The Role of Big Data Analytics in Modern Cybersecurity: A Report

This report provides a comprehensive overview of how big data analytics is transforming the field of cybersecurity. It begins by defining big data and its characteristics, emphasizing its velocity, veracity, and variety, which are crucial for analyzing vast amounts of security-related data. The report highlights how big data analytics improves cyber defense by identifying and mitigating risks, detecting anomalies, and responding to threats. It discusses the use of big data analytics in risk management, including risk identification, assessment, and mitigation. Furthermore, the report examines how big data analytics enhances resistance to cyberattacks by providing timely and accurate actionable decisions. It also addresses the role of big data in decreasing vulnerabilities in existing technology applications and acknowledges that attackers also leverage big data analytics. The conclusion emphasizes the importance of big data analytics in creating intelligent defense systems in cybersecurity, supporting the need for advanced data analysis techniques.

Big Data Analytics – An Emerging Application of Technology
Introduction
Big data analytics is current trend of the data analysis that brings the most valuable information
for which the big data are used in analytics processes. Big data is defined as the data having the
properties of velocity, veracity, variety. Big data is generated in millions of bytes per second so
that it contains every piece of information. Big data analytics is showing the abundant scope to
improve the cyber security. US government survey stated that 84% of respondents declined the
security breaches by the help of big data in blocking the attacks. The company that has the huge
analytics users have much of the confidence that to use of analytics to detect the threat of
cyberspace (Hussain, & Roy, 2016). The article ITWire states that most eleven common cyber
threats, the biggest gaps concerning the ability of the organizations to detect advanced malware
and ransom ware compromised devices. There is need of the risk management and intelligent
action oriented. This is common with the big data analytics to manage risks and provide
intelligence actionable item to make cyber defense.
Cyber security positive implication of the selected technology such as big data analytics are
stated with following points.
 Big data analytics provides the intelligent mechanisms to analyzed the relevant security
related data to find out the effective and robust cyber defense mechanism
 The solution of security breaches are identified and employed timely when the big data
analytics is used to find out the defensive solution.
 Big data analytics enhances the confidence of analysts by providing much scope for
finding the appropriate solution for the given security issues and braches.
Characteristics of Big data Analytics Technology
Big data analytics is characterized as a process to analyze the various facets of the system to get
the desired outcomes. There are so many tools and technology available to execute the analysis
process. In case of the cyber security big data provides the risk identification, risk assessment to
develop the intelligent defensive mechanism or application to protect the informational assets of

the consumers and businesses. Big data analytics has tools which provides the help in analysis of
data with automated task. Due to this fact of big data timely result of the actionable system or
mechanism is derived from the large volume of data by applying the effective process of
analytics. The analyst of big easily classify and categorize the threats in time which assists the
quick decision for the defensive action behind the discovered threat.
Big Data Analytics Use to Improve Cyber Security
Technology such as big data analytics quickly solves the issues and problems associated with the
cyber security industry. Big data and its analytics allows the security industries such as Norton,
Semantic, and Kaspersky, etc to identify the anomalies and advanced attack vectors (Leenen, &
Meyer, 2016). For example, SentinelOne uses the machine learning paired with cloud
intelligence and automated response to detect the malicois activity and when there is need of
response then it respond.
Big data analytics technology make the intelligent and automated aware defense mechanism in
the defense application to detect all malicious activities and take automated action to prevent the
damage of the information assets of the users. The PDR (Prevent, Detect and respond) system of
security mechanism becomes too robust and effective by the help of big data analytics.
Big Data Analytics to Manage Risks
Risk management includes the risk identification, risk assessment, and risk mitigation. These
three pillars of risk management by the help of big data analytics are efficiently carried out.
Large volume and variety of data increase the scope to identification of risk. The relevant
security breach data and other security related data stored in data warehouse are taken to analyze
the attack vectors and find out the pattern of attacks. This helps the findings of finer aspects
related with the security breaches by attack process analysis.
The known pattern of attacks and security vulnerabilities are effectively analyzed and scope of
the identification of risks are enhanced by the big data analytics technology. Massive data
processing by big data analytics also maximize the possibility of risk identification. Today, the
big data analytics technologies are so advanced that can automate whole analytics processes to
detect the risk and vulnerability of the cyber system. Whenever the risks are identified the

