Week 5_Discussion

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Nov 24, 2024

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In information security, terms such as "secured by 128-bit AES" and "protected by 2048-bit authentication" are applied regularly. A few examples of algorithms that have repeatedly been demonstrated to be highly challenging to decipher and decode include RSA, AES, and ECC. These are just a handful of the many algorithms that exhibit this trait. They are skilfully integrated into protocols that protect not only our identities but also the privacy of our data and our capacity to uphold its integrity consistently. To put it another way, they defend our right to data privacy. In all these behaviours, private information is transmitted across the Internet (Zhang et al., 2019). Confidential information must be shared for each initiative across the Internet and a public network. In all these cases, confidential information must be delivered via the Internet. If you want to connect your laptop to the network at your place of employment, you can use IPsec and IKE. You could carry out any of these actions in a safe manner. You can undoubtedly come up with a ton of more examples as well (He et al., 2018). We have never encountered any declarations regarding the dependability of the random number generator that a security system employs, which is a great disappointment. Things of this sort should take place with a higher degree of regularity. In general, power consumption and bit formation rate are more important to system designers than the actual randomness of the produced bits (He et al., 2018). It is true because each of these factors directly affects the rate at which information can be generated. It is due to the exact correlation between the rate of bit creation and the amount of power utilized. If one finds out that the quality of the random numbers used in most, if not all, cryptographic systems directly affect the security level that the system provides, it will be harder to understand why this would be the case. But once one understands this, it will be easier to see why this could be the case. A direct correlation exists between the reliability of
the random number generator and the difficulty of launching an attack on the system (Zhang et al., 2019). References Zhang, G., Zhao, L., Jin, J., Zhang S. (2019). network communication security through the use of encryption technology. Physics Journal Conference Series, 2006(1). doi:1088/1742-6596/2006/1/012037 He, S., Li, X., Wang, Q. (2018). Application of data encryption technology to simulation software. Conference series in physics, 2024 (1). doi:1088/1742-6596/2024/1/012060 Reply: It's plausible that "random" is a measurement in and of itself, in the same vein as "length" or "time." On the other hand, what it measures is intangible; more specifically, it evaluates how little you know about a specific system. It is possible to define "true randomness" as the lack of knowledge that would let one result be favoured over another. It is the only situation in which there is a possibility for "true randomness" to exist. If one accepts this definition, it is conceivable, but only for those who do not have access to the relevant information. The facts have always been there, regardless of whether anyone knows them, even if there is no way they could ever be known to anyone. They have always been there because they have always existed. Even seemingly unrelated events, such as the static on a television or the decay of radioactive material, originate in a convoluted web of causal factors. Because of this, there is no such thing as "true randomness" in that the term is understood when applied in its most literal sense. Reply: The biggest danger associated with PRNGs is that an opponent can guess or discover the seed value, potentially allowing them to predict the entire series of numbers. This would put
cryptographic systems in jeopardy of having their integrity compromised. The fact that PRNGs are utilized to produce random numbers makes this a matter of concern. Even though the practical safety of pseudorandom number generators (PRNGs) is a topic of ongoing debate, many commonly used cryptographic systems rely on them. It is even though the security of PRNGs in practice is often questioned. The challenge is designing and implementing PRNGs that offer an appropriate level of protection for the specific cryptographic application being contemplated, as this is where the problem lies. Academics are always researching new ways to increase the security of cryptographic systems, and the fields of cryptography and the generation of random numbers are continuing to take significant steps forward.
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