Security Information And Event Management System Research Articles

Breaking Alert Fatigue: AI-Assisted SIEM Framework for Effective Incident Response

Contemporary security information and event management (SIEM) solutions struggle to identify critical security incidents effectively due to the overwhelming number of false alerts generated by disparate security products, which results in significant alert fatigue and hinders effective incident response. To overcome this challenge, we propose a next-generation SIEM framework that integrates security orchestration automation and response capabilities and utilizes a divide-and-conquer strategy to mitigate the impact of low-quality IDS alerts. The proposed framework leverages advanced machine learning and data visualization tools—including a cost-sensitive learning method and an event segmenting algorithm—to filter and correlate alerts plus an augmented visualization tool to expedite the triage process. The proposed framework was evaluated experimentally on a dataset collected from a real-world enterprise network, and we report highly convincing results. The alert screening scheme demonstrates significant potential for real-world security operations. We believe that our findings will contributing to the development of a next-generation SIEM system that effectively addresses alert fatigue and lays the foundation for future research in this field.

Comparative Analysis of Open Source Security Information & Event Management Systems (SIEMs)

A Security Information and Event Management system (SIEM) is a tool used to collect, analyze, normalize and correlate data from various devices to identify potential cyber threats almost in real-time. SIEM provides a unified approach to security issues through two zones: Security Information Management (SIM) and Security Event Management (SEM). SIM deals with managing logs and reporting, while SEM deals with event management and real-time monitoring. SIEM tools collect data events in a central unit from various devices, normalize their format, analyze them, and generate reports and alerts. SIEM combines the ability of log management to generate a compliance report with the ability to manage threats. However, the central approach may present significant disadvantages, such as slowing system performance and complicating the prioritization of queries.

Open source SIEM solutions for an enterprise

PurposeThe security of applications, systems and networks has always been the source of great concern for both enterprises and common users. Different security tools like intrusion detection system/intrusion prevention system and firewalls are available that provide preventive security to the enterprise networks. However, security information and event management (SIEM) systems use these tools in combination to collect events from diverse data sources across the network. SIEM is a proactive tool that processes the events to present a unified security view of the whole network at one location. SIEM system has, therefore, become an essential component of an enterprise network security architecture. However, from various options available, the selection of a suitable and cost-effective open source SIEM solution that can effectively meet most of the security requirements of small-to-medium-sized enterprises (SMEs) is not simple because of the lack of strong analysis.Design/methodology/approachIn this work, the authors first review the security challenges faced by different SME sectors and then consider a comprehensive comparative analysis of the capabilities of well-known open source SIEM solutions. Based on this, the authors provide requirements based recommendations of open source SIEM solutions for SMEs. This paper aims to provide a valuable resource that can be referred to by SMEs for the selection of a SIEM system best suited to their organization’s security posture.FindingsSecurity requirements of SMEs vary according to their network infrastructure; therefore, every open source SIEM solution would not be suitable for an SME. Selection of a SIEM solution from available open source solutions based upon the security requirements of an SME network is a critical task. Therefore, in this work, a meaningful insight for the selection of an appropriate SIEM solution for SMEs is provided.Originality/valueMajor contribution of this work is the mapping of the security requirements of the SME sectors under consideration, against the open source SIEM options to provide meaningful insight for SMEs in the selection of an appropriate solution.

SIEM4GS: Security Information and Event Management for a Virtual Ground Station Testbed

As the space sector continues to grow, so do the cybersecurity risks. As large as the attack surface of a space system is, the ground segment remains an attractive source of intrusion points, not only because of its relative accessibility but also because the ground system is often viewed as little more than a conventional IT system. Thus, a representative security assessment of a space system cannot avoid addressing the vulnerabilities of the associated ground system and the relevant threats. This motivates the construction of a virtual ground station testbed, as part of larger reference platform, to support our ongoing research on the cybersecurity of space systems. Presented here is a discussion of the preliminary work being undertaken at the University of South Australia node of the SmartSat Cooperative Research Centre on such a testbed. A distinguishing feature of the testbed is the integration of a security information and event management (SIEM) system justifying the name of the testbed, “SIEM4GS”. Based on the latest literature on ground stations, a logical architecture and an implementation plan involving only open-source software building blocks for SIEM4GS are proposed. Features of the ground station and SIEM services are discussed. A plan is provided on how to extend the SIEM system from a primarily “detect” role in the NIST Cybersecurity Framework to a “detect and respond” role.

