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Lava Lamps – A Surprising Beacon of Light for Internet Encryption

May 3, 2024

In the realm of Internet security, where digital threats loom large and data protection is paramount, innovative solutions often emerge from unexpected sources. One such solution is Cloudflare’s use of lava lamps as an unconventional approach to encryption.

Cloudflare, an IT service management company, works with clients to improve the speed, security, and reliability of their Internet properties. As a leading Internet security and performance corporation, Cloudflare handles a significant proportion of all Internet traffic, making ultimate security a critical concern for the company and compelling it to find better solutions for secure encryption.

At the heart of Cloudflare’s San Francisco, California headquarters lies an unusual feature: a wall of about a hundred lava lamps. Apart from adding an aesthetically-pleasing quality to the office, the mesmerizing wall forms a crucial component of the company’s encryption strategy.

The lava lamp wall in the San Francisco office of Cloudflare.

Invented in the 1960s, lava lamps consist of a transparent vessel filled with colored wax and liquid. When heated by an incandescent bulb at the base, the wax begins to melt and rise, creating undulating shapes and patterns within the liquid. The movements are chaotic and inherently unpredictable, making lava lamps an ideal source of randomness for cryptographic purposes. Due to their unique fluid dynamics and unpredictable patterns, lava lamps provide a rich source of entropy. Entropy, simply put, refers to the amount of disorder in a system. A camera captures the movement of wax  within each lava lamp, which is then fed into a cryptographic algorithm and used to generate cryptographic keys for encrypting internet traffic.

The high entropy of lava lamps provide the key and most essential element of the process – randomness. Lying at the core of secure encryption algorithms, randomness can be considered the foundation for generating cryptographic keys that resist brute-force attacks and other such vulnerabilities. Unlike deterministic processes, which follow predictable patterns, randomness introduces unpredictability and complexity, making it exceedingly difficult for adversaries to decipher encrypted data without the corresponding keys.

In the busy lobby of Cloudflare’s headquarters,  obstructions are commonplace, as people come and go, blocking parts of the wall from the camera’s view for varying periods of time. Surprisingly, these interruptions become part of the randomness that the camera captures, contributing to the entropy leveraged for secure encryption.

Computers, which operate on logic, are programmed to work based on if-then statements: By design, repeatedly entering the same input should produce the same output each time as a result. Certain computer programs can simulate randomness, but it is just that – a simulation. Eventually, patterns within these simulations can be found and predicted, forming an unstable base for security. As such, the lava lamp wall is a remarkable alternative to create unpredictable randomness and generate stronger keys.

Understanding the need for backups, Cloudflare has various contingency measures in place. The possibility of the camera being shut off or damaged is a potential concern for the integrity of the encryption process. In the event of camera failure, the company can rely on two other sources for randomization: the Linux operating system running on Cloudflare servers and physical access to the camera, which is situated in a Cloudflare-owned space. This accessibility enables Cloudflare to quickly rectify any issues by turning the camera on again or replacing it as is necessary, ensuring the continuity of the encryption process. Another possible scenario to consider is the secret use of an external camera to film the wall and generate cryptographic keys. However, to combat this case, Cloudflare also utilizes its two other major offices around the world to generate random data from real-world inputs. Filming the movements of a double-pendulum system in its London office and recording the radioactive decay of a uranium pellet via a Geiger counter in its Singapore location, Cloudflare has enabled the encryption process to become even stronger and more chaotic.

The lava lamp wall at Cloudflare, along with its other endeavors at its global offices, not only exemplifies a practical solution for generating cryptographic keys, but also models creative problem-solving. The success of Cloudflare’s lava lamp wall serves as inspiration for others in the technology industry to rethink traditional paradigms and explore new, unique avenues for enhancing digital security.

 

Sources:
Airhart, Ellen. “How a Bunch of Lava Lamps Protect Us from Hackers.” Wired, 29 July 2018, www.wired.com/story/cloudflare-lava-lamps-protect-from-hackers/.
Garge, Ishwari. “Cloudflare’s Encryption with Lava Lamps.” CSI Decrypt, 9 July 2021, medium.com/csirait-decrypt/cloudflares-encryption-with-lava-lamps-a144b4ad623f.
“How Do Lava Lamps Help with Internet Encryption?” Cloudflare.com, Cloudflare, www.cloudflare.com/learning/ssl/lava-lamp-encryption/.
“The Lava Lamps That Help Encrypt the Internet.” Atlasobscura.com, 29 Apr. 2019, www.atlasobscura.com/videos/these-lava-lamps-help-encrypt-the-internet.

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  Timothy Durham was convicted of rape when a test showed his DNA genotype matched the DNA recovered from the crime scene. Eye witnesses testified that Durham was in a different state at the time of the incident, but he wasn’t exonerated from his 3000 year sentence until follow up DNA analysis showed that the preliminary forensic analysis used in the trial was misinterpreted (Thomas et al.). DNA testing serves an invaluable part in our criminal justice system, but it comes with complications and bias that can lead to wrongful convictions and misinformed juries.  