assessment of risks becomes easy and further deployment of mitigation technique is again
identified through the extracted patterns of attack vectors by the big data analytics.
Big Data Analytics and Increase of Resistance to Attacks
At present day, the cyber security demands a new generation of cyber defense tactics. The
attackers are more trained and well funded. They are more advanced cyber criminals by applying
the advanced methodology to hack the sensitive and vital information of consumers and
businesses. The effective defense mechanisms do not prevent them to protect the information
system. It is also obvious that the business and consumers interactions become higher on online
virtual Interface where the non secured network such as Internet is used as a platform of
communication (Elder, 2015).
Big data analytics provide the more accurate, timely and appropriate actionable decisions for
cyber security and management of information technology. Big data extends the automated
defense and mitigation techniques through the new applications or by old applications having
modified state of functionalities. Threat analysis, vulnerability analysis and identification are
properly conducted through the big data analytics. The probability of threat and vulnerability
identification is increased when big data analytics produces the intelligent system to detect. The
attacker mission, network monitoring, network management visualization and cyber training are
comprehensively covered by the big data analytics. This enables the effectiveness and suitability
for identification and mitigation of the threats of cyber security timely and automatically.
Big Data Analytics to Decrease Vulnerabilities in Existing Technology Application.
The existing technology applications lack the intelligent and automated behavior of defensive
mechanism. Big data analytics induces the intelligence in the existing application by adding
more accurate and effective solution for vulnerability identification and then prevention of
security attacks. A large volume of vulnerabilities are analyzed with respect to the attack profile
to get the most common aspects and similarity conditions of attacks (Everett, 2015). The pattern
analysis again provides the suitable information related with the attack scenario and scope with
the information system in cyber security field. Therefore, big data analytics proposes the
modifications in existing system or applications to become more prevalent for the defense in the
field of cyber security.

Big Data Analytics Exploitation by Attacker
Attackers are also too much intelligent to employ the big data analytics to identify the security
applications mechanism for defense against the attack (Joglekar, & Pise, 2016). They also
makes analysis of the application actionable profile and tactics by employing the big data
analytics. Hence, with respect to the cyber security big Data analytics has positive and also
negative impacts in the field of cyber security.
Conclusion
The technology is advancing day by day. Big data analytics is a data science technology by
which the analysis of data and patterns are performed to get the finer details. The output or
outcomes of analytics are taken to deploy with the system or application to act accordingly. In
the field of cyber security big data analytics provides the huge support to make intelligent
defense system for the cyber security. Attacker also use the big data analytics to find out the
attacking mode with robust security system in the area of cyber security.
Reference
Hussain, A., & Roy, A. (2016). The emerging era of Big Data Analytics. Big Data
Analytics, 1(1). http://dx.doi.org/10.1186/s41044-016-0004-2
Leenen, L., & Meyer, T. (2016). Semantic Technologies and Big Data Analytics for Cyber
Defence. International Journal Of Cyber Warfare And Terrorism, 6(3), 53-64.
http://dx.doi.org/10.4018/ijcwt.2016070105
Elder, J. (2015). A new training program in data analytics & visualization. Big Data And
Information Analytics, 1(1). http://dx.doi.org/10.3934/bdia.2016.1.1i
Everett, C. (2015). Big data – the future of cyber-security or its latest threat?. Computer Fraud &
Security, 2015(9), 14-17. http://dx.doi.org/10.1016/s1361-3723(15)30085-3
Joglekar, P., & Pise, N. (2016). Solving Cyber Security Challenges using Big Data. International
Journal Of Computer Applications, 154(4), 9-12. http://dx.doi.org/10.5120/ijca2016912080