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Cryptography With the DES Algorithm

Nowadays, information security is the main concern on the Internet. With web data continuously flowing from one end to another, to ensure data security, there are many procedures that must be implemented. Different organizations are working to find a more secure way to protect data.

There are also some key terms when it comes to information security — like confidentiality, integrity, availability, etc. Confidentiality means that only authorized users can gain access to sensitive data. Integrity confirms that data has not been modified by any mid-level person. Additionally, this means that the data reached the other user without changes or a breach. Lastly, availability means that data is available for any authorized user. There are many procedures that confirm data confidentiality, integrity, and availability. Almost all procedures use some type of encryption/decryption algorithm to keep data secure from middle attacks. And there are two kinds of security algorithms: symmetric algorithms (use the same secret key to encrypt/decrypt data) and asymmetric algorithms (use different secret keys to encrypt/decrypt data). The main goal of this article is to describe DES algorithm and how it secures data. 

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What Are the Stages of the Certificate Lifecycle?

Digital certificates are electronic credentials that are used to certify the identities of individuals, computers, and other entities on a network. Because they act as machine identities, digital certificates function similarly to identification cards such as passports and drivers’ licenses. For example, passports and drivers’ licenses are issued by recognized government authorities, whereas digital certificates are issued by recognized certification authorities (CAs).

Private and public networks are being used with increasing frequency to communicate sensitive data and complete critical transactions. This has created a need for greater confidence in the identity of the person, computer, or service on the other end of the communication. In addition, these valuable communications must be protected while they are on the network. Although accounts and strong passwords provide a certain level of assurance in the identity of the entity on the other end of the network, they offer little or no protection while data is in transit. In comparison, digital certificates and public key encryption identify machines and provide an enhanced level of authentication and privacy to digital communications.

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Up to Speed: Can Your Website Keep Up?

Site speed has always been a major concern in SEO circles, with slow sites bumped down in the rankings so that they perform poorly in searches. Unlike a few years ago, though, a slow site no longer lags behind its competitors by a few seconds. Rather, slow sites are typically only a few milliseconds slower because, as a site’s load time increases from 1 second to 3 seconds, bounce rate probabilities increase to 32 percent; by 5 seconds, the probability is 90 percent. In terms of ranking and engagement, even the smallest increase in speed can make a big difference.

Why Speed Matters

Obviously, slow sites have higher bounce rates than their speedier counterparts, but beyond our trained impatience, does speed really matter? According to Google, it’s a key factor, particularly for those using mobile devices, and it certainly plays a role in their ranking program. That’s why the website building company Wix recently introduced a program called Wix Turbo, which provides users with speed-focused optimization services. This includes improved server-side CSS layout optimization and changes to Wix’s data center system. Like other optimization programs, this system is designed to improve users’ Google rankings and put them on that first page.

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Operationalization of Machine Learning Models: Part 2

In part 1 of the series, we discussed the need to focus on Model Operationalization. We discussed Model Deployment and features required in scoring engines. We will continue with other areas of focus for model operationalization.

Fig: Operationalization (O16N) of Machine Learning Models in Enterprise