Introduction
The term big data is a field that treats ways to evaluate and extract data from data sets that are too large. It is an advanced technology that is now used in companies for obtaining reliable data and solving data management related issues. In this generation numbers of companies are using big data technology in order to predict model and manage complexity related issues (Kantarcioglu, 2019). There are major three characteristics of big data including volume, variety, and velocity. The key intention of this paper is to evaluate the concept of big data and identify access control challenges linked with the big data. There are three major sections that will be included in this paper, for example, big data and its analysis, access control challenges for securing big data and approaches used to secure big data systems.
Big data and its analysis
It is determined that big data is a combination of structured, unstructured and semi-structured data obtained by the companies which may be used for predictive modeling, machine learning, and other analytics processes. The term big data evaluates the large and complex volume of data which can be evaluated in order to gather effective value (Zhang, 2018). From a recent study, it is found that big data contains three V-properties including velocity, volume, and variety.
In this generation, big data has become capital with enterprises enhancing their consumer relations and operations in an appropriate manner. Big data is often characterized to have numerous data involving semi-structured, structured and unstructured. Traditional approaches like access control or role-based access control may soon become cumbersome and unmanageable due to numerous granularities. It is observed that in the case of big data term volume is the amount of data matters that may be data of undefined value, for example, clickstreams, Twitter and many more.
Moreover, velocity is the best rate at which gathered data is obtained and evaluated in a reliable manner. In big data, the term variety is defined as the numerous kinds of data that are available in the database. Current data types were structured and fit the interpersonal database systems. By increasing the use of big data technology companies are capable to manage both structured and unstructured data and gather effective information. It is argued that using big data technology companies can address numerous business activities and handle a large number of data sets in an appropriate way.
Big data analytics is the often complex procedure of determining larger and reliable data sets from the networks. Such kind of process helps the companies to develop informed business decisions and handle complex data sets effectively. From previous research, it is found that big data analysis is a form of advanced analytics that mainly includes complex applications with elements like predictive models and statistical source codes. Big data examine larger numbers of data in order to uncover hidden patterns and other insights and provide a way for analyzing the complex data effectively.
Gruschka, et al., (2018) described that big data is a kind of technology which is mainly used in the business in order to analyze a huge amount of data. Companies obtain data from various sources including social media, digital images, sensors, and other sources. In this generation, the usage of big data is increasing quickly due to their capability to provide better outcomes and effective data to the companies. It is observed that big data has the potential to evaluate the huge volume of transaction data and other data resources that current business communities would be not able to handle. Due to the lack of proper resources and approaches companies are not able to handle larger data sets but the involvement of big data technology will help to manage both structured and unstructured data effectively.
Access control challenges for securing big data
It is observed that controlling and managing security risk is a major challenge linked with the big data due to which companies are not able to handle privacy-related issues and data breach problems. Recent journal paper indicates that leakage of big data can result in enormous monetary loss and produces financial issues in the companies. Kantarcioglu and Ferrari, (2019) argued that lack of security is the key challenge associated with the big data technology due to which users may suffer from the cybersecurity attacks and threats. It is true that the utilization of third party networks and fraud systems may produce privacy risks in the big data and companies are not capable to reduce unwanted signals from the systems. There are numerous challenges associated with the access controls which are described below:
Privacy risks
While consumers enjoy the convenience brought by big data technology, they also encounter numbers of inconvenience in the systems and produce hacking related issues. If big data is not well protected for consumer data in the process of usage, it will directly threaten the security of consumers and the privacy of data. According to Colombo, and Ferrari, (2018), there are major three factors that lead security issues in the big data technology such as lack of privacy, the involvement of third-party networks and unauthorized networks. It is very significant for the consumers to use only secured networks as the criminals are capable to produce fraud signals and access the sensitive data of the consumers.
