Securing Enterprise Java Applications: A Comprehensive Approach

Enterprise Java applications form the backbone of many mission-critical systems in sectors such as healthcare, finance, and government. With increasing security threats targeting these applications, a comprehensive understanding of Java-based security frameworks and authentication mechanisms is essential. This paper presents an in-depth exploration of contemporary security frameworks in the Java ecosystem, such as Spring Security, Apache Shiro, and Jakarta Security. It also analyzes various authentication mechanisms, including Basic Auth, OAuth2, JWT, SAML, and mutual TLS (mTLS), and their suitability for enterprise deployment. Furthermore, the paper delves into threat modeling techniques such as STRIDE and OWASP Top 10 vulnerabilities relevant to Java applications. A case study of a Hospital Management System (HMS) demonstrates the practical application of layered security strategies using modern frameworks and secure coding practices. The paper concludes with a discussion on emerging challenges, such as API-level threats, and offers future research directions. The goal is to provide a holistic reference for developers, architects, and security analysts working on Java enterprise applications.

The integration of cloud computing and data security systems is vital for the operational success and competitiveness of fintech startups. Cloud computing enables these startups to scale quickly, manage resources efficiently, and reduce infrastructure costs, making it an indispensable tool for businesses in the rapidly evolving fintech sector. However, with the benefits come significant challenges, particularly in data protection and cybersecurity. As fintech services handle sensitive financial data, ensuring robust security measures such as encryption, access controls, and continuous monitoring is crucial to maintaining user trust. Furthermore, regulatory compliance, both local and global, adds complexity to the data protection strategies of fintech companies. This research explores the key factors that drive cloud adoption in fintech, the security challenges associated with cloud environments, and the strategies implemented by startups to address these challenges. Interviews with IT managers from Indonesian fintech startups reveal that while cloud computing offers scalability and cost-effectiveness, issues like compliance with local regulations and the protection of sensitive data remain major concerns. The research suggests that fintech startups should invest in both cloud infrastructure and advanced cybersecurity measures to protect their operations and customer data. Additionally, creating a comprehensive roadmap for regulatory compliance and fostering partnerships with cybersecurity firms will help mitigate risks and ensure long-term success. The findings highlight the importance of integrating cloud computing with effective security strategies to navigate the complex regulatory and security landscape of the fintech industry.

Purpose: This article aims to assess the effectiveness of security management systems in public organisations using statistical data and institutional reports, with particular emphasis on the relationship between the maturity of these systems and the level of threats, including cybersecurity threats and incidents.The article aims to fill a research gap in the empirical analysis of the actual functioning of security systems in the public sector.Design/Methodology/Approach: The research was conducted using triangulation of research methods.Statistical data from institutional reports, document analysis (control and audit reports), comparative methods and analysis of scientific literature on security management, risk management and organisational resilience were used.The main research problem was formulated as follows: to what extent does the maturity of security management systems affect the level of threats and the effectiveness of public organisations' responses?The research hypothesis was that public organisations with more mature security management systems have fewer security incidents, shorter response times, and greater organisational resilience than entities with fragmented or informal security systems. Findings:The study indicates a clear relationship between the maturity of security management systems and the level of risk in public organisations.Entities with integrated security systems, regular risk analyses, functioning audit mechanisms, and a developed security culture are characterised by fewer incidents (including cybersecurity incidents) and a higher effectiveness in responding to threats.Practical implications: The article contributes to research on security management in the public sector by empirically confirming the importance of system maturity for organisational resilience. Originality value:The results also have a practical dimension and can serve as a basis for improving security management systems and data-driven decision-making in public organisations.

2 - Integrated Security System Design Benefits and Philosophy

Radio systems are in contact with the channels of information transmission in high-tech information times tightly more and more. The channel becomes an important part of radio systems, which is known as the radiowave propagation environment. Digital grid data can not only reflect the continuous visibilities of different part of the radiowave environmental parameters, but can achieve the propagation forecasts and generate the necessary visual maps for any regions. Based on the radiowave space grid environmental information data from advanced remote sensing instruments and radiowave environment station networks, as well as the management and application of space-time information which is expressed by radiowave environment grid data, the radiowave environment observation and security system is realized with comprehensive observation system, abundant data acquisition methods, integrated earth space, and real-time information capacity that can be used in radar, communication, monitoring and control, navigation and other electronic information systems, and integrated security systems, etc.

Integrating security in the software development life cycle has been a significant concern for researchers, security professionals and software developers. Security frameworks help to improve security in SDLC and mitigate threats by promoting the use of best practices. While in the presence of such best practices, security is somehow considered to be an afterthought and often leaves us with insecure software. Insecure web development makes web applications vulnerable to security threats like injection attacks, data breaches, privilege escalation, CSRF and other threats. This research based on mixed methods approach aims to provide valuable insights for security professionals and web application developers regarding the use of security frameworks to map threats for secure web development. Security frameworks including NIST SSDF, OWASP top 10, OWASP SAMM, SAFECode 3rd edition and BSIMM13 are involved for this purpose. The goal is to address the gap by leveraging these security frameworks to systematically map threats in web development environment. The research will aim to provide a comprehensive methodology for identifying potential security risks, analysing their impact and recommending security measures tailored to specifically web development environment. To achieve this, a comparative study of security frameworks, testing of web applications has been conducted to achieve the results.

Integrated security system need an efficient communication network to exchange the great amount of data necessary to make them work correctly. In the present paper, a new adaptive genetic controller for the dynamic optimization of network traffic of integrated security systems whose theoretical results have been tested and confirmed on wide and complex integrated security systems such as the Vatican City and Senate of Italian Republic ones is presented.

Optimization methods have had successful applications in business, economics, and finance. Nowadays the new theories of soft computing are used for these purposes. The applications in business, economics, and finance have specific features in comparison with others. The processes are focused on private corporate attempts at money making or decreasing expenses; therefore the details of applications, successful or not, are not published very often. The optimization methods help in decentralization of decision-making processes to be standardized, reproduced, and documented. The optimization plays very important roles especially in business because it helps to reduce costs that can lead to higher profits and to success in the competitive fight.

For performance and for incorporating legacy libraries, many Java applications contain native-code components written in unsafe languages such as C and C++. Native-code components interoperate with Java components through the Java Native Interface (JNI). As native code is not regulated by Java's security model, it poses serious security threats to the managed Java world. We introduce a security framework that extends Java's security model and brings native code under control. Leveraging software-based fault isolation, the framework puts native code in a separate sandbox and allows the interaction between the native world and the Java world only through a carefully designed pathway. Two different implementations were built. In one implementation, the security framework is integrated into a Java Virtual Machine (JVM). In the second implementation, the framework is built outside of the JVM and takes advantage of JVM-independent interfaces. The second implementation provides JVM portability, at the expense of some performance degradation. Evaluation of our framework demonstrates that it incurs modest runtime overhead while significantly enhancing the security of Java applications.