Secured Access Control in Security Information and Event Management Systems

Nowadays, Security Information and Event Management (SIEM) is very important in software. SIEM stores and monitors events in software and unauthorized access to logs can prompt different security threats such as information leakage and violation of confidentiality. In this paper, a novel method is suggested for secured and integrated access control in the SIEM. First, the key points where the SIEM accesses the information within the software is specified and integrated policies for access control are developed in them. Accordingly, the threats entered into the access control module embedded in this system are carefully detected. By applying the proposed method, it is possible to provide the secured and integrated access control module for SIEM as well as the security of the access control module significantly increases in these systems. The method is implemented in the three stages of the requirements analysis for the establishment of a secure SIEM system, secure architectural design, and secure coding. The access control module is designed to create a secured SIEM and the test tool module is designed for evaluating the access control module vulnerabilities. Also, to evaluate the proposed method, the dataset is considered with ten thousand records, and the accuracy is calculated. The outcomes show the accuracy of the proposed method is significantly improved. The results of this paper can be used for designing an integrated and secured access control system in SIEM systems.

SPEAR SIEM: A Security Information and Event Management system for the Smart Grid

The technological leap of smart technologies has brought the conventional electrical grid in a new digital era called Smart Grid (SG), providing multiple benefits, such as two-way communication, pervasive control and self-healing. However, this new reality generates significant cybersecurity risks due to the heterogeneous and insecure nature of SG. In particular, SG relies on legacy communication protocols that have not been implemented having cybersecurity in mind. Moreover, the advent of the Internet of Things (IoT) creates severe cybersecurity challenges. The Security Information and Event Management (SIEM) systems constitute an emerging technology in the cybersecurity area, having the capability to detect, normalise and correlate a vast amount of security events. They can orchestrate the entire security of a smart ecosystem, such as SG. Nevertheless, the current SIEM systems do not take into account the unique SG peculiarities and characteristics like the legacy communication protocols. In this paper, we present the Secure and PrivatE smArt gRid (SPEAR) SIEM, which focuses on SG. The main contribution of our work is the design and implementation of a SIEM system capable of detecting, normalising and correlating cyberattacks and anomalies against a plethora of SG application-layer protocols. It is noteworthy that the detection performance of the SPEAR SIEM is demonstrated with real data originating from four real SG use case (a) hydropower plant, (b) substation, (c) power plant and (d) smart home.

A User Centric Machine Learning Framework for Cyber Security Operation Center

In order to ensure a company's Internet security, SIEM (Security Information and Event Management) system is in place to simplify the various preventive technologies and flag alerts for security events. Inspectors (SOC) investigate warnings to determine if this is true or not. However, the number of warnings in general is wrong with the majority and is more than the ability of SCO to handle all awareness, because of this, malicious possibility. Attacks and compromised hosts may be wrong. Machine learning is a possible approach to improving the wrong positive rate and improving the productivity of SOC analysts. In this article, we create a user-centric engineer learning framework for the Internet Safety Functional Center in the real organizational context. We discuss regular data sources in SOC, their workflow, and how to process this data and create an effective machine learning system. This article is a immediate two groups of readers. The first group is intelligent researchers who have no knowledge of data scientists or computer safety fields but who engineer should develop machine learning Systems for machine safety. The second groups of visitors are Internet security practitioners that have deep knowledge and expertise in Cyber Security, but do Machine learning experiences do not exist and I'd like to create one by themselves. At the end of the paper, we use the account as an example to demonstrate full steps from data collection, label creation, feature engineering, machine learning algorithm and sample performance evaluations using the computer built in the SOC production of Seyondike

Anomaly Detection Trusted Hardware Sensors for Critical Infrastructure Legacy Devices.

