Discuss about the Privacy and Security Issues Associated with Big Data.
Big Data refers to massive amounts and volumes of data sets that are analyzed with the help of automated tools in order to retrieve important information out of the same such as patterns, reports, statistics and likewise. The data that is involved with Big Data may be structured, semi-structured or unstructured and may comprise of information of varied types such as public, sensitive, confidential, private and many others. Due to the presence of such huge volumes of data, there are a number of security and privacy issues that have been seen in association with the Big Data. The document covers these issues along with their description.
There are five important properties that are associated with the data that is comprised in the Big Data.
Volume refers to the amount of data that is incorporated in the repositories with every passing second. The present era is the era of information and the information that is associated with one particular organization is massive. There are millions and billions of terabytes or zettabytes of data that is accessed and included on a daily basis.
It refers to the speed at which the data moves around from one entity to the other in case of Big Data. The velocity at which the data moves around is just few milliseconds and it is essential to keep track of the movement of every data bit at all times.
The data that is included and amalgamated for one organization is not of one particular data or format type. The data has a great degree of variety associated with it in terms of the structure and the format. It may be completely structured or totally unstructured and thus varies from one data set to the other.
The veracity of the data is its quality or accuracy that is associated with it. There is the presence of huge volumes of data and the quality of the data is not consistent all throughout. The data varies from one data set to the other and is therefore required to have a standard quality measure all throughout.
The value of data of of utmost importance since all of the data that is collected is not of use. There are data bits and sets that must be discarded as they do not add any value to the organization.
These are two of the most common issues that are encountered in case of the Big Data. Due to the presence of huge variety of data and such large volumes of data, it becomes easier for the attackers to get access to one or the other data set through unauthorized manners. Also, the data moves from one location to the other at almost on a non-stop basis. It may often lead to the leakage of the data at one node in the network or the other. These issues adversely impact the security and privacy of the data as the intent of the attackers is always malicious and the nature of the attack is always deliberate. It may take a toll on the privacy, confidentiality and integrity of the data. There are a number of cases of security breaches that have affected the organization and the victim from moderate to extremely severe impacts (Csa, 2012).
Big Data is a term and a set of methods that is still a newer concept for many. There are organizations that are not aware about the concept and the practices that are followed in the same. It is because of this reason that the required security architecture is missing from the organizations with respect to the Big Data and the same leads to a number of security loopholes. The features such as encryption, advanced authentication, dedicated risk management and likewise are still missing from the security infrastructure of the organizations (Moura & Serrao, 2016).
In continuation with the previous security concern, there is also a problem of the inadequate skills that are required among the resources for the maintenance and the management of the security as far as the Big Data is concerned. The resources still have areas in Big Data that they have not had access to before and are still unexplored for them which results in some of the severe problems associated with the security and the privacy of the data (Schmitt, 2016).
The data that is present and associated with Big Data is huge in volume. It is because of this reason that the data is stored on a number of locations and places rather than at one single data repository. There are scenarios in which the required security measures are not implemented across all the storage locations which create a security loophole and allow the attackers to enter the storage system and violate the privacy of the data (Thayananthan & Albeshri, 2015).
Data is constantly moved from one place or location to the other as pointed out earlier. During the transfer of the data, there are often the integrity attacks that are executed by the attackers. As a result of these attacks, the data is either modified from its original form or gets completely lost. For instance, message alteration is an attack that is often executed on the Big Data to modify the information in an unauthorized manner and it takes place during the data transfer. The data is either re-routed or altered so that it loses its original structure (Ahmed, 2016).
There are often scenarios wherein the data sources that are involved with the Big Data are faulty and do not follow the security norms as required by the nature of data that is acquired from a particular source. For instance, there may be malicious codes such as viruses, worms or Trojan horses present along with the data that get acquired along with the data. These malicious codes may then spread to the other parts of the repository and may infect the other data bits as well (Toshniwal, 2015).
These are a common form of attacks that are executed in case of Big Data and affect the availability of the information which in turn takes a toll on the security and privacy of the data. There is a number of availability attacks that are executed out of which Denial of Service (DoS) attacks are the most common. The attackers introduce huge volume of unnecessary traffic in the network that hampers the availability of the network and makes the service completely inaccessible (Tsai, 2016).
