544334999811150056977236 890927563 with under 2 GB of memory.
Shor’s Algorithm could exponentially speed this up by working as follows:
Start with the large number (N) and a guess (g). If g is a factor of N or shares a factor with N then we have already found the factors.
If g is foreign to N, then we use the property that for any 2 prime numbers (a,b) there exists one power (n) and one multiple (m) such that an= mb+1. Applying this here we get gn= mN + 1. We can further rewrite this as (gn/2-1)(gn/2+1)= mN. We can now change our objective from searching for values of g to searching for values of n.
This is where quantum computing makes a vital difference. By testing many possible values of n, the quantum system starts in a superposition of states. After attempting to solve for n using the above equation (mod N), we begin to take advantage of the fact that if gx mod(N) = r then gx+pmod(N) =r if p is the period of the equation ( gp=1). When we utilize superposition, we test to see what values of x produce the same remainder, as the distance between those x values will be the period.
We can derive from this the frequency (f=1/p)
Here we can apply a Quantum Fourier Transform (similar to a classical Fourier Transform): When we absorb all the constructive and destructive interference of the superposition, 1/p is the remaining frequency.
Now that we have a candidate for p, we calculate our best guess for gp and iterate as necessary to correct quantum error.
Aside from algorithms, many corporations have made recent advancements towards building quantum computers as well. As recently as June 2025, Nord Quantique, a Canadian startup, announced their breakthrough ‘bosonic qubit’ which has built in error correction. This creates the potential to produce successful, encryption breaking 1000-qubit machines by 2031, far more efficient than the previously estimated 1 million-qubits.
The ‘Harvest Now, Decrypt Later’ Tactic
Another major reason why quantum mechanics is a threat to cryptography includes the ‘harvest now, decrypt later’ (HNDL) tactic. As the predicted Q-day nears (2035), threatening actors have begun to collect and store encrypted data, with the goal of decrypting it in the future with sufficiently powerful quantum machines. The attackers may not be able to decrypt the data, but they can intercept communications to steal encrypted data.
While it is easy to dismiss these attacks as something that could only be effective on nation-state levels, this assumption only feeds a false sense of security. For bad actors, corporate information could enable them to threaten economic chaos and large-scale disruptions. In fact, experts believe that these attacks have become increasingly focused on businesses as they hold the people’s data and the power to create mass economic instability.
Matthew Scholl, Chief of the Computer Science at NIST described the threat by saying,
“Imagine I send you a message that’s top secret, and I’ve encrypted it using this type of encryption, and that message is going to need to stay top secret for the next 20 years. We’re betting that an adversary a) hasn’t captured that message somehow as we sent it over the internet, b) hasn’t stored that message, and c) between today and 20 years from now will not have developed a quantum machine that could break it. This is what’s called the store-and-break threat.”
The most concerning aspect of these HNDL attacks is that it is nearly impossible to know when your data has been stolen, until it comes into effect with the rise of quantum computing. By then, the damage will be irreversible. While not all data will be of high value over a decade from now, attackers are threatening specific data that they believe will hold long-term value.
Over the past 10 years, incidents have arisen that resemble HNDL attacks:
In 2016, Canadian internet traffic to South Korea, was being rerouted through China
In 2020, data from many large online platforms was rerouted through Russia
A study by HP’s Wolf Security discovered that one third of the cyber attacks conducted by nation-states between 2017 and 2020 were aimed at businesses
Post Quantum Cryptography ( PQC)
However, companies and nations have already begun to look into ways to protect data from quantum attacks. Post-Quantum encryption algorithms focus on encrypting data in a way that will be equally difficult for quantum machines to break as it is for the classic computer.
The Deputy Secretary of US Commerce, Don Graves said,
“The advancement of quantum computing plays an essential role in reaffirming America’s status as a global technological powerhouse and driving the future of our economic security. Commerce bureaus are doing their part to ensure U.S. competitiveness in quantum, including the National Institute of Standards and Technology, which is at the forefront of this whole-of-government effort. NIST is providing invaluable expertise to develop innovative solutions to our quantum challenges, including security measures like post-quantum cryptography that organizations can start to implement to secure our post-quantum future. As this decade-long endeavor continues, we look forward to continuing Commerce’s legacy of leadership in this vital space.”
One example of a potentially powerful PQC algorithm is CRYSTALS-Kyber, which the NIST declared the best for general encryption in 2022. They added HQC to their list of PQC algorithms in 2024, giving us a grand total of five algorithms that have met the standard.
The NIST has named their standards for PQCs and urges people to work towards incorporating them now, because the full shift to PQCs may take as long as developing those quantum computers will take. Their key goals in this endeavor are to not only find algorithms that are resistant to quantum computing, but to diversify the types of mathematics involved to mitigate the risk of compromised data. They search for algorithms that are both able to be easily implemented and improved so that they maintain a ‘crypto-agility’.
Many companies support PQCs and believe that they will safeguard the future of cryptography. Whitfield Diffie, cryptography expert, explains that
“One of the main reasons for delayed implementation is uncertainty about what exactly needs to be implemented. Now that NIST has announced the exact standards, organizations are motivated to move forward with confidence.”
Companies such as Google, Microsoft, IBM, and AWS are actively working to develop better resistance to quantum threats, helping to build some of the most powerful PQC algorithms. IBM is currently advocating for a Cryptography Bill of Materials (CBOM), a new standard to keep tabs on cryptographic assets and introduce more oversight into the system. Microsoft has become one of the founding members of the PQC Coalition, a group whose mission is to step forward and provide valuable outreach alongside education to support the shift towards PQC as the primary form of encryption.
While PQCs could be a valuable resource against quantum threats, there are still setbacks that make people question the validity of the whole effort. The Supersingular Isogeny Key Exchange (SIKE) algorithm, one of the NIST finalists for the PQC standard, failed due to a successful attack by a classical computer, rendering many of the fundamental mathematical assumptions false. In addition, many of these algorithms suffer due to a lack of extensive testing and uncertainty regarding how much quantum machines will actually be able to accomplish.
Conclusion
While the timeline of PQC development might be uncertain, it is imperative that we work now. Quantum computing is no longer a threat looming in the future, but a present reality with significant impacts.It is imperative that we begin shifting towards these safer systems as a community. We cannot wait until the threat has come, we need to prepare now.
Rob Joyce, the Director of the National Security Administration’s Cybersecurity has stated that,
“The transition to a secured quantum computing era is a long-term intensive community effort that will require extensive collaboration between government and industry. The key is to be on this journey today and not wait until the last minute.”
Above all, it is crucial to recognize the threat and take action. Educating the people is the first step towards group action. Let awareness be our first line of defense.
Youth Stemline 