Rise of Big Data – Issues and Challenges

Abstract

The recent rapid rise in the availability of big data due to Internet-based technologies such as social media platforms and mobile devices has left many market leaders unprepared for handling very large, random and high velocity data. Conventionally, technologies are initially developed and tested in labs and appear to the public through media such as press releases and advertisements. These technologies are then adopted by the general public. In the case of big data technology, fast development and ready acceptance of big data by the user community has left little time to be scrutinized by the academic community. Although many books and electronic media articles are published by professionals and authors for their work on big data, there is still a lack of fundamental work in academic literature. Through survey methods, this paper discusses challenges in different aspects of big data, such as data sources, content format, data staging, data processing, and prevalent data stores. Issues and challenges related to big data, specifically privacy attacks and counter-techniques such as k-anonymity, t-closeness, l-diversity and differential privacy are discussed. Tools and techniques adopted by various organizations to store different types of big data are also highlighted. This study identifies different research areas to address such as a lack of anonymization techniques for unstructured big data, data traffic pattern determination for developing scalable data storage solutions and controlling mechanisms for high velocity data.

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“…Each iteration works by combining different transformations to construct a complex encryption function. There are various implementations of these techniques, such as DES [7], 3DES [20], AES [2][3][4][5], and BLOWFISH [21].…”

“…This makes the relation between the plaintext and the ciphertext The second contribution of this work is the use of a dynamic offset based on the characters' position in the plaintext. It is generated automatically for each character using a pseudo-random generator and the character's position, as shown in Equation (2). This dynamic offset is produced as a function of the initial key, the character's position, and the pseudo-random number.…”

“…Breaches of sensitive data expose organisations to many threats, including reputational risk, financial penalties, and other fines for non-compliance with regulations that require high levels of security to protect sensitive data [1,2]. For example, the General Data Protection Regulation (GDPR) [3] outlines a specific set of rules for transferring and storing personal data to protect individual privacy.…”

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“…However, can these data be used as a valid, truthful, and reliable support in making decisions or in supporting research in various fields? The balance between potentialities and risks linked to these new data still needs to be fully explored [6]. On the one hand, the web data collection has relevant advantages.…”

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“…the representativeness of the covered statistical units). Most of these challenges still need to be fully explored (Goonetilleke et al, 2014, Alabdullah et al, 2018and Morstatter et al, 2013.…”