Critical infrastructures and associated real time Informational systems need some security protection mechanisms that will be able to detect and respond to possible attacks. For this reason, Anomaly Detection Systems (ADS), as part of a Security Information and Event Management (SIEM) system, are needed for constantly monitoring and identifying potential threats inside an Information Technology (IT) system. Typically, ADS collect information from various sources within a CI system using security sensors or agents and correlate that information so as to identify anomaly events. Such sensors though in a CI setting (factories, power plants, remote locations) may be placed in open areas and left unattended, thus becoming targets themselves of security attacks. They can be tampering and malicious manipulated so that they provide false data that may lead an ADS or SIEM system to falsely comprehend the CI current security status. In this paper, we describe existing approaches on security monitoring in critical infrastructures and focus on how to collect security sensor–agent information in a secure and trusted way. We then introduce the concept of hardware assisted security sensor information collection that improves the level of trust (by hardware means) and also increases the responsiveness of the sensor. Thus, we propose a Hardware Security Token (HST) that when connected to a CI host, it acts as a secure anchor for security agent information collection. We describe the HST functionality, its association with a host device, its expected role and its log monitoring mechanism. We also provide information on how security can be established between the host device and the HST. Then, we introduce and describe the necessary host components that need to be established in order to guarantee a high security level and correct HST functionality. We also provide a realization–implementation of the HST overall concept in a FPGA SoC evaluation board and describe how the HST implementation can be controlled. In addition, in the paper, two case studies where the HST has been used in practice and its functionality have been validated (one case study on a real critical infrastructure test site and another where a critical industrial infrastructure was emulated in our lab) are described. Finally, results taken from these two case studies are presented, showing actual measurements for the in-field HST usage.

Problems of implementing SIEM systems in the practice of managing information security of economic entities

The aim of the study is to increase the efficiency of information security management of economic entities that use Security Information and Event Management (SIEM) systems by identifying and solving the main problems of introducing these systems into the management of information security practices of economic entities [1-3]. Materials and research methods . Based on the analysis of scheme of the typical architecture of the SIEM system and the standard process of introducing the SIEM system into practice of managing information security of various types of economic entities, the main problems of the installation and configuration of the SIEM system are determined, and ways to solve them are substantiated. During the installation and configuration of the SIEM system, the team of customers and contractors may experience the following typical problems. The process of installing and configuring the SIEM system as part of a systematic approach is considered as a set of interconnected resource-based procedures that implement the installation and configuration of individual components of the SIEM system. Out of the whole set of these procedures, the procedures to be automated are determined. To determine the rational structure of the process of automated installation and configuration of the SIEM system, a method of network planning and management is proposed [4-5], which also allows you to evaluate the effectiveness of implementing the SIEM system in the practice of managing information security of economic entities based on the development and calculation of network schedules. Results. In this work, we developed ways to solve the problems of introducing SIEM systems into information security management practice: simplifying the SIEM system, which is a rejection of rarely used modules and rebuilding the architecture of the SIEM system; automation of the process of typical installation and general setup of the SIEM system, which represents the development of a methodology for automating the procedure of typical installation and general setup of the SIEM system and software module that implements the developed methodology; a combined approach, which is a joint application of the two above approaches, which allows you to bring the SIEM system closer as a product to the “box option. The paper presents reasonable proposals for improving the implementation of the SIEM system, based on the development and application of automated procedures for the typical installation and configuration of the SIEM system, which reduces the time spent on the implementation of the SIEM system, increases the convenience of performing these procedures, and in general can lead to the “boxed version of the solution for a product of this class of information security event management systems. Conclusion. The proposed ways to solve the problems of implementing SIEM systems in the practice of managing information security of economic entities based on the optimization of the installation and configuration of SIEM systems can accelerate the distribution and implementation of information security event management systems and increase efficiency by automating standard installation procedures and SIEM system settings.

Formal modeling and verification of security controls for multimedia systems in the cloud

Organizations deploy the Security Information and Event Management (SIEM) systems for centralized management of security alerts for securing their multimedia content. The SIEM system not only prese...