The research helped in understanding of the concept of the Big Data and the essential properties that are associated with the same. It also helped in the understanding of the privacy and security issues that are associated with the concept and are often overlooked or not paid due attention. The issues such as those related to the data sources or the data storage were something that were not thought of before and the research allowed gaining the information about them along with the meaning, execution and description of each.
There is another important issue of insider threats that has not been covered in the list of the privacy and security issues that are discussed. The issue is of significant importance since there are a number of threats and attacks that are executed with the medium as employees of an organization. These employees include the current as well as ex employees and they are completely aware about the security policies and parameters that are associated with a particular organization. They give shape to an attack in the Big Data by violating the security and risk management policy or allow an intruder to have access to the information by violating the identity and access management norms. This issue exposes the important and private information to the attackers and is therefore extremely sever in nature.
The impact of the issues that have been listed above can be low, medium, high or severe and the same would depend upon the nature and type of the data that is impacted. For instance, if the attacker succeeds in acquiring the information that is private, sensitive and confidential in nature such as the one that is associated with healthcare or financial institutions, then the impact would be extremely severe. It may result in legal punishments and policies as well. However, if the data or information that is affected is public in nature then the impact would be low or moderate (Goodendorf, 2016).
There are a number of lessons and important information that are acquired through the medium of research on the topic Privacy and Security Issues associated with Big Data. The primary lesson that is acquired is the concept and the properties that are associated with Big Data. The second lesson that has been learnt revolves around the number of issues and attacks that the information and the data related with big data is exposed to. These issues include the ones related with the data storage, data breaches, data loss, data sources and many others. Another important lesson that is acquired includes the importance of the maintenance of security parameters within an environment in order to protect the privacy and confidentiality of the data.
Conclusion
Big Data comprises of huge volumes, variety and value of data and it is because of this reason that there are a number of privacy and security issues that are associated with the same. These issues can be controlled and prevented with the help of a number of countermeasures such as implementation of advanced identity and access management. Physical security along with the basic security such as use of anti-malware and firewalls can also be of great assistance in the maintenance of security. Cryptography and the application of encryption are the two methods that can be extremely useful in the protection of the privacy and security of the information. Encrypted information will allow the maintenance of security even when the attacker would be able to get hold of the same.
References
Ahmed, E. (2016). A Survey of Big Data Cloud Computing Security. Retrieved 22 September 2016, from https://ijcsse.org/published/volume3/issue1/p3-V3I1.pdf
Csa,. (2012). Top Ten Big Data Security and Privacy Challenges. Retrieved 22 September 2016, from https://www.isaca.org/Groups/Professional-English/big-data/GroupDocuments/Big_Data_Top_Ten_v1.pdf
Goodendorf, L. (2016). Managing big data privacy concerns: Tactics for proactive enterprises. SearchSecurity. Retrieved 22 September 2016, from https://searchsecurity.techtarget.com/feature/Managing-big-data-privacy-concerns-Tactics-for-proactive-enterprises
Moura, J. & Serrao, C. (2016). Security and Privacy Issues of Big Data. Retrieved 22 September 2016, from https://arxiv.org/ftp/arxiv/papers/1601/1601.06206.pdf
Schmitt, C. (2016). Security and Privacy in the Era of Big Data. Retrieved 22 September 2016, from https://www.renci.org/wp-content/uploads/2014/02/0213WhitePaper-SMW.pdf
Thayananthan, V. & Albeshri, A. (2015). Big Data Security Issues Based on Quantum Cryptography and Privacy with Authentication for Mobile Data Center. Procedia Computer Science, 50, 149-156. https://dx.doi.org/10.1016/j.procs.2015.04.077
Toshniwal, R. (2015). Big Data Security Issues and Challenges. Retrieved 22 September 2016, from https://www.ijirae.com/volumes/Vol2/iss2/03.FBCS10080.pdf
Tsai, C. (2016). Big data analytics: a survey. Retrieved 22 September 2016, from https://journalofbigdata.springeropen.com/articles/10.1186/s40537-015-0030-3
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