In this modern generation, numerous companies are suffering from privacy risks while using access control of big data technology and systems. Information is processed anonymously; the hackers have the potential to access personal information and block communication networks. There are major three privacy risks occurred in the big data technology, data breach, hacking, and cyber-attacks. In this generation, china still lacks rules and regulations for consumer information under the era of big data and it does not have a better supervision system. It is observed that lack of self-protection between consumers is the key issue associated with the access control big data that directly impact on the organizational performance and sensitive data.
Big data credibility needs to be confirmed
It is observed that data used by the companies may be structured and unstructured and the involvement of fraud networks may produce risks in the systems. Most of the hackers use malware software in order to collect information and block computing networks used in big data systems. Criminals are capable of intentionally fabricating and forge data into systems which may lead to security-related risks in the companies (Krishnan, 2014). It is determined that if the data utilization is more effective or specific, several consumers can make up the information for developing data illusions which are beneficial to them may lead consumers to produce wrong judgments.
Malware attack
It is one of the biggest challenges linked with the big data technology where the criminals develop unwanted signals and frauds in order to perform data breach. Mainly, malware attack uses unauthorized networks and attack on the computing devices and databases of the companies in order to access personal information. From a recent study, it is found that most of the hackers use malicious tools and develop high-level source codes for blocking networks linked with the big data and gather relevant information.
The companies are using less secured networks and systems while developing access control big data which directly impacts on the databases and sensitive data. Controlling and addressing malware signals and unauthorized access both are major challenges faced by the management that also lead to data breach issues in the systems. Therefore, it is important to manage unwanted signals and collect data from only secured sources in order to address such kind of cyber-attacks and threats.
Accountability issues
As machine learning affects more and more aspects of society, it becomes crucial to evaluate and understand how developed systems change the way of decisions. It is observed that the lack of transparency in the field of data-driven may easily conceal fallacies and issues codified in the underlying mathematical frameworks. A recent study determined that the accountability of big data is a key challenge faced by the companies and it is complex to understand unstructured data and obtain reliable decisions or information (Hu, and Vasilakos, 2016). Access control big data provides a way to manage a large amount of data but it may produce accountability related issues while using in the business.
Approaches for securing big data
There are numerous approaches and methods that can be used by the companies in order to solve issues or risks linked with the big data and enhance the security of developed networks. These approaches are described below:
Fully supervise data in social networks
It is observed that online media has become the most effective platform for performing data communication and transmission and many companies collect data from social networking sites. So, it is very significant to strengthen the supervision and evaluation of data in order to protect information from risks and threats. Moreover, in order to develop supervision and management of social data companies should ensure that private data security is not exploited by the attackers and causes larger data losses. Manogaran, Thota, and Kumar, (2016) reported that for increasing consumers’ awareness of security and reducing the filling of private data, self-prevention and vigilance pitfalls are also required from the perspective of data security. It is argued that management should develop effective policies and rules in order to use big data technology in the business and adopt legal security rules or regulations.
Enhance the security protection legal mechanism
In this advanced generation, consumers and companies pay more attention to security and data breaches as the rate of cyber-attack is increasing day by day. Using big data networks in the business is a crucial strategy due to the lack of proper security for which management can enhance the privacy protection rules and systems and provide proper information to the employees about cyber-attacks and issues. Currently, there is no law that significantly secures personal information in management. Therefore, for performing effective data communication and management government should develop better laws and regulations related to the security of data.
Develop a privacy protection agency
Many countries have developed special security protection agencies for protecting consumer’s private data and files from criminals. By developing a security protection agency, the government can change the behavior of consumers towards cyber-attacks and help companies to address security risks using big data technology (Dwivedi, and Vyas, 2016). Analysis of the latest development in China, although the association has implemented useful departments in order to protect data from security issues, for example, the Public Security Bureau and so on, but security protection is the only one that is not valued. So, it is important to develop and implement a professional security protection agency in order to handle data breach issues and manage the large volume of data effectively. Moreover, companies can implement effective security strategies in the workplace and adopt the IT security team for handling IT infrastructure and manage unwanted signals from the systems.
