This essay has been submitted by a student. This is not an example of the work written by professional essay writers.

Big Data Analytics in Cyber Security

downloadDownload printPrint

Remember! This is just a sample.

You can get your custom paper by one of our expert writers.

Get custom essay

121 writers online

Download PDF


In 2015 assault influencing the US Government’s Office of Personnel Management has been ascribed to what’s being described as on-going cyberwar between China and the U.S. The most recent rounds of assaults have been alluded to utilizing a wide range of codenames, with Deep Panda being among the most common attribution. The attack on OPM in May 2015 was understood to have compromised over 4million US personnel records with fear that information pertaining to secret service staff may also have been stolen. And the FBI and various security experts concluded that it’s an advanced persistent threat (APT).

Executing an APT strike requires a bigger number of assets than a standard web application assault. The culprits are normally groups of experienced cybercriminals having considerable money related support. Some APT assaults are government-subsidized and utilized as digital fighting weapons. Traditional security systems may not be able to help to control or mitigate the issue. That’s where the Bigdata analytics comes in to the picture of information security providing the ability to correlate logging events based on time and user behavior across the entire spectrum of devices and technologies in an enterprise and many more dynamic insights and solutions to keep it secured.


Cyber-attacks have pushed corporate fraud around the world to an all-time high, with information theft overwhelming the apportionment of physical resources out of the blue on record, as indicated by new information. Levels of reported fraud have gradually climbed since 2012, but 86 per cent of organizations around the globe revealed that they had encountered no less than one digital occurrence in 2017, as indicated by reactions given to Kroll’s yearly worldwide misrepresentation and hazard study.

The reactions come as nervousness is high in meeting rooms about hacking following multiyear when the Wanna Cry digital assaults focused on a huge number of associations worldwide, disabling operations from the UK’s National Health Service to US delivery service FedEx. Even more as of late, the imperfections found in chips made by Intel, AMD and ARM, have raised fresh concerns that companies could be vulnerable to attacks. Information-related risks are now the greatest concern cited among executives who participated in the overview, as the experience of Equifax has honed minds and demonstrated that specialists are taking an increasingly robust response.

The US credit-reporting company now faces criminal and regulatory investigations on both sides of the Atlantic after a digital assault brought about the burglary of individual information of the same number of as 143m US citizens. The greater part the respondents to the review trusted that their organizations were “profoundly or somewhat vulnerable” to information theft; an ascent of six rate focuses on a year ago.

Advanced Persistent Threat (APT) Progression

A successful APT attack can be broken down into three stages:

  1. network infiltration,
  2. the expansion of the attacker’s presence and
  3. the extraction of amassed information—all without being identified.


Endeavors are regularly invaded through the bargaining of one of three assault surfaces: web resources, network resources or authorized human users. This is proficient either through malignant exchanges or social building attacks perils looked by considerable affiliations constantly. Additionally, infiltrators may all the while execute a DDoS assault against their objective. This serves both as a smoke screen to divert arrange work force and as a means of weakening a security perimeter, making it easier to breach.

When starting access has been accomplished, aggressors rapidly introduce an indirect access shell-malware that gifts network access and allows for remote, stealth operations. Secondary passages can likewise come as Trojans covered as genuine bits of programming.


After the toehold is built up, aggressors move to widen their essence inside the system. This includes climbing an association’s pecking order, trading off staff individuals with access to the touchiest information. In doing as such, they’re ready to assemble basic business data, including product offering data, representative information and budgetary records. Contingent upon a definitive assault objective, the collected information can be sold to a contending undertaking, modified to disrupt an organization’s product offering or used to bring down a whole organization. If harm is the thought process, this stage is utilized to inconspicuously pick up control of different basic capacities and control them in a succession to cause most extreme harm. For instance, aggressors could erase whole databases inside an organization and after that disturb arrange interchanges to delay the recuperation procedure.


While an APT case is in progress, stolen data is normally put away in a safe area inside the system being attacked. When enough information has been gathered, the cheats need to separate it without being recognized. Normally, white noise tactics are utilized to divert your security group, so the data can be moved out surreptitiously. This may appear as a DDoS assault, again tying up network work force and potentially debilitating site protections to encourage extraction.

