Existing Security Infrastructure Research Articles

The Role of Machine Learning in Detecting and Preventing Data Breaches

Data breaches pose a growing threat to individuals, organizations, and public safety. In response, machine learning (ML) has emerged as a powerful tool for both detecting and preventing these breaches. This research paper analyses the multifaceted role of ML in data security, exploring its strengths, limitations, and potential future directions. Through a comprehensive literature review, this paper examines how different ML models and algorithms can be employed to detect anomalous behavior, predict cyberattacks, and mitigate vulnerabilities. The importance of ethical considerations surrounding privacy and user rights is also addressed, emphasizing responsible data handling practices. Furthermore, the paper investigates the challenges and best practices of integrating ML into existing security infrastructure, providing recommendations for organizations seeking to leverage its benefits. Finally, it assesses the current limitations of ML in data breach detection and prevention, identifying promising research avenues for advancing data security through ML advancements. In conclusion, this research highlights the crucial role of ML in the ongoing battle against data breaches. By effectively utilizing its capabilities while maintaining ethical considerations, organizations can significantly enhance their data security posture and safeguard valuable information in our increasingly digital world.

Enhancement the Security by creating ontology-based Trust Management using Semantic Web tools

The most traditional policy models which do not consider dynamic nature of distribute systems and the limitation in addressing issues like adaptability, extensibility, and reasoning over security policies. The main cause of the flexibility and scalability issues in the environments of the Internet and dynamic networks is that there is no central control over the environments, and users are not predetermined. As a result, security and trust issues become critical in the various systems; enhancing the security of these environments would require adding trust to the existing security infrastructures. Few trust models have taken into account the semantic relationship for pervasive elements, despite the fact that numerous models have been proposed to address trust issues in dynamic environments; especially those who related to trust categories. In our work, we solve issues resulted from security and tracking the dynamics of participating communication devices in dynamic distributed networks. Through using ontology for trust management which it is define vocabularies used to described and represented an area of knowledge. For representation, we used semantic web's tools to represent the domain of the dynamic environment and we improv that the reasoning succusses in inference the trusted device and user exactly where we do query.

Legal aspects of functional security standardisation of the Internet of Things

IoT technologies provide smart things with the ability to make decisions in the management of physical objects using intelligence and consensus. To support the Internet of Things, technologies such as built-in devices, cloud and fog computing, big data processing, machine learning, and artificial intelligence are used to produce intelligent physical objects. A review of existing security infrastructures for IoT-based intelligent environments shows that every connected device can be a potential entry point for an attack.
 An overview of the key aspects of security standards for smart environments based on the Internet of Things has been provided in the following areas: potential solutions, intelligent environments, limits of security assessment, open issues and challenges. Additional research on the development of methodological and technological standardisation measures in the field of interoperability of heterogeneous IoT devices is an urgent task in order to start further discussions on the development of new security standards and certification infrastructure for smart environments based on the IoT.
 Based on the analysis of the existing problems of implementing the Internet of Things, the methodological and technological features of legal regulation of intellectual environments have been studied. The structures of standardisation of networks and services of the IoT environments at the regional, European and global international levels have been considered.
 The architecture of the Internet of Things environments has been defined as a multi-level, heterogeneous system with a complex topology and the use of innovative technologies. The single phenomenon of IoT security has been identified as a complex concept that includes functional security and information security with their interconnection, contradictions, challenges and risks.
 The functional security of the Internet of Things has been studied in terms of the security function, security completeness and resilience, which are subject to regulation in the technical requirements for the product being designed. An aspect model of IoT interoperability has been presented and examples of its application in terms of interrelated components (transport, syntactic, semantic, behavioural, and policy aspects) have been given.
 An assessment of generally accepted practices and risks of creating regulatory documents (standards, instructions, methodological materials) in the field of functional security of the Internet of Things has been carried out. Recommendations for the introduction of a scientifically based approach to national standardisation of IoT security and measures to address the problem of interoperability of heterogeneous IoT devices have been provided.

Control of Web Traffic Using Web Application Firewall : Techniques and Challenges

The increasing complexity and sophistication of web-based applications have made them vulnerable to various security threats. Web Application Firewalls (WAFs) have emerged as an essential security measure to protect web applications from common attacks such as SQL injection, cross-site scripting (XSS), and others. This research paper explores the techniques and challenges involved in controlling web traffic using a Web Application Firewall. The paper discusses the working principles of WAFs, the various methods employed to analyze and filter web traffic, and the effectiveness of these techniques in mitigating different types of attacks. Additionally, the paper highlights the challenges faced in deploying and managing WAFs and provides insights into potential future developments in the field. This research paper delves into the techniques and challenges associated with controlling web traffic using a Web Application Firewall. It explores the fundamental principles of WAFs, including signature-based filtering, behavior-based analysis, whitelisting, blacklisting, rate limiting, and protection against common vulnerabilities. The paper evaluates the effectiveness of these techniques in mitigating various attacks and highlights the challenges involved in deploying and managing WAFs, such as configuration complexity, false positives and negatives, performance impact, and integration with existing security infrastructure. Furthermore, the paper discusses emerging trends and potential future directions in the field, including the integration of machine learning and artificial intelligence, advanced behavioral analysis techniques, and cloud-based architectures.