Enhance consumer’s awareness and quality of data
With the incessant progression of the big data sectors, the rate of data has increased effectively and many consumers are using social platforms for performing data communication. Consumers require adapting to changes in the times and gradually enhancing the security of their data along with the awareness. In this generation, most of the users do not know about cyber-attacks and data breaches for which the government can design and implement education programs and provide reliable information related to cyber-crimes. Data awareness is generally linked to the public and needs to evaluate and analyze the significance of big data (Gahi, Guennoun, and Mouftah, 2016). Do not randomly issue data concerning their own security on the internet and social networks, so that they are not exploited by the hackers and easily manage the privacy of data.
Provide training and education to the employees
It is observed that the lack of proper training is a major issue linked with the consumers and workers in the organization due to which hackers can easily enter into the systems and perform hacking related activities. Therefore, it is necessary for the management to design and implement training programs in the workplace and provide complete information to the employees. Moreover, management can adopt an IT team for better explaining key factors leading to data breach and hacking issues in the systems. Lv, et al., (2017) provided their views on big data and suggested that employees should ensure that they use only secured networks and servers while gathering data from social networks and avoid the involvement of unauthorized networks. Many criminals transfer unwanted signals to the computer systems for which management should provide complete education to the new joiners for handling security-related risks and threats.
Install firewall and antiviruses
It is argued that the utilization of computing devices and networks require security tools for detecting unwanted signals from the systems. Therefore, companies can use firewalls and antivirus tools in order to handle the fraud signals from the networks and enhance the security of big data. A firewall is a kind of security tool that has the potential to identify spam and viruses from computing devices and protect big data against cyber-attacks and threats (Thomson, and Thibadeau, 2016). Antivirus scan adopted systems on a regular basis and provide a way for performing data communication effectively and reduce the key factors which are leading cyber-crimes. In this generation, many companies like Amazon, Google, and Flipkart are using such an approach in order to protect big data from hackers and reduce the rate of cyber-crimes in a reliable manner.
Use cryptography networks
It is observed that cryptography is a kind of security tool that mainly converts data into a form of code using encryption techniques. Converting signals into code may help companies for enhancing the security of data communication and provide secure networks to use big data technology. Therefore, it is suggested that companies must include cryptography technology in order to handle fraud signals and cyber-attacks effectively (Shoro, and Soomro, 2015). The major advantage of cryptography is that it provides secured networks by which consumers can send data securely from one source to another. Moreover, companies can install encryption tools in the databases and use high-level source code for accessing data. So, using such kind of approach consumers and businesses can enhance the rate of security and avoid the data breach-related issues in a reliable way.
Secure data storage and transaction logs
It is determined that storage management is an essential part of big data technology. Involvement of signed message digests provide digital identified to every file and help companies for securing data storage elements effectively. It is argued that SUNDR is one of the best approaches used for detecting unwanted signals and malware from the systems so; it can be used by the companies in order to enhance the privacy of big data (Li, Lu, and Misic, 2017). There are several other techniques that can be used in the business for protecting big data from hackers including lazy revocation, broadcast, and policy-based encryption and key rotation process.
Conclusion
From this research, it can be summarized that big data is an effective technique that can be used to manage large volumes of data but it is necessary to handle security-related risks while using big data networks. This research provided depth information about big data and security challenges associated with the access control of big data. It is determined that malware and privacy risks both are major challenges faced by the management using big data technology because employees use unauthorized networks which leads to data breach and hacking. This paper also provided numerous approaches in order to protect data from hackers which can help readers for securing big data effectively. It is found that the development of a privacy protection agency and providing training to the employees both are effective approaches can be used in the management to secure big data and communication networks. There are major three risk factors that increase security issues in companies such as lack of privacy, unauthorized access, and third party networks. Therefore, it is significant to use firewall and antivirus related tools in the companies to protect data against cyber-crimes and enhance the performance of big data technology.
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