Background:

Forensic genetics aims to identify the origin of a biological sample. It can be traced back to Karl Landsteiner who discovered human ABO blood groups. With blood groups, suspects could be eliminated based on their blood type. For example, if a suspect had type A blood and there was type B blood left at the scene by the perpetrator, the investigators could rule out the suspect. Unfortunately, the reverse didn’t work. If the suspect and perpetrator both had the same blood type, it can’t be concluded that the suspect was guilty. Blood identifiers evolved into 8 distinct categories which improved the ability to eliminate suspects, but could only conclude that (if the system matched) it might be the perpetrator or this person might be related to the perpetrator (Jobling and Gill). The field evolved in the 1980s with the discovery of Minisatellites, lines of repetitive DNA that don’t encode proteins. Minisatellite patterns in DNA create what we know today as the DNA fingerprint, and it has a much higher accuracy rate than previous methods (Augustyn et al.). Around the same time, a breakthrough for victims of sexual assault was discovered. In the case of assault, bodily fluids of both the victim and the assaulter can get mixed. A process called differential lysis was created which could selectively increase the concentration of sperm in a fluid sample thereby allowing for accurate DNA testing (Jobling and Gill). Forensics evolved to use single-locus probe testing after several years because of its ease of interpretation. It looked at specific minisatellites that had high variability between subjects. This was the first DNA-based method to be used in a criminal investigation. Two murder homicides from several years apart were connected using DNA evidence. The evidence was then used to exonerate an innocent man, and the guilty party was found when he tried to evade mandatory DNA testing for all men in the small town. His guilt was then reinforced when the DNA profiles matched, and he gave a confession (Jobling and Gill). Finding DNA at a crime scene doesn’t guarantee that you’ll find a murderer. There are issues with non-pure samples and limited samples that make DNA work difficult, and accreditation of facilities and new techniques and take time (Jobling and Gill).  

Subjectivity of DNA Interpretation:

In a 2009 publication, the National Academy of Science discusses the possibility for subjective influence in lab based forensics. The interpretation bias happens in complex cases where, for example, there could be a mixture of DNA. A study published in 2011 looked specifically at this issue. A gang rape happened in Georgia, and the mixture in DNA from the case was used to prosecute one suspect after another suspect took a plea bargain to testify against him. With DNA mixtures, there are three possible conclusions: suspect excluded, suspect cannot be excluded, and inconclusive. If the suspect is excluded, it means that there’s little to no possibility that his DNA is part of the sample. If the suspect cannot be excluded, it means that there’s a possibility that his DNA is part of the sample. In the trial, the DNA examiners who knew the context of the case concluded that the suspect being prosecuted could not be excluded. The 2011 study gave the DNA evidence from this case and the DNA profiles of the suspects to 17 forensic examiners. These examiners had no context of the case, and they all worked independently. Of the 17, only 1 came to the same conclusion (suspect cannot be excluded) as the examiners who knew the context of the case. Twelve of the 17 concluded that the suspect who was prosecuted and convicted had no relation to the DNA found in the sample. Not only does this show that subjectivity occurs due to the context of the case, but the 17 examiners came up with different findings based on their past experiences meaning that not all DNA analysis is objective. Some organizations like the Scientific Working Group on DNA Analysis Methods say that quantitative statistical evidence should be presented with every categorical conclusion, but the US doesn’t require this (Dror and Hampikian).

False Positives:

There are two categories that cause wrongful identification in a DNA report: coincidental matches and false positives. Coincidental matches are DNA matches between two unrelated people. The probability of these matches is about 1 to 500,000 for white individuals and about 1 to 350,000 for black individuals. This small probability of coincidental matches makes people feel confident in DNA evidence. False positives, on the other hand, are matches between DNA and test DNA that result from issues in the forensics lab. There have been multiple cases of forensics labs accidentally switching victim and suspected rapist DNA which lead to convictions that were later overturned when the lab realized the error. There are also cases of misreading or misunderstanding a sample. In a case from 1993, a man was convicted of rape because someone interpreted a mixed sample of victim and perpetrator DNA as an individual sample. The conviction was again overturned. To prevent false convictions, retesting DNA is allowed, but it’s not an efficient solution. Many people are pushing for statistical information on the probability of false positives, so that the jurors can make accurate judgements based on DNA evidence (Thomas et al.).  

Conclusion:

DNA analysis is a useful tool for the criminal justice system, but subjectivity can be an issue in forensic testing. To combat wrongful convictions, there are organizations like The Innocence Project who use DNA testing to free the innocent, but reformed forensic testing standards should be put in place to prevent subjectivity and to ensure juries are correctly informed during trials. https://www.innocenceproject.org/    

Citation:

Augustyn , Adam, et al. “DNA Finerprinting.” Encyclopedia Britannica , 26 Apr. 2018, www.britannica.com/science/DNA-fingerprinting#ref153186. Dror, Itiel E., and Greg Hampikian. “Subjectivity and Bias in Forensic DNA Mixture Interpretation.” Science & Justice, vol. 51, no. 4, 2011, pp. 204–208., doi:10.1016/j.scijus.2011.08.004. Jobling, Mark A., and Peter Gill. “Encoded Evidence: DNA in Forensic Analysis.” Nature Reviews: Genetics, vol. 5, no. 10, Oct. 2004, pp. 739–751., doi:10.1038/nrg1455. Thompson, William C, et al. “How the Probability of a False Positive Affects the Value of DNA Evidence.” Journal of Forensic Sciences, vol. 48, no. 1, Jan. 2003, pp. 1–8., doi:10.1520/jfs2001171.