ANALYSIS OF CURRENT THREATS TO THE INFORMATION SECURITY OF ORGANIZATIONSAND THE FORMATION OF THE INFORMATION PLATFORM AGAINST THEM

Taking into account the process of complication of the geopolitical and geoeconomic landscape space, the development of information technologies and the formation of new security challenges associated with the emergence of new cyber threats, there is a need for constant monitoring and forecasting of them in order to prevent consequences in the form of damage and leakage of valuable and confidential information. The authors analyzed the new predictable cyber security threats to organizations, with special attention paid to the protection of endpoints. Threats identified in the field of artificial intelligence development (underground development of malicious Large Language Models (LLM); “Script Kiddies” update; voice fraud for social engineering, which is created by artificial intelligence); changing trends in the behavior of threat actors (attacks on supply chains against managed file transfer solutions, malware threats that are becoming multilingual); as new emerging threats and attack methods (growing QR code rivalry; stealth attacks on peripheral devices; Python implementation in Excel creating a potentially new vector for attacks; LOL drivers changing action algorithms). The resulting detection of future threats emphasizes the need for strategic planning for the adoption of new technologies and platforms: such as Endpoint Detection and Response (EDR) capabilities, as well as the use of EDR as part of a multi-instrumented enhanced detection and response (XDR) architecture. Gartner’s research has been proven to have a tremendous impact on improving organizations’ threat detection capabilities by providing valuable insight into the strengths and weaknesses of each cybersecurity service provider with respect to emerging threat intelligence, by focusing organizations’ attention on opportunities to identify gaps in their existing security infrastructure and adopt sound decisions to invest in additional solutions or services that effectively address these gaps. The spheres of activity of the world’s leading companies were analyzed, their connection with Ukrainian companies was found, and further cooperation was proposed for the effective protection of national cyberspace.

Adaptive IDS for Cooperative Intelligent Transportation Systems Using Deep Belief Networks

The adoption of cooperative intelligent transportation systems (cITSs) improves road safety and traffic efficiency. Vehicles connected to cITS form vehicular ad hoc networks (VANET) to exchange messages. Like other networks and systems, cITSs are targeted by attackers intent on compromising and disrupting system integrity and availability. They can repeatedly spoof false information causing bottlenecks, traffic jams and even road accidents. The existing security infrastructure assumes that the network topology and/or attack behavior is static. However, the cITS is inherently dynamic in nature. Moreover, attackers may have the ability and resources to change their behavior continuously. Assuming a static IDS security model for VANETs is not suitable and can lead to low detection accuracy and high false alarms. Therefore, this paper proposes an adaptive security solution based on deep learning and contextual references that can cope with the dynamic nature of the cITS topologies and increasingly common attack behaviors. In this study, deep belief networks (DBN) modeling was used to train the detection model. Binary cross entropy was used as a loss function to measure the prediction error. Two activation functions were used, Relu and Softmax, for input–output mapping. The Relu was used in the hidden layers, while the Sigmoid was used in the last layer to map the real vector to output between 0 and 1. The adaptation mechanism was incorporated into the detection model using a moving average that monitors predicted values within a time window. In this way, the model can readjust the classification thresholds on-the-fly as appropriate. The proposed model was evaluated using the Next Generation Simulation (NGSIM) dataset, which is commonly used in such related works. The result is improved accuracy, demonstrating that the adaptation mechanism used in this study was effective.

Naturally safe: Cellular noise for document security.

Modern document protection relies on the simultaneous combination of many optical features with micron and submicron structures, whose complexity is the main obstacle for unauthorized copying. In that sense, documents are best protected by the diffractive optical elements generated lithographically and mass-produced by embossing. The problem is that the resulting security elements are identical, facilitating mass-production of both original and counterfeited documents. Here, we prove that each butterfly wing-scale is structurally and optically unique and can be used as an inimitable optical memory tag and applied for document security. Wing-scales, exhibiting angular variability of their color, were laser-cut and bleached to imprint cryptographic information of an authorized issuer. The resulting optical memory tag is extremely durable, as verified by several century-old insect specimens still retaining their coloration. The described technique is simple, amenable to mass-production, low cost and easy to integrate within the existing security infrastructure.

Dashboard Prototype for Improved HIV Monitoring and Reporting for Indiana

Dashboard Prototype for Improved HIV Monitoring and Reporting for Indiana

Stego anomaly detection in images exploiting the curvelet higher order statistics using evolutionary support vector machine

Steganalysis is an important extension to existing security infrastructure, and is gaining more research focus of forensic investigators and information security researchers. This paper reports the design principles and evaluation results of a new experimental blind image steganalysing system. This work approaches the steganalysis task as a pattern classification problem. The detection accuracy of the steganalyser depends on the selection of low-dimensional informative features. We investigate this problem as a three step process and propose a novel steganalyser with the following implications: a) Selection of the Curvelet sub-band image representation that offers better discrimination ability for detecting stego anomalies in images, than other conventional wavelet transforms. b) Exploiting the empirical moments of the transformation as effective steganalytic features c) Realizing the system using an efficient classifier, evolutionary-Support Vector Machine (SVM) model that provides promising classification rate. An extensive empirical evaluation on a database containing 5600 clean and stego images shows that the proposed scheme is a state-of-the-art steganalyser that outperforms other previous steganalytic methods.

Research on Multi-Core Network Equipment Virus Defense System

With the arrival of the wave of information technology, the business activities of a variety of business systems via the network to complete. But the virus to exploit system vulnerabilities to sneak into the enterprise information network server, the enterprise network into a leak and suffered the double threat of external hackers. Leverage existing security infrastructure, enterprise networks, statistical analysis of all possible virus invasion point, combined with a good virus defense technology layers protection system vulnerabilities, the formation of a whole network antivirus, coordinated operations, a unified management modernization virus defense systems.

Integrated Security Process Improvement Framework for Systems and Services

Security of systems and services has been dominant research area in recent years as today's cloud services, big data and networked systems, especially when they provide wireless application access where personal and confidential data to be transmitted across the networked systems. Numerous tools and technologies are available to ensure system's security; however, external threats to computer systems and applications residents thereon, are also becoming more and more sophisticated and on the increase. Therefore, the key aim of this research is to integrate security engineering techniques and process with systems development life-cycle and process improvement frameworks. This paper presents a framework that consists of two components: 1) a security assessment model to looks at the existing security infrastructure of an organisation to determine its security maturity level; and 2) a security improvement maturity model to suggest an improvement mechanism for the organisation to progress from one maturity level to the next higher level. The intention is to provide a scheme to improve the organisation's Systems and network security with the aim that it becomes more efficient and effective than before.

Ontological Engineering Approach towards Trust Oriented Security Framework for Adhoc Networks

Conventionally, user authentication and access control mechanisms would be almost enough, to handle security for stand-alone computers and small networks. Ad hoc networks are illustrated by multi-hop wireless connectivity and recurrently changing network topology which have made them infrastructure less. Adding trust to the existing security infrastructures would improvise the security of these environments. Describing trust relations and their sub-components using ontologies, creates a methodology and mechanism in order to efficiently design and engineer trust networks. This is going to be used as a service for providing trust for ad hoc network at any level i.e. routing, authentication or access control. A trust oriented security framework for adhoc network using ontological engineering approach is proposed by modeling ad hoc network, the OLSR (Optimized Link State Routing) protocol and trust model as OWL (Ontology Web language) ontologies, which are integrated using Jena. In this model, a trustor can calculate its trust about trustee and use the calculated trust values to make decisions depending on the context of the application or interaction about granting or rejecting it. A number of experiments with a possible implementation of suggested framework are performed to make out the characteristics of the trust model and its effect on the ad hoc network operations.

Role-based access control for a Grid system using OGSA-DAI and Shibboleth

In this paper, we propose a new role-based access control (RBAC) system for Grid data resources in the Open Grid Services Architecture Data Access and Integration (OGSA-DAI). OGSA-DAI is a widely used framework for integrating data resources in Grids. However, OGSA-DAI's identity-based access control causes substantial administration overhead for the resource providers in virtual organizations (VOs) because of the direct mapping between individual Grid users and the privileges on the resources. To solve this problem, we used the Shibboleth, an attribute authorization service, to support RBAC within the OGSA-DAI. In addition, access control policies need to be specified and managed across multiple VOs. For the specification of access control policies, we used the Core and Hierarchical RBAC profile of the eXtensible Access Control Markup Language (XACML); and for distributed administration of those policies and the user-role assignments, we used the Object, Metadata and Artifacts Registry (OMAR). OMAR is based on the e-business eXtensible Markup Language (ebXML) registry specifications developed to achieve interoperable registries and repositories. Our RBAC system provides scalable and fine-grain access control and allows privacy protection. It also supports dynamic delegation of rights and user-role assignments, and reduces the administration overheads for the resource providers because they need to maintain only the mapping information from VO roles to local database roles. Moreover, unnecessary mapping and connections can be avoided by denying invalid requests at the VO level. Performance analysis shows that our RBAC system adds only a small overhead to the existing security infrastructure of OGSA-DAI.

