Database Security

Abstract

Database security is a crucial factor in safeguarding sensitive data in today\'s information-centric world. As organizations increasingly rely on databases for storing and managing vast volumes of data, ensuring the security of databases has become a top priority. This paper proposes a methodology for enhancing database security by addressing identified challenges and attacks. The methodology involves various steps, including identifying and assessing potential threats, evaluating existing security measures, implementing multi-layered defense, enforcing the principle of least privilege, regularly updating and patching DBMS, conducting regular security audits, providing user awareness training, implementing data encryption, monitoring and logging database activities, developing an incident response plan, staying updated with the latest research and best practices, and continuously improving security measures. By following this methodology, organizations can effectively enhance the security of their databases and safeguard critical data from potential attacks and breaches. Emphasis is placed on regular review and updates to security measures to proactively address evolving threats and ensure continuous protection of sensitive data.

Introduction

I. INTRODUCTION

As organizations increasingly rely on information systems and the Internet for their daily business operations, they also face higher vulnerability to security breaches. One commonly used security measure is a firewall [1]. A firewall acts as a barrier between an organization's internal network and the Internet, monitoring all incoming and outgoing traffic and blocking unauthorized traffic.

However, firewalls are not fool proof and should only be considered as the first line of defines. They are susceptible to penetration, and once a system is breached, firewalls do not provide protection to internal resources. Additionally, firewalls do not safeguard against security violations from authorized users within the organization, who are believed to be responsible for a significant portion of computer crimes according to a U.S. Air Force study [2].

Protecting internal resources is a complex task that requires suitable methods and tools to fulfill three key requirements [3, 4]:

Identification and Authentication:

Systems must be able to identify users and verify their identity. User identification is a basic security requirement. Users must be identified before their privileges and access rights can be determined, and their actions on the data can be audited. There are several ways to authenticate users before they are granted access to the database, such as external authentication by the operating system or network service, Secure Socket Layer (SSL) authentication, enterprise roles, and middle-tier server authentication (also known as proxy authentication). Ensuring user identification and authentication is crucial for data security, as it prevents unauthorized access and modification of sensitive data. Attackers may attempt to compromise user identification and authentication through methods such as bypassing authentication, exploiting default passwords, privilege escalation, password guessing through brute force and rainbow attacks. Access controls establish a separation between users and the various data and computing resources, protecting internal resources from unauthorized or improper modification.Access control is a fundamental service that should be provided by any Data Management System. It ensures that data is protected from unauthorized read and write operations. Access controls define and enforce policies for communication with the database and other system objects. Errors in access controls can have serious consequences for an organization's operations. Implementing access rights can also reduce risks that may impact the security of the database on the main servers. For example, accidental deletion or modification of a table can be rolled back or restricted through proper access control measures.

Access Control systems include:

1. File permissions - create, read, edit, or delete on a file server.
2. Program permissions - the right to execute a program on an application server.
3. Data rights - the right to retrieve or update information in a database.

Encryption ensures that any data that is sent over the network can be deciphered only by the intended recipient. Encryption is the process of converting information into a cipher or a code so that it cannot be readable to all other people except those who hold a key for the ciphertext. The ciphertext or encoded text is called encrypted data. There are two states for data protection in a database. Data may exist either at rest - data may be stored in a database or in backend tape - or at transit - data traveling across the network - which dictates different encryption solutions for the data in transit. Data encryption can solve some of the issues related to data at rest. For data at transit, solutions such as SSL/TLS can be leveraged.

Since the first and third requirements are outside the scope of database management systems (DBMSs), we focus in this paper on the state of the art in access control models for databases and discuss open research issues. We do not attempt to be exhaustive but try to articulate the reasons for the approaches we deem most promising.

Data plays a crucial role in today's world for the success or failure of an organization because most organizations use databases for storage of major or important data of the organization. The data is not limited to just user details but also includes all credentials or sensitive information of an organization. Many organizations spend a lot of money on securing their databases, and the importance of data makes database security important in every sector, whether it is the private sector or the government sector. Hence, the data must be protected.

