The case study mainly deals with the threats and the security issues associated with big data. Big data mainly deals with the storage of large amount of data that can be accessed by public to be used in business purposes. The use of big data can offer significant benefits to the business and organizations (Wu et al., 2014). However, there are different security issues associated with the use and access of big data, which ultimately results in data breach and loss of data. This case study deals with the threats associated with ENISA and the key threat agents involved in this. The report discusses the process of elimination of threat from the system. Furthermore, it discusses the different security issues associated with ENISA and the key threat agents along with the threat infrastructure. The impact of these threat and the threat mitigation process is discussed in this report (Inukollu, Arsi & Ravuri, 2014). The detailed analysis of different aspects of the case study is elaborated in the following paragraphs.
A brief overview of the ENISA case study and the infrastructure diagram of ENISA is elaborated and illustrated in the following paragraphs-
The case study focuses on the big data, its increasing implementation and use along with the threats associated with it. The increasing data and security breaches is an alarming issue in today’s world and therefore proper measures are to be taken in order to curb it (Wright & De Hert, 2012). The case study elaborates the threats associated with the technology of big data, which has a significant role in affecting the various aspects of the society. The impact of big data is huge in the thriving data driven economy. Big data has increasing use in different fields such as in military applications, fighting terrorism and also in research work ( ENISA 2017). Therefore, this technology offers numerous advantages and is considered as a major source of information. However, this source of information is exposed to different threats and attacks by different threat agents that are discusses in the report. The big data systems can be widely used in different applications. The case study aims at deepening the understanding the threats and recommendations of eliminating the threats. The case study further aims at suggesting different risk management strategy for eliminating the risks and threats associated with big data. The case focuses on the use of cloud storage as the major data storage system of big data. Cloud storage is however associated with different types of risks and security issues that need to be considered in order to eliminate the risk of data breach and data loss. The case study report also elaborates the big data architecture, which is a high-level conceptual model that that demands certain security requirements in Big Data. The different layer of big data infrastructure consists of different data sources, data storage, computing models and presentation (Gonzalez et al., 2012). The big data asset taxonomy elaborated in the case study gives an overview of the big data assets and structure. The major component of big data assets includes big data analytics, security and privacy techniques. The different threat identified in the case study is mapped in the big data asset. The infrastructure diagram of ENISA along with the threat associated with it is illustrated below.
Figure 1: Representing the ENISA big data security Infrastructure
(Source: created by author using MS Visio)
The storage of huge amount of data is associated with different security threats. Attackers plan and implement these attacks in order to gain access over voluminous amount of data. the top threats associated with ENISA are listed below ( ENISA, 2017)-
1) Leak of data due to the use of unsecure APIs: Big data is built with very little security and data breaches due to unsecure APIs are very common. Different injection attacks can be launched with by making use of unsecure APIs and therefore this is considered as a mojor threat in big data.
The assets that are mainly targeted by this threat include data, big data analytics, software and computing models.
2) Inadequate or improper designing of the security system may lead to arrival of number of threats. The techniques used in fusion of heterogeneous data sources increases the redundancy in data representation and therefore, managing the data becomes impossible. This redundancy in data increases the probability of data disclosure and data leaks as the managing of data becomes impossible (Theoharidou et al., 2013).
The assets that are mainly targeted by this threat include data and applications.
3) Denial of service attack: Denial of service attack mainly aims are making the resources unavailable for the authorized users. This is implemented by exploiting the vulnerabilities associated with the system and as a result of DOS, the performance of the system also decreases (Tan et al., 2014).
The assets that are targeted by this attack include servers and networks.
4) Malicious code and software activity: The most significant threat associated with big data is mainly due to the malicious code and software activity. The different threat agents of this threat include ransomware, Trojan horses, works, trapdoors, spoofing and viruses. These threat agents are infused into the system with the help of a malicious codes and programs (Theoharidou, Tsalis & Gritzalis, 2013). After the threat is installed in the system, the attacker gains access of the entire system and therefore, the risk associated with this particular threat is very high. These threats easily spread from system to system and therefore it must be eliminated with highest priority (Seshardi et al., 2012).
The assets that are mainly targeted by this threat consists of database and computing infrastructure models.
5) Use of rogue certificates: generation of rouge certificate in order to gain access to certain devices is a significant threat in big data. this can result in data theft, data manipulation, data leakage and the misuse of data (Pearson, 2013).
The assets that are mainly targeted by this particular threat includes software, hardware and associated data.
6) Interception of Information: The attackers can intercept the transfer of data among the different nodes mainly by making use of communication links is a prominent threat.
The assets that are mainly targeted by this threat includes data, application and back end services.
7) Identity fraud: Accessing the data impersonating someone else gives rise to the threat of identity fraud. This is a significant issue because the it mainly deals with the loss of personal information (Roberts, Indermaur & Spiranovic, 2013).
The assets that are targeted by this threat include personal identifiable information and back end services and servers.
The top threats that are discussed above results in a considerable data security risks in big data. Out of them, the threat due to malicious program and activities is most significant. This is because this type of threat can easily spread from system to system and with the installation of the malicious code, the attacker can gain access to the whole system. Hacking is one of the major source of injecting malicious code into the system (Chen & Zhao, 2012). This is most significant because the attacker after gaining the access to the system can easily modify and manipulate the data. The attacker can make use of those data for personal benefits thus giving rise to significant threat and data leakage. This threat or risk should be eliminated from the system with immediate concern in order to eliminate the risks associated with the big data. Implementing a proper intrusion detection system can further help in eliminating the risks of hacking (Pavlyushchik, 2014).
The top threat agents, the impact of the threats associated with big data and the threat probability of ENISA are elaborated is listed below-
1) Corporation: One of the major threat agents associated with the security concerns of big data is the corporation or organizations that use ill techniques of data manipulation and stealing of data in order to gain competitive advantages.
2) Cyber criminals: This is one of the most dangerous threat agent associated with the privacy issue of big data. The cyber criminals gain access of the big data by different techniques mainly for financial benefits. They can intrude into the system with an intention of data stealing and therefore proper risk management strategies are to be implemented to secure these data.
3) Cyber terrorists: The cyber terrorists are similar to cyber criminals but the effects of their attack are wide spread. The main target of cyber terrorists are critical infrastructures and large organizations. Cyber terrorist mainly target these organization as any impact or effect over these organization can cause severe impact over society as well (Taylor, Fritsch & Liederbach, 2014).
4) Script kiddies: These threat agents are not very dangerous as they make use of already developed codes and programs in order to launch an attack. Therefore, the effect of these attacks are very negligible and the risk associated with this threat agents can be easily avoided.
5) Hacktivists or online social hackers: These threat agents mainly target hig profile website to promote their views. Computer systems are used in order to launch and execute an attack.
6) Employees: Employees of an organization can be a major threat agent as well. This is because they possess a good knowledge of the data and security system of an organization and make use of that knowledge to launch an attack. Data manipulation cannot be a hard task for an employee of an organization and therefore they are considered as a major threat agents.
7) Nation States: These are most dangerous threat agents out of the discussed threat agents. Nation states are sophisticated cyber criminals and are associated with launching a well planned attack using the modern tools and techniques. This attacker have high level skill and expertise and therefore considered as a significant threat agent.
Minimizing the impact of the threat is essential in order to eliminate the security and the privacy issues associated with the system. The different measures that can be undertaken in order to eliminate the risk are listed below-
1) Access control is an important aspect of data protection by preventing the unauthorized access of data. Since the storage of big data involves storage of data in cloud, it is vulnerable to a number of attacks and therefore access control may considerably help in data protection (Brucker et al., 2012)
2) Limiting the use of data using modern cryptographic techniques and proper encryption is another suggested method of data protection (Stallings & Tahiliani, 2014).
3) Implementing better and effective security systems is essential for preventing the intrusion into the system.
4) Training the staffs and users of an organization in order to generate awareness among the employees about need of information security is essential for data protection.
The threat associated with the use and access of big data in increasing considerably as the attackers are coming up with different ways of implementing an attack into the system. The threat probability is needed to be reduces in order to secure the big data. different security measures can be implemented in order to protect this data. the threats are becoming more dangerous and hence, curing it from the roots becomes essential.
ENISA threat landscape or ETL reports about the different threats associated with an organization. The report mainly deals with the threats associated with the information and communication technology asset (ENISA, 2017). The major drawback of this ETL is that it only discusses the threat associated with the big data. The threats and the threat agents have evolved with time and therefore the report should contain a more detailed structure of the threats and the consequences. The EYL can be improvised by incorporating a detailed overview of the threats associated with the big data and its use (Cherdantseva et al,. 2016).
The ENISA organization is not satisfied with the current IT structure of the organization as there are number of threats associated with the security system. The security essentials are needed to be updated and stronger security features are to be incorporated into the statement. With the increase of a number of threats and their sophistication, a stronger security infrastructure is essential. The report discusses the number of different security measures that can be implemented (Von Solms & Van Niekerk, 2013). The major drawback of the current security system is that it cannot filter the redundancy of data which gives rise to a number of threats. Different risk management strategies can be implemented to eliminate the risks associated with the IT security system of ENISA. The use of insecure APIs can be avoided in order to eliminate the risk of intrusion into the system. Furthermore, proper intrusion detection system and firewall can be implemented in order to protect the data (Albakri et al., 2014).
Conclusion
Therefore, from the above discussion it can be concluded that the IT security structure of ENISA should undergo improvisation. The report identifies the major threats associated with the system and the threat agents. The report further suggests the different techniques to minimize the risks associated with the system. The major threats agents are identified in the report that are responsible for implementing an attack. Big Data has increasing use in today’s world and therefore the security essentials of big data should be thoroughly improvised in order to protect the data.
Reference
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Big Data Threat Landscape — ENISA. (2017). Enisa.europa.eu. Retrieved 6 September 2017, from https://www.enisa.europa.eu/publications/bigdata-threat-landscape
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