Role-Based Access Control in a Data Grid Using the Storage Resource Broker and Shibboleth

In this paper, we propose a role-based access control (RBAC) system for data resources in the Storage Resource Broker (SRB). The SRB is a Data Grid management system, which can integrate heterogeneous data resources of virtual organizations (VOs). The SRB stores the access control information of individual users in the Metadata Catalog (MCAT) database. However, because of the specific MCAT schema structure, this information can only be used by the SRB applications. If VOs also have many non-SRB applications, each with its own storage format for user access control information, it creates a scalability problem with regard to administration. To solve this problem, we developed a RBAC system with Shibboleth, which is an attribute authorization service currently being used in many Grid environments. Thus, the administration overhead is reduced because the role privileges of individual users are now managed by Shibboleth, not by MCAT or applications. In addition, access control policies need to be specified and managed across multiple VOs. For the specification of access control policies, we used the Core and Hierarchical RBAC profile of the eXtensible Access Control Markup Language (XACML); and for distributed administration of those policies, we used the Object, Metadata and Artifacts Registry (OMAR). OMAR is based on the e-business eXtensible Markup Language (ebXML) registry specifications developed to achieve interoperable registries and repositories. Our RBAC system provides scalable and fine-grain access control and allows privacy protection. Performance analysis shows that our system adds only a small overhead to the existing security infrastructure of the SRB.

Managing Role-Based Access Control Policies for Grid Databases in OGSA-DAI Using CAS

In this paper, we present a role-based access control method for accessing databases through the Open Grid Services Architecture – Data Access and Integration (OGSA-DAI) framework. OGSA-DAI is an efficient Grid-enabled middleware implementation of interfaces and services to access and control data sources and sinks. However, in OGSA-DAI, access control causes substantial administration overhead for resource providers in virtual organizations (VOs) because each of them has to manage a role-map file containing authorization information for individual Grid users. To solve this problem, we used the Community Authorization Service (CAS) provided by the Globus Toolkit to support the role-based access control (RBAC) within OGSA-DAI. CAS uses the Security Assertion Markup Language (SAML). Our method shows that CAS can support a wide range of security policies using role-privileges, role hierarchies, and constraints. The resource providers need to maintain only the mapping information from VO roles to local database roles and the local policies in the role-map files, so that the number of entries in the role-map file is reduced dramatically. Also, unnecessary authentication, mapping and connections can be avoided by denying invalid requests at the VO level. Thus, our access control method provides increased manageability for a large number of users and reduces day-to-day administration tasks of the resource providers, while they maintain the ultimate authority over their resources. Performance analysis shows that our method adds very little overhead to the existing security infrastructure of OGSA-DAI.

End-to-end Security in Telemedical Networks – A Practical Guideline

The interconnection of medical networks in different healthcare institutions will be constantly increasing over the next few years, which will require concepts for securing medical data during transfer, since transmitting patient related data via potentially insecure public networks is considered a violation of data privacy. The aim of our work was to develop a model-based approach towards end-to-end security which is defined as continuous security from point of origin to point of destination in a communication process. We show that end-to-end security must be seen as a holistic security concept, which comprises the following three major parts: authentication and access control, transport security, as well as system security. For integration into existing security infrastructures abuse case models were used, which extend UML use cases, by elements necessary to describe abusive interactions. Abuse case models can be constructed for each part mentioned above, allowing for potential security risks in communication from point of origin to point of destination to be identified and counteractive measures to be directly derived from the abuse case models. The model-based approach is a guideline to continuous risk assessment and improvement of end-to-end security in medical networks. Validity and relevance to practice will be systematically evaluated using close-to-reality test networks as well as in production environments.

Role-Based Access Control for Grid Database Services Using the Community Authorization Service

In this paper, we propose a role-based access control (RBAC) method for grid database services in open grid services architecture-data access and integration (OGSA-DAI). OGSA-DAI is an efficient grid-enabled middleware implementation of interfaces and services to access and control data sources and sinks. However, in OGSA-DAI, access control causes substantial administration overhead for resource providers in virtual organizations (VOs) because each of them has to manage a role-map file containing authorization information for individual grid users. To solve this problem, we used the community authorization service (CAS) provided by the globus toolkit to support the RBAC within the OGSA-DAI framework. The CAS grants the membership on VO roles to users. The resource providers then need to maintain only the mapping information from VO roles to local database roles in the role-map files, so that the number of entries in the role-map file is reduced dramatically. Furthermore, the resource providers control the granting of access privileges to the local roles. Thus, our access control method provides increased manageability for a large number of users and reduces day-to-day administration tasks of the resource providers, while they maintain the ultimate authority over their resources. Performance analysis shows that our method adds very little overhead to the existing security infrastructure of OGSA-DAI