Basically, there are five layers of security - database admin, system admin, security officer, developer, and employee. Thus, security can be affected at any of these levels by an attacker. In database security, attackers are divided into three segments:

a.  Administrator An admin is an authorized person who has permission to control the system but misuses his/her privileges against the security policies to obtain important information.

b.  Insider An insider is also a member of the trusted committee in an organization but misuses his/her authority to obtain sensitive or other important information.

c. Intruder An intruder is not a part of an organization. Actually, he/she is unauthorized people who access the personal data of an organization and try to obtain sensitive information. The security of data basically requires three things - Confidentiality, Integrity, and Availability. Confidentiality means the data must be used by an authorized person, Integrity means the data must be controlled by an authorized person in an authorized manner, and Availability means the data must be available to an authorized user at the appropriate time.

These three are shown in Fig.1 below:

II. LITERATURE REVIEW

In the paper "Review of Attacks on Databases and Database Security Techniques" written by Saurabh Kulkarni1 and Siddhaling [5], the authors discuss important and private information in databases and the risk of attacks. They examine various attacks on databases and review several important database security strategies, including access management, SQLIA strategies, encryption, and data scrambling. The paper also addresses potential areas of study in the field of database security.

In the paper "Security Issues in Databases" written by Sohail IMRAN and Dr. Irfan Hyder [6], the authors highlight the different security models for databases and their limitations in providing a comprehensive defense for organizational security. They address various security problems in databases and propose a strategy for transparent and tailored security specifications. The paper also discusses security concerns and specifications in optional and compulsory protection frameworks for conventional and focused database networks, as well as security-related problems in a practical, database-oriented manner. A review of past and current trends in database security is provided.

In the paper "Core Threats and Prevention in Database Security" written by ILO Somtoochukwu F, Ubochi Chibueze, and Osondu U. S [7], the authors emphasize the increasing issue of database security due to the growing number of recorded events and the need to protect confidential data from unauthorized access. They discuss the principles and processes of computer security and the three structures of database security: data confidentiality, prevention of unauthorized access, and detection of hardware and software failures. The paper addresses various sub-topics of database security, including ransomware, weak security, inappropriate database setup, SQL injection, cross-request, and misuse of disproportionate rights, and reviews data management techniques for securing machine knowledge.

In the paper "Database Encryption - An Overview of Contemporary Challenges and Design Considerations" written by Erez Shmueli, Ronen Vaisenberg, Yuval Elovici, and Chanan Glezer [8], the authors discuss the challenges and architecture issues related to database encryption. They provide an overview of attacks and problems related to computer security, public encryption, key management, and data indexing. The paper reviews recent theoretical research on alternative encoding solutions and key management, and proposes a design-oriented architecture for database encryption that can be used by security vendors, DBAs, and information technology developers. The paper compares multiple configurations for the implementation of database encryption and discusses the impact of encoding precision on data protection and efficiency.

In the paper "A Review Report on Security Threats on Database" written by Shivnandan Singh and Rakesh Kumar Rai [9], the authors highlight the importance of data and database security for organizations. They discuss the high rate of database breaches and attacks on databases, which can disclose critical information to intruders. The paper reviews various database-based threats and algorithms for database security, and discusses the attacks on databases and the review of important database security strategies, including access management, SQLIA strategies, encryption, and data scrambling. The paper also addresses potential areas of study in the field of database protection.

III. ATTACKS ON DATABASE

The attacks performed on a database are classified into two segments:

A. Passive Attacks

Passive attacks focus on observation. Here, the attacker observes the data present in the database without modifying it. Passive attacks are less problematic than active attacks but can still be dangerous. There are three forms of passive attacks:

1. Static Leakage: In this type of passive attack, the attacker observes the snapshot of the database to obtain plain text values at a particular specified time. Static leakage only deals with the observation of data in the database at a specified time period, and the data remains unchanged. While it is not very harmful as appropriate data is received by the intended recipient, it is still considered an attack because the attacker is observing the data in the database. It is called static leakage because it is performed only for a specified time period.
2. Linkage Leakage: In this type of passive attack, the attacker establishes the linkage between the database value and the position of that specified value in the index to obtain the plain text value. Linkage leakage involves checking the index of the database and searching for the particular data on which the attack is to be performed. When the required data value is found in an index of the database, the data is linked with the database value. Linkage leakage can create problems, but it is not as dangerous as compared to other attacks.

3. Dynamic Leakage: In this type of passive attack, the plain text value can be generated by observing the continuous changes performed in the database for a particular time. The attacker observes the data transmitted between users for a time period and then analyzes the changes to get related data about the plain text value.