Supervised PU Learning for Cyber Security Event Prioritization

To ensure the cyber security of an enterprise, typically a SIEM (Security Information and Event Management) system is in place to alert security events and assign each of them a severity score based on some pre-determined rules. Analysts in the security operations center (SOC) investigate the high severity events to decide if they are truly malicious or not. However, generally, the number of events is overwhelmingly large, far exceeding the SOC’s budget to handle them. There is a great need for a machine learning system to assist for the accurate detection of malicious events. Traditional supervised learning algorithms cannot be directly applied to this problem because there are only a very small percentage of events that are verified and labelled malicious events (called positively labelled) by SOC analysts and vast majority of events are unlabeled as they are not even investigated. In this paper, we propose to aggregate security events to host level and use supervised PU (Positive Unlabeled) learning technique to accurately detect the high risk hosts. We use Support Vector Machine with radial basis kernel for label propagation and classification and achieve a high classification accuracy of AUC (area under the curve) of 0.96 and lift of 18 relative to the current rule-based alerting mechanism.

A high-level domain-specific language for SIEM (design, development and formal verification)

Organizations deploy security information and event management (SIEM) systems for centralized management of security events. The real-time security monitoring capability of the SIEM depends on the correlation process where events data are matched against the security rules. Most SIEM systems use general purpose languages to define security rules. Creating new rules in general purpose languages require excellent programming skills in the proprietary language and intimate knowledge of events. This paper introduces a high-level domain-specific language (HDSL) which simplifies rule creation for the SIEM system. We formally specify the HDSL with extended Backus–Naur form grammar in another tool for language recognition according to the model driven engineering approach. In our implementation framework, the rules defined in the HDSL are converted in the standard event processing language. For evaluation purpose, the converted security rules are tested on the service real-time data security analytics. The results indicate that the rules are converted accurately and generate alarms when specific attacks are detected. For checking correctness of the HDSL, formal verification is carried out using satisfiability modulo theory and Z3 solver. The results are evaluated under diverse attack scenarios, which reveal that HDSL is functioning correctly. The HDSL enhances the SIEM correlation capabilities by providing a tranquil approach for writing the correlation rules.

Towards a system for complex analysis of security events in large-scale networks

After almost two decades of development, modern Security Information and Event Management (SIEM) systems still face issues with normalisation of heterogeneous data sources, high number of false positive alerts and long analysis times, especially in large-scale networks with high volumes of security events. In this paper, we present our own prototype of SIEM system, which is capable of dealing with these issues. For efficient data processing, our system employs in-memory data storage (SAP HANA) and our own technologies from the previous work, such as the Object Log Format (OLF) and high-speed event normalisation. We analyse normalised data using a combination of three different approaches for security analysis: misuse detection, query-based analytics, and anomaly detection. Compared to the previous work, we have significantly improved our unsupervised anomaly detection algorithms. Most importantly, we have developed a novel hybrid outlier detection algorithm that returns ranked clusters of anomalies. It lets an operator of a SIEM system to concentrate on the several top-ranked anomalies, instead of digging through an unsorted bundle of suspicious events. We propose to use anomaly detection in a combination with signatures and queries, applied on the same data, rather than as a full replacement for misuse detection. In this case, the majority of attacks will be captured with misuse detection, whereas anomaly detection will highlight previously unknown behaviour or attacks. We also propose that only the most suspicious event clusters need to be checked by an operator, whereas other anomalies, including false positive alerts, do not need to be explicitly checked if they have a lower ranking. We have proved our concepts and algorithms on a dataset of 160 million events from a network segment of a big multinational company and suggest that our approach and methods are highly relevant for modern SIEM systems.

Toward an Efficient Ontology-Based Event Correlation in SIEM

Cooperative intrusion detection use several intrusion detection systems (IDS) and analyzers in order to build a reliable overview of the monitored system trough a central security information and event management system (SIEM). In such environment, the definition of a shared vocabulary describing the exchanged information between tools is prominent. Since these pieces of information are structured, we propose in this paper to use an ontological representation based on Description Logics (DLs) which is a powerful tool for knowledge representation. Moreover, DLