With the growth of the web and smartphones over the past years, the internet and technology sector has generally experienced a surge in digital data. These data could be in the form of audio, text, or video. Since most network administrators handle such data on a daily basis, it has led to the increasing demand for storage spaces. Most organizations have therefore invested heavily in various storage devices to back up their data. However, with data compression, organizations are set to save storage capacity while speeding up file transfer as the technology reduces the number of stings required to represent information. Data compression is conducted by algorithms that determine how data sizes shrink, optimizing backup storage performances. Even though many programs can perform such activities, Winzip and 7Zip are the most common compression tools that use ZIP and RAR archive file format compressions, among many others. Since most organizations are adopting these tools into their daily backup activities, their security is more critical, and network administrators and other security experts should be aware of the proper procedure for encrypting and compressing organizational data.
While compression is essential, security is even more critical. Network administrators and other cybersecurity personnel within an organization should not compress data before encrypting it. Since encryption first turns data into random streams and relies on patterns to gain file size reduction, some individuals might prefer this method since compression algorithms might be unable to give much reduction size for encrypted data. However, the method exposes these data to a side-channel attack called compression oracle, which malicious attackers can use to remove plaintext information. With such data, hackers can cause stings to be places into unknown data streams of plain texts leading to data breaches. Examples of such methods of attacks include CRIME and BREACH, whereby hackers attacked SSL/TLS ( Alsing & Wandelt, 2018).
Delegate your assignment to our experts and they will do the rest.
References
Alsing, J., & Wandelt, B. (2018). Generalized massive optimal data compression. Monthly Notices of the Royal Astronomical Society: Letters , 476 (1), L60-L64.