Critical Information Infrastructure Protection Techniques Implementation Against Cyber Attacks Using Big Data Analytics (a Case Study of Inec and Jamb).
In 2016, BT, the telecoms company that owns and maintains the physical infrastructure that makes up the UK’s broadband network, experienced an outage of a portion of its broadband services, causing hundreds of thousands of customers (including businesses) to lose Internet and phone connections for approximately two hours (Williams, 2016). This was the largest and most extensive network breakdown in years, according to the news item. Despite the fact that the corporation denies it and blames the network outage on a malfunctioning router, it has been speculated that the outage was caused by a cyber-attack. Whether or whether BT’s explanation for the outage (a malfunctioning router) is correct, the point is that it is definitely feasible to conduct a cyber-attack that may bring an organization’s infrastructure down. What if this was a cyber-attack that affected more routers and lasted days rather than hours? Can you picture the devastating effects on the country’s economy, not to mention the lives lost when emergency services lost communication? On October 19, 2020, IBM researchers discovered vizom, a new type of stealthy malware that targets Brazilian account holders using remote overlay assaults [Guillermo, 2014]. It is currently being used in a campaign in Brazil that aims to compromise bank accounts through online financial services. Due to the coronavirus pandemic, Vizom poses as a popular video conferencing software, which is now critical to businesses and social life [Brewer, 2021]. The problem with such attacks is that they can eventually lead to a cascading failure of inter-bank funding, triggering a tipping point for a broader systemic liquidity crisis. In both of these scenarios, the organizations’ operations are so intertwined with other organizations in their respective countries that their failure will inevitably trigger a domino effect, causing these other or related organizations to fail. As a result, the safeguarding of such infrastructures, also known as critical information infrastructures, is seen as a national security issue.
1.1 Background of the study
Cyber-attacks are constantly making headlines, putting countries, industries, and businesses at danger of security breaches. With society’s reliance on technology and the introduction of the internet of things, things could get even worse. Cyber criminals are growing more smart and knowledgeable, as seen by the fatal software they use to attack businesses. In the year 2020, hackers used stealthy malware to infiltrate Solar breezes (a United States-based firm that provides network monitoring and other technical services to thousands of companies, including government agencies), and injected malicious code to the firm’s software system. Companies utilize the Orion system to manage their information technology resources. The code provided a backdoor into the customer information technology system, which hackers used to spy on businesses, organizations, and government agencies. Because critical information is exposed to the hackers, a hack of this magnitude has a global impact.
Information on healthcare, the electricity grid, disease management, and military operations that might be used to destroy a country. How does one protect against such assaults? Is big data analytics the way to go? We’ve seen a significant rise in data volume over the previous few years. Global IP traffic reached an estimated 1.2 zettabytes in 2016, according to Cisco Systems. Global IP traffic refers to all digital data that travels over an IP network; it is expected to exceed 20 zettabytes by the end of 2021. Data is collected from a variety of sources, including contracts, call centers, social media, and phones. Interactions between faxes, for example. This data could be very useful in detecting fraud. Large corporations are increasingly using big data analytics for cyber-security and defense because it allows them to see bigger and clearer pictures when detecting threats. As a result, a study of the effectiveness of big data analytics – for cyber-attack detection will be conducted in this research. This would be done by looking at the success rate of employing the technology to detect sophisticated and stealthy cyber-attacks like Advance Persistent Threats (through a surveyBy questionnaire).
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Given that stealthy malware is designed to go undetected and that an attack can compromise a computer system in seconds (Brewer, 2015), the term “effectiveness” is defined as: having a detection speed of seconds, minutes, or hours, but no more than a day, as a day may be too late; being able to detect stealth attacks significantly more often than not – at least 75%
1.2 Problem Statement
The internet is a global network of interconnected systems which serves billions of users worldwide. Its popularity and rapid growth have come at an expensive cost, i.e., loss of information and resources due to cyber threats and attacks. The first cyber crime was reported in 2000 and infected almost 45 million internet users (Message Labs Intelligence, 2010).
Over the few past years cybercrimes have increased rapidly with cyber criminals continuously exploring new ways to circumvent security solutions to get illegal access to computer systems and networks. Some important cyber attacks includes spamming, Search Poisoning, Botnets, Denial of Service (DoS), Phishing, Malware, hacking, etc
The Importance of protecting Critical Information Infrastructure cannot be overemphasized due to the catastrophic nature of such attacks to Governments, Attacks of such manner can be devastating and lead to a domino effect of disaster. This cyber-attacks often disguises in form of stealthy malware in attacking critical information sectors such as defense, food and agriculture, financial services, oil and gas, public health care, transportation etc. either to steal information or disrupt the normal operations of a government.
The extensive damage caused by these cyber attacks has lead to the design and implementation of cybersecurity systems. Cybersecurity refers to the techniques, processes and methodologies concerned with thwarting illegal or dishonest cyber attacks in order to protect one or more computers on any type of network from any type of damage.
This research proposes to address how critical information infrastructure can be protected against cyber-attacks using big data analytics.
1.3 Aims and Objectives of the study
The The main aim of this study is to investigate the implementation of critical information infrastructure protection techniques against cyber attacks using big data analytics. Specifically, the study seeks to:
- Investigate the efficacy of big data analytics as a protection technique.
- Examine the extent of big data analytics implementation in government agencies.
- Elucidate on the challenges in implementing big data analytics as a protection technique.
1.4 Research Questions
The following questions guide this research:
- How effective is big data analytics as a protection technique?
- What is the level of big data analytics implementation in government agencies?
- What are the challenges militating the implementation of big data analytics protection technique?
1.5 Research hypotheses
Hypothesis refers to an experimental statement, tentative in nature, showing the relationship between two or more variables. It is open to test and can be accepted or rejected depending on whether it agrees or disagrees with the statistical test.
The study will test the validity of the following null hypothesis:
H01: Big data analytics is not effective as an information protection technique.
H02: There is no significant implementation of big data analytics in government agencies.
H03: There are no significant challenges impeding the implementation of big data analytics.
1.6 Significance of the study
Big data analytics as a cyber attack information prevention technique is a tool capable of curbing cybercrime due to the fact that it focuses on studying trends or patterns in which this attacks occur which in turn give organizations how to protect critical information and data. The greatest threat to network security procedures is that everyday hackers develop new malicious software and hacking techniques and no single software can practically keep up with the amount of threat. The aftermath of an initial breach in a system’s network is often not helped by modern cyber security measures because of the way this cybersecurity measures are designed.
This study will be of immense benefit to both private and public agencies to first come to the understanding of the height of havoc cyber threats could cause to their databases. This study will also help organizations to identify the various information protection techniques to apply in other to combat and secure their data from cyber theft.
This study will further introduce to organizations under different sectors in Nigeria such as the banking sector, educational sector, insurance etc the benefit that comes with the adoption and implementation big data analytics as a prevention technique against cyber attacks such as helping organizations in providing the path in revolutionary transformations in several fields like inventions, marketing statistical status, etc. Helping big organizations in analyzing big data to achieve good raw data from it. It makes work easy and examines all the information available and provides only the required data needed by the organization.
This study will further add to existing literature on this study topic and as well serve as a reference material to students, scholars and researchers who may which to carryout further study on this topic or related domain.
1.7 Scope of the study
This study focuses on investigating the efficacy of big data as a protection technique. Also, this study will look into the extent big data is being implemented in government agencies. The study will further examine the challenges countered in implementing big data analytics as a protection technique.
Furthermore, the findings of this study will be restricted to the government agencies due to their high need of information protection against cyber theft. Joint Admission and Matriculation Board (JAMB) and Independent National Electoral Commission (INEC), Abuja serve as the enrolled participants for this study.
1.8 Limitation of the study
The major limitation to the study are insufficient fund to involve many respondents to this research and carry out other logistics required in this study. Also, time factor was another constraint where the researcher had to share available time with academic work and conducting of this research within the given time frame.
Inadequate materials needed for the success of this study was another factor that limited this study. The researcher was denied access to some information from the respondents when interviewed as such information was target “official” for security purposes. This made the sources for literature and conducting of interviews a bit difficult as hence posed a barrier to the researcher.
Furthermore, this study focused mainly on studying Big Data Analytics (BDA) as a major information infrastructure protection techniques against cyber attacks instead of exploring and evaluating other information infrastructure protection techniques that could as well serve same purpose as that of Big Data Analytics (BDA). Also, the respondents of this study was another limitation to this work because the study was not carried out in many or all sectors of the Nigeria economy in order to generate more valid facts for better conclusion for this study.
However in the midst of the above mentioned limitation the researcher devotedly ensured that the purpose of the study was actualized.