B. Active Attacks

Active attacks are more problematic as compared to passive attacks because active attacks involve modifying data. For example, the user captures the wrong information as a result of a query. Active attacks can be performed in different ways:

1. Spoofing Attacks:  In this active attack, a value is generated and then the cipher text is replaced by that value. This value is generated using some algorithms and techniques.
2. Splicing Attacks:  In this active attack, two cipher text values are there, and one cipher text value is then replaced by another cipher text value.

3. Replay In this active attack, the cipher text value is replaced by an old version that was previously updated or deleted. This attack is called replay because the deleted old version value is under consideration.

C. SQL Injection Attack

SQL injection attack is the most serious attack on database security. In today's world, almost all applications use the database as a backend, and the most critical attack on web applications is SQL injection attack, abbreviated as SQLIA or SIA. SQLIA is a dangerous attack in database security because SQL attacks are performed on the server, and the server runs malicious queries that result in the manipulation of the database. SQL injection is a technique in which malicious users can add SQL commands into SQL statements through web page input. An attacker typically adds unauthorized database statements into an insecure SQL data channel. SQL injection attack is performed to allow unauthorized access to the database.

SQL injection attacks are a type of database vulnerability that can be exploited by attackers to gain unauthorized access to the database or retrieve sensitive information. There are several types of SQL injection attacks, including tautology-based attacks, union queries-based attacks, and piggybacked queries.

Tautology-based attacks are simple to perform and involve injecting SQL tokens into conditional statements to make them always evaluate to true. For example:

SELECT name FROM bank WHERE name='' or 1=1--' AND pin=''

In this example, the injected code in the WHERE clause always returns true, allowing the attacker to retrieve data from the database.

Union queries-based attacks involve injecting unsecured parameters and joining them with the original query using UNION to retrieve data from the database. For example:

SELECT name FROM bank WHERE name='' UNION SELECT name from employee WHERE employee_id='123'-- AND pin=''

In this example, if the original query returns null, the injected query retrieves the name of the employee with employee_id '123', and the final result is a union of both queries.

Piggybacked queries involve injecting a query alongside the original query, separated by a delimiter (;), and the database executes both queries. For example:

SELECT name FROM bank WHERE name='Preeti' AND pswrd='abcde' AND pin='132001'; DROP TABLE bank

In this example, the injected query drops the bank table in the database.

To protect against SQL injection attacks, it is important to implement security measures such as restricting unauthorized access, using strong credentials with multi-factor authentication, conducting load/stress testing on the database, providing physical security to server rooms, implementing a disaster recovery plan, separating web servers and applications from the database server, reviewing existing systems for vulnerabilities and mitigating them, implementing data encryption for data in motion and at rest, configuring firewalls in the perimeter layer, managing passwords and permissions, isolating sensitive databases, implementing change management processes, and conducting regular database auditing for monitoring and detecting unauthorized access or actions.

IV. RESEARCH METHODOLOGY

Here is a proposed methodology for enhancing the security of databases based on the challenges and attacks identified in the content:

1. Identify And Assess Potential Threats

Conduct a thorough analysis of potential threats to the database, including attacks from administrators, insiders, and intruders. This can involve reviewing historical data breaches, analyzing known vulnerabilities in database management systems (DBMS), and identifying potential attack vectors.

2. Evaluate Existing Security Measures

Review the current security measures in place, such as firewalls, access controls, and encryption methods, and assess their effectiveness in mitigating identified threats. Identify any gaps or weaknesses in the current security measures that need to be addressed.

3. Stay Updated With Latest Research And Best Practices

Keep up-to-date with the latest research and best practices in the field of database security, as new threats and vulnerabilities can emerge over time. Stay informed about industry standards and regulations, and adapt the security measures accordingly.

4. Implement Multi-Layered Defense

Recognize that no single security measure is foolproof, and implement a multi-layered defense strategy. This can involve using a combination of firewalls, intrusion detection and prevention systems (IDPS), strong authentication methods (such as two-factor authentication), and encryption techniques to protect against different types of attacks.

5. Implement Principle Of Least Privilege

Enforce the principle of least privilege, which restricts users and administrators to the minimum level of access necessary to perform their tasks. This can prevent unauthorized access and reduce the potential damage from insider threats.

6. Regularly Update And Patch Dbms

Keep the DBMS and associated software up-to-date with the latest security patches and updates. This can address known vulnerabilities and protect against exploits that could be used by attackers.

7. Conduct Regular Security Audits

Perform regular security audits to assess the effectiveness of existing security measures and identify any potential vulnerabilities or weaknesses. This can involve penetration testing, vulnerability scanning, and security assessments to identify and address any gaps in the security posture.

8. Provide User Awareness Training

Educate users and employees about the importance of database security and provide training on best practices for data protection, such as strong password management, identifying and reporting suspicious activities, and understanding the risks associated with insider threats.

9. Implement Data Encryption

Utilize encryption techniques, such as SSL/TLS, to protect data both at rest and in transit. This can prevent unauthorized access to sensitive data even if the database is compromised.

10. Monitor And Log Database Activities

Implement robust logging and monitoring mechanisms to track and detect any suspicious activities in the database. This can involve monitoring access logs, database activity logs, and using security information and event management (SIEM) systems to detect potential security breaches.

11. Develop An Incident Response Plan

Have a well-defined incident response plan in place to quickly respond to and mitigate any security incidents. This can involve defining roles and responsibilities, establishing communication protocols, and having a plan for backup and recovery in case of data breaches.

12. Continuous Improvement

Continuously assess, evaluate, and improve the security measures in place based on changing threat landscapes, technology advancements, and organizational requirements. Regularly review and update the security policies, procedures, and controls to ensure they are effective in protecting the database and its data.

By following this proposed methodology, organizations can enhance the security of their databases and protect their critical data from potential attacks and breaches. It is important to regularly review and update the security measures to stay ahead of evolving threats and ensure the ongoing protection of sensitive data.

V. FUTURE RESERACH

Longitudinal Studies: Conducting long-term studies to analyze unusual data access patterns can provide valuable insights into the evolving nature of data security threats and how organizations can adapt their security measures accordingly. By identifying patterns, trends, and emerging behaviors over an extended period, such studies can capture nuances that may not be apparent in shorter-term analyses.

Industry-Specific Studies: Conducting studies specific to different sectors, such as healthcare, finance, or manufacturing, can provide targeted insights into industry-specific data security challenges and effective countermeasures. This can help organizations tailor their data security strategies according to the unique requirements of their respective industries.

Hybrid Approaches: Combining different techniques, such as machine learning algorithms, behavior-based modeling, and context-aware analysis, can potentially enhance the accuracy and effectiveness of detecting unusual data access patterns. Further research could explore the synergistic effects of multiple techniques to improve the detection and prevention of data security threats.

Human Factors: Investigating the role of human factors, such as human error, insider threats, and social engineering attacks, in unusual data access patterns can provide insights into how human behavior impacts data security. Research could delve into the psychological, social, and organizational factors that influence data access patterns and develop strategies to mitigate human-related security risks.

Practical Applications of Research Findings in Real-World Data Security Systems:

Enhanced Data Security Measures: Organizations can implement enhanced data security measures based on research findings, such as incorporating advanced anomaly detection algorithms, context-aware anomaly detection, and real-time monitoring capabilities, to improve the accuracy and effectiveness of detecting anomalous data access patterns. This can help organizations detect and respond to potential security breaches or data misuse more effectively.

Improved User Education and Awareness Programs: Organizations can develop and implement user education and awareness programs based on research findings to promote a culture of security awareness among users. This can include regular training sessions, awareness campaigns, and ongoing communication to educate users about the importance of adhering to access controls, recognizing and reporting suspicious activity, and understanding the implications of anomalous data access patterns.

Robust Access Control and Permissions Management Practices: Organizations can implement robust access control and permissions management practices based on research findings, such as the principle of least privilege (POLP), to restrict users' access to only the data and resources they need to perform their job responsibilities. Regular review and updates of permissions and access rights can also help prevent unauthorized access and reduce the risk of anomalous data access patterns.

Well-Defined Incident Response and Investigation Processes: Organizations can establish well-defined incident response and investigation processes based on research findings to effectively respond to anomalous data access patterns. This can include defining roles and responsibilities, establishing communication channels, and leveraging forensic techniques and tools to investigate anomalous data access patterns and determine the root cause of the anomaly.

Continuous Monitoring and Improvement of Data Security Systems: Organizations can implement continuous monitoring and improvement practices based on research findings to regularly review, assess, and update their data security measures. This can help organizations stay proactive in addressing potential vulnerabilities and adapting to changing security threats, ensuring their data security systems remain effective over time.

Enhanced Data Security Measures: Based on research findings, organizations can implement advanced anomaly detection algorithms, context-aware anomaly detection, and real-time monitoring capabilities to enhance their data security measures.

This can help detect anomalous data access patterns more accurately and effectively, enabling organizations to respond to potential security breaches or data misuse more efficiently.

Improved User Education and Awareness Programs: Research findings can inform the development of user education and awareness programs to promote a culture of security awareness among users. These programs can include regular training sessions, awareness campaigns, and ongoing communication to educate users on access controls, recognizing and reporting suspicious activity, and understanding the implications of anomalous data access patterns.

Robust Access Control and Permissions Management Practices: Organizations can implement robust access control and permissions management practices, such as the principle of least privilege (POLP), to restrict users' access to only the data and resources they need to perform their job responsibilities. Regular review and updates of permissions and access rights can also help prevent unauthorized access and reduce the risk of anomalous data access patterns.

Well-Defined Incident Response and Investigation Processes: Organizations can establish well-defined incident response and investigation processes to effectively respond to anomalous data access patterns. This can include defining roles and responsibilities, establishing communication channels, and leveraging forensic techniques and tools to investigate anomalous data access patterns and determine the root cause of the anomaly.

Continuous Monitoring and Improvement of Data Security Systems: Organizations can implement continuous monitoring and improvement practices to regularly review, assess, and update their data security measures. This can help organizations stay proactive in addressing potential vulnerabilities and adapting to changing security threats, ensuring their data security systems remain effective over time.

VI. RESULT

Database security measures are essential for safeguarding sensitive data against unauthorized access, adhering to regulatory requirements, minimizing the risk of data breaches, enhancing customer confidence, and improving business efficiency. These measures are designed to ensure the confidentiality, integrity, and availability of data stored in databases, and by adopting them, organizations can prevent financial losses, reputational harm, and legal liabilities resulting from security breaches. In summary, maintaining a secure and dependable data infrastructure heavily relies on implementing robust database security measures.

The implications of research findings related to anomalous data access patterns for data security systems can have significant implications for improving the overall security posture of an organization. Some potential areas of improvement based on research findings could include:

Enhanced anomaly detection algorithms: The findings of research studies may indicate a requirement for the enhancement of machine learning algorithms or other methodologies to identify unusual data access patterns. It may be possible to improve the precision and efficiency of detecting such patterns by incorporating advanced statistical or behavioral modeling techniques. Anomaly detection based on machine learning algorithms like clustering, classification, or anomaly scoring could potentially be utilized to achieve this objective.

Context-aware anomaly detection: To enhance the accuracy and effectiveness of detecting anomalous data access patterns, it may be necessary to take contextual information into account. For example, contextual factors such as user roles, job functions, location, time of day, and the type of data being accessed can provide a more comprehensive understanding of anomalous behavior. Integrating contextual information into anomaly detection algorithms can reduce false positives and false negatives, leading to more precise and relevant alerts.

Real-time monitoring and response: Real-time monitoring of data access patterns can be beneficial for detecting anomalous behavior as it occurs. This can enable organizations to quickly respond to potential security breaches or data misuse.

Technologies such as security information and event management (SIEM) systems, user behavior analytics (UBA) tools, or other monitoring solutions can provide timely alerts and notifications to security teams. Incorporating real-time monitoring capabilities can help organizations quickly identify and address potential security threats.

User education and awareness: The research may point out that user education and awareness are vital in ensuring data security. Educating users on the significance of access controls, detecting and reporting suspicious activity, and the potential consequences of anomalous data access can help create a culture of security within the organization. This can be achieved through regular training sessions, awareness campaigns, and continuous communication to encourage good security practices among users.

Access control and permissions management: Improved access control and permission management practices may be necessary based on research findings. Implementing strong access control mechanisms, such as the principle of least privilege (POLP), can restrict users' access to only the data and resources they require to perform their job duties. Periodically reviewing and updating permissions and access rights can also help prevent unauthorized access and reduce the possibility of anomalous data access patterns.

Incident response and investigation: Research may indicate the significance of having well-defined incident response and investigation processes in place to efficiently respond to anomalous data access patterns. Establishing precise protocols for incident detection, escalation, investigation, and resolution can aid organizations in responding promptly and effectively to security incidents. This may involve defining roles and responsibilities, establishing communication channels, and leveraging forensic techniques and tools to investigate anomalous data access patterns and identify the root cause of the anomaly.

Continuous monitoring and improvement: Research findings may highlight the significance of regularly updating and enhancing data security systems to maintain their effectiveness. Data security is an ongoing process, and organizations should continuously evaluate, improve, and adapt their security measures based on the latest industry standards, emerging threats, and research findings. This approach can help organizations stay ahead of potential security risks and maintain the confidentiality, integrity, and availability of their data assets.

In resultant, research findings related to anomalous data access patterns can have significant implications for data security systems. By leveraging these findings, organizations can identify potential areas of improvement in their data security measures and implement strategies to enhance the detection, prevention, and response to anomalous data access patterns, thereby strengthening their overall data security posture.

Conclusion

In conclusion, the safeguarding of data stored in databases is crucial in today\'s digital environment. The literature review conducted in this study has identified the difficulties and potential hazards linked with database security, which includes illicit access, data breaches, insider threats, and data leakage. The investigation has examined several approaches and optimal practices to address these hazards and guarantee strong database security. The study\'s results have demonstrated the existence of various practical solutions to ensure the protection of databases and prevent unauthorized access and breaches of data. These solutions involve the deployment of robust authentication mechanisms, including multi-factor authentication, utilization of encryption techniques to secure data in transit and at rest, consistent updating and patching of database systems, implementation of strict access controls and permissions, and the conducting of frequent security audits and monitoring.. Moreover, new and developing technologies such as database activity monitoring, database firewall, and machine learning-based anomaly detection solutions have demonstrated encouraging potential for strengthening database security. Ensuring compliance with relevant regulations and standards, including GDPR and PCI-DSS, was also found to be vital for maintaining adequate database security. Nevertheless, it is essential to recognize that no solution is completely fullproof, and organizations must take a comprehensive and proactive approach to database security. This involves not only implementing technical measures but also fostering a security-conscious culture among employees, providing regular training programs, and devising incident response plans to handle security incidents and data breaches efficiently. In conclusion, to protect databases and prevent unauthorized access or breaches, it is necessary to employ a combination of technical, procedural, and human-focused measures. Organizations can reduce risks and ensure robust database security by implementing best practices, adhering to applicable regulations, and keeping up with emerging technologies and threats. Protecting critical data assets and maintaining trust with stakeholders can be achieved through these actions. Future research may explore advanced database security techniques, such as homomorphic encryption, secure hardware enclaves, and blockchain-based solutions, and their potential impact on enhancing database security. Additionally, further studies could investigate the human element in database security, including factors affecting employee behavior, organizational culture, and the role of training and awareness programs in promoting database security. Furthermore, it is important for policymakers and regulators to continually update and enforce data security laws and regulations, taking into account the constantly evolving technological and threat landscapes. Effective data security strategies and practices require collaboration between organizations, government entities, and other stakeholders. Future research may explore emerging technologies and approaches, such as artificial intelligence, blockchain, and zero-trust architecture, and their potential impact on improving data security practices. Additionally, research could investigate the human element of data security, including factors that influence employee behavior and decision-making regarding data security. Protecting data assets and ensuring data security requires ongoing attention, investment, and collaboration among various stakeholders. By addressing the identified challenges and implementing effective data security measures, organizations can mitigate risks, protect sensitive information, and maintain trust in the digital ecosystem. In conclusion, safeguarding databases and the sensitive data they contain is a multifaceted task that necessitates constant research, innovation, and collaboration among various stakeholders. Organizations must stay alert, adaptive, and proactive to the changing threat landscape to guarantee the confidentiality, integrity, and availability of their data assets. This will help them maintain the trust of their customers and partners.

References

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Copyright

Copyright © 2023 Prof. K. R. Ingole, Akshada S. Hage, Khushali V. Dudhabade, Sakshi D. Tayade, Radhika S. Khewalkar, Supriya N. Deshpande. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.