The rapid adoption of cloud computing has transformed the way data is stored, shared, and accessed across organizationsand individuals. Despite its scalability and cost efficiency, cloud storage introduces serious security and privacy challenges, particularly when sensitive data is outsourced to third-party cloud service providers. Traditional access control mechanisms often rely on the cloud provider’s trustworthiness, which may expose data to unauthorized access, insider threats, and data breaches. To address these concerns, CryptCloud+ is proposed as a secure and expressive data access control framework that enforces fine-grained authorization directly through cryptographic techniques. CryptCloud+ focuses on ensuring data confidentiality while enabling flexible and policy-driven access control over encrypted cloud data. The system leverages encryption-based access control, where data is encrypted before being uploaded to the cloud, and only authorized users possessing valid cryptographic credentials can decrypt and access the data. This approach eliminates the need to trust the cloud service provider, as all sensitive operations related to data access are handled at the client side. A key contribution of CryptCloud+ is its support for expressive access policies, allowing data owners to define complex rules based on user attributes such as roles, departments, access levels, or time constraints. These policies enable fine grained access control without requiring data owners to manage individual permissions manually. The framework ensures that users can access only the data they are authorized for, while unauthorized users, including cloud administrators, are unable to infer any meaningful information from the encrypted data. The proposed system is implemented using Python, taking advantage of its robust cryptographic libraries, simplicity, and integration capabilities. Python-based modules handle key generation, encryption, decryption, and policy enforcement, making the system modular and easy to extend. The implementation demonstrates how secure key management and attribute-based access enforcement can be achieved efficiently in a real-world cloud environment. CryptCloud+ also addresses scalability and performance concerns by minimizing computation overhead during data access. Encryption and decryption operations are optimized to ensure that system performance remains practical even as the number of users and data files increases. Experimental results indicate that the framework maintains strong security guarantees while providing acceptable response times for authorized users. In addition to security, the system enhances usability by allowing seamless data sharing among multiple users without re encrypting data for each individual. This significantly reduces management complexity for data owners while preserving strict access control policies. The system design ensures compatibility with existing cloud storage services, making itadaptable to various deployment scenarios. Overall, CryptCloud+ presents a secure, flexible, and effiient solution for cloud data access control. By combining cryptographic enforcement with expressive policy definition and Python-based implementation, the frameworkstrengthens data security, protects user privacy, and improves trust in cloud storage systems. The proposed model demonstrates the feasibility of practical, cryptography-driven access control for modern cloud environments.

In this paper we offer a comprehensive review of Sociophysics, focusing on relevant models as well as selected applications in social trading, behavioral finance and business. We discuss three key aspects of social diffusion dynamics, namely Opinion Dynamics (OD), Group Decision-Making (GDM) and Knowledge Dynamics (KD). In the OD case, we highlight special classes of social agents, such as informed agents, contrarians and extremists. As regards GDM, we present state-of-the-art models on various kinds of decision-making processes. In the KD case, we discuss processes of knowledge diffusion and creation via the presence of self-innovating agents. The primary question we wish to address is: to what extent does Sociophysics correspond to social reality? For that purpose, for each social diffusion model category, we present notable Sociophysics applications for real-world socioeconomic phenomena and, additionally, we provide a much-needed critique of the existing Sociophysics literature, so as to raise awareness of certain issues that currently undermine the effective application of Sociophysics, mainly in terms of modelling assumptions and mathematical formulation, on the investigation of key social processes.

In response to the growing insecurity in school environments, the integration of Information and Communication Technology (ICT)-based security systems has become increasingly vital in Nigerian educational institutions. This study examined the level of awareness, availability, usage, and the challenges associated with implementing ICT security resources in secondary schools across South-West Nigeria. Employing a descriptive survey design, the study sampled 300 respondents comprising teachers and school administrators using a multistage sampling method. Data were gathered through a structured questionnaire and analyzed using descriptive statistics (means and percentages) alongside inferential statistics, including the t-test and Pearson Product Moment Correlation Coefficient, at a 0.05 level of significance. Results indicated moderate awareness and availability of ICT security tools such as CCTV cameras, biometric scanners, and public address systems, while resources like drones and intrusion detection alarms were largely unknown or unavailable. The usage of ICT security tools varied, with some being frequently utilized and others seldom adopted due to key challenges. Identified constraints included inadequate funding, unreliable electricity supply, limited ICT expertise among staff, high installation and maintenance costs, and poor internet connectivity. Inferential findings revealed a significant relationship between the level of ICT resource usage and both awareness and implementation challenges. The study concludes that sustainable integration of ICT-based security systems in schools demands enhanced government support, investment in infrastructure, and staff capacity building. Recommendations include increased funding, comprehensive ICT training for educators, and the formulation of enforceable ICT security policies at the institutional level.

Tourism is a significant contributor to the economic growth and cultural enrichment of Lagos State, particularly in the Eti-Osa Local Government area. Private beaches play a crucial role in coastal tourism development, attracting millions of visitors each year for business, leisure, and recreational purposes. However, the area faces several challenges such as over-congestion during peak periods, insufficient infrastructural facilities, pollution, and occasional flooding, which can affect the safety and security of tourists. To address these issues and ensure a safe and secure environment for visitors, the integration of robust information technology security systems is essential. This study aims to examine the relationship between IT security measures and the patronage of private beaches by exploring the perceptions and experiences of beachgoers and operators. A total of 150 valid questionnaires were collected from respondents of the two major beaches in the area, representing an average number of customers over time. The data were analyzed using percentages and descriptive statistics. The study found that most respondents agreed that adequate security systems would strengthen the security of the beach and increase their patronage, leading to referrals to the destination. The study recommended the monitoring and transmission of information using gadgets like Closed Circuit Television (CCTV), Walkie Talkies, and Electric Security Alarms.

The uninhabited housing situation is very vulnerable to the existence of theft activities. Anticipation using a variety of door locking system of the house also often can be overcome by various the perpetrators of theft. Information technology today is inseparable from the development of internet communication technology. The Internet today are an essential part of every society as a means of Informastion Source. Therefore, there needs to be integration of home security system which can be integrated with internet based information system as one of innovation in security system. The research objective is the design and manufacture of sensor-based home security system as a passive infrared motion detectors integrated with Internet-based information system with the concept of the Internet of things (IoTs). The research used Passive Infra Red Sensor as input data, Arduino Uno Microcontroller as Sensor Data Processor and Ethernet as Web Server. The research resulted in a series of home security information system prototype based internet information and has successfully accessed through an Internet browser in the form of home security information to detect the presence of an intruder without permission remotely via the internet.

As the healthcare industry undergoes rapid digital transformation, the need for robust cybersecurity measures has never been more critical. AI-driven solutions, such as Machine Learning (ML) and anomaly detection, are proving to be pivotal in securing healthcare data. These technologies enable healthcare organizations to identify cyber threats proactively, automate incident response, and enhance data security. Furthermore, AI's ability to provide continuous network monitoring, predictive analytics, and real-time anomaly detection offers healthcare providers the tools needed to mitigate risks before they escalate. This research highlights the key applications of AI in healthcare data security, including its effectiveness in vulnerability management and regulatory compliance. It also delves into the ethical and operational challenges of integrating AI-driven threat detection systems into healthcare settings, including concerns related to bias in AI models, regulatory hurdles, and the complexity of AI system integration into existing healthcare infrastructures. In a 2023 study, Accenture reported that AI-based cybersecurity systems reduced detection and response time by up to 60%, illustrating how AI accelerates response to potential data breaches​. Similarly, HIMSS noted that the risk of data breaches in healthcare could be halved by AI technologies that continuously monitor and analyze data​. These findings emphasize AI's role in minimizing the delays and errors typically associated with human-driven responses​. AI techniques such as supervised, unsupervised, and semi-supervised learning play a crucial role in anomaly detection. These models identify irregular patterns in healthcare systems, flagging potential threats even when subtle​. For example, deep learning approaches, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), can uncover outliers in healthcare data, enhancing system security​. The ability of AI to continuously learn from previous attacks ensures that systems evolve with emerging threats, further solidifying its place in healthcare cybersecurity​. Additionally, AI aids in predictive analytics, which can forecast future cyber threats based on historical data, allowing healthcare providers to address vulnerabilities proactively​. By leveraging such capabilities, AI not only safeguards sensitive patient data but also enables healthcare institutions to stay compliant with stringent regulatory standards like HIPAA and GDPR​. However, AI implementation in healthcare security comes with its own challenges. Integrating AI into legacy systems requires substantial infrastructure upgrades, and the complexity of dynamic encryption can strain system resources​. Furthermore, the ethical concerns surrounding AI, such as the transparency of decision-making processes and potential bias in AI algorithms, must be carefully managed to ensure equitable and effective security solutions​