Most famous APT attacks in 21st century

Titan Rain (2003)

In 2003 malicious hackers situated in China started a progression of far-ranging cyber-attacks against U.S government focuses with the point of taking delicate state privileged insights and secrets, in a task nicknamed Titan Rain by U.S specialists (Thornburgh, 2005). The hackers’ emphasis was on military information and included APT assaults on top of the line frameworks of organizations such as NASA and the FBI.

Sykipot Attacks (2006)

Sykipot cyber-attacks use vulnerabilities in Adobe Reader and Acrobat and are a part of a long-running set of cyber-attack crusades happened in a series pointed basically at U.S and U.K associations including resistance defense workers, broadcast and telecommunications organizations and government offices.

GhostNet (2009)

GhostNet is the name that analysts provided for an extensive scale cyber espionage task that was first came out in 2009. Completed in China, the assaults were fruitful in bargaining PCs in more than 100 distinct nations with an emphasis on penetrating network devices related with international embassies and government services.

Stuxnet Worm (2010)

Considered at an opportunity to be a standout amongst the most advanced bits of Malware ever identified, the Stuxnet Worm was utilized as a part of activities against Iran in 2010. Its intricacies showed that exclusive country state actors could have been engaged with its development and deployment. A key differential with Stuxnet is that, unlike most infections, the worm targets frameworks that are customarily not associated with the web for security reasons. It rather contaminates Windows machines by means of USB keys and afterward proliferates over the system, examining for Siemens Step7 programming on PCs controlling a PLC (programmable rationale controllers).

Deep Panda (2015)

A recently found APT attack influencing the US Government’s Office of Personnel Management has been credited to what’s being portrayed as on-going cyber war amongst China and the U. S (Jeremy, 2015). The most recent rounds of attacks have been referred to utilizing a wide range of codenames, with Deep Panda being among the most well-known attribution. The assault on OPM in May 2015 was comprehended to have bargained more than 4million US personnel records with expect that data relating to mystery benefit staff may likewise have been stolen.

Why should you make use big Bigdata analytics in cyber security?

Before, anything it’s good to understand how exactly the data analytics functions with available data sets.

The ever rise in the successful execution of digital attacks and its unwanted consequences and broad impacts demonstrate that the traditional cyber security instruments and practices are not ready to adapt to the complex danger scene because of the accompanying reasons

  • retaining a lot of information
  • analyzing unstructured information
  • managing expansive information distribution centers
  • responding progressively and
  • detecting Advanced Persistent Threats (APT).

To address these impediments, propose a development display for cybersecurity that energizes the fuse of enormous information apparatuses and advancements. There exist hundreds of such tools and technologies and are well-documented in the academic literature. A portion of the unmistakable enormous information instruments incorporate Hadoop, Spark, Storm, Flume, HBase, Hive, Kafka, Cassandra, and Mahout.

It has been proposed in that huge information instruments and innovations would change cybersecurity investigation by empowering associations to

  • collect a large amount of security-related heterogeneous data from diverse sources
  • perform deep security analytics at real-time and
  • provide a consolidated view of the security-related information.

The big data processing framework employed in the security analytic systems. The preparing structure gives the rules to handling the enormous information. In the reviewed papers, there are three frameworks used – Hadoop, Spark, and Storm. These frameworks are quite popular as evident from their use by well-known organizations such as Yahoo, Google, IBM, Facebook, and Amazon.

Big data analysis may be an appropriate approach for APT detection. A challenge in investigation APTs is that the huge quantity of data to sift through in search of anomalies. Data comes from ever-increasing range of numerous information sources that must be compelled to be audited. This huge volume of information makes the detection task appear as if finding out a needle in a very stack. Because of the amount of information, ancient network perimeter defense systems will become ineffective in police investigation targeted attacks and that they aren’t scalable to the increasing size of organizational networks. As a result, a brand-new approach is needed. Several enterprises collect information regarding users’ and hosts’ activities inside the organization’s network, as logged by firewalls, net proxies, domain controllers, intrusion detection systems, and VPN servers. Whereas this information is often used for compliance and rhetorical investigation, it additionally contains a wealth of knowledge regarding user behavior that holds promise for police investigation stealthy attacks.

Big Data Tools for Cybersecurity

Apache Spark

Apache Spark is a fast engine for data processing on a large scale. It is an open source cluster computing framework. Apache Spark can help cybersecurity officers analyze data and answer questions:

  • Which internal servers of the company are trying to connect to internationally based servers?
  • Has user‘s access pattern to internal resources changed over time?
  • Which users exhibit irregular patterns of behavior such as connecting using non-standard ports?

Spark powered big data discovery solutions can be used to detect anomalies and outliers within large datasets. Visualization techniques help when Large amounts of data i.e. petabytes of data is to be examined.

Fort scale

Services Fort scale is a big data solution against APT attacks. APT attacks can take place over a stretched period of time while the victim organization remains ignorant about the invasion. According to Fort scale, big data analysis is a appropriate approach for APT recognition.

  • A challenge in detecting APT is the massive amount of data to examine through in search of abnormalities.
  • The data comes from an ever-increasing number of miscellaneous information sources that have to be audited.
  • Fort scale uses Cloudera Hadoop distribution to address big data challenges and examine network traffic data to check for invasions if any.
  • Fort scale employs data science techniques like machine learning and statistical analysis to adapt to changes in the security environment.

IBM Security Radar

This tool uses big data capabilities to help keep pace with advanced threats and prevent attacks proactively. It uncovers hid connections inside huge amount of security information, utilizing examination to lessen billions of security occasions to a controllable arrangement of organized occurrences. It uses the following features of Big Data solution:

  • Real-time correlation and anomaly detection of security data, which is diverse in nature.
  • High-speed querying of security intelligence data.
  • Flexible big data analytics across structured as well as unstructured data – this includes security data, email, document and social media content, business process data; and other information.
  • Graphical front-end tool for visualizing as well as exploring big data.


Big data technologies are changing the whole world, everything from internet of things to gathering both more qualitative and more quantitative data will lead to better decision-making and insight. By utilizing enormous information innovations successfully, associations can be more proficient and more focused. Privacy advocates and data organizers criticize the history of big data as they watch the growing ubiquity of data collection and increasingly tough uses of data enabled by powerful processors and boundless stockpiling. Scientists, business, and business visionaries firmly point to concrete or anticipated innovations that may be dependent on the default collection of large data sets. Also, the quick growth of the internet has bought with it an exponential increase in the type and frequency of cyber-attacks. Many well-known cyber security solutions are in place to counteract these attacks.

The huge argument today is how should privacy risks be weighed against big data rewards? Especially the recent controversy over leaked documents revealing the massive scope of data collection, analysis. Big data makes gigantic shot for the world economy in field of security, as well as in promoting and credit chance investigation to restorative research and developed arranging. In the meantime, the startling advantages of huge information are tempered by worried that advances of information biological community will turn over the power connections between government, business and people, and prompt racial or other profiling. Isolation over criminalization, and other bound adaptabilities. At long last: It is extremely essential to comprehend the security and protection suggestions coming about because of huge information executions supporting non-data security capacities. Specifically, security required executives should be aware of who Big data increases attack surface of hackers and understand how to protect against link ability threats.

Remember: This is just a sample from a fellow student.

Your time is important. Let us write you an essay from scratch

experts 450+ experts on 30 subjects ready to help you just now

delivery Starting from 3 hours delivery

Find Free Essays

We provide you with original essay samples, perfect formatting and styling

Cite this Essay

To export a reference to this article please select a referencing style below:

Big Data Analytics In Cyber Security. (2019, April 26). GradesFixer. Retrieved August 16, 2022, from
“Big Data Analytics In Cyber Security.” GradesFixer, 26 Apr. 2019,
Big Data Analytics In Cyber Security. [online]. Available at: <> [Accessed 16 Aug. 2022].
Big Data Analytics In Cyber Security [Internet]. GradesFixer. 2019 Apr 26 [cited 2022 Aug 16]. Available from:
copy to clipboard

Where do you want us to send this sample?

    By clicking “Continue”, you agree to our terms of service and privacy policy.


    Be careful. This essay is not unique

    This essay was donated by a student and is likely to have been used and submitted before

    Download this Sample

    Free samples may contain mistakes and not unique parts


    Sorry, we could not paraphrase this essay. Our professional writers can rewrite it and get you a unique paper.



    Please check your inbox.

    We can write you a custom essay that will follow your exact instructions and meet the deadlines. Let's fix your grades together!


    Hi there!

    Are you interested in getting a customized paper?

    Check it out!
    Don't use plagiarized sources. Get your custom essay. Get custom paper

    Haven't found the right essay?

    Get an expert to write you the one you need!


    Professional writers and researchers


    Sources and citation are provided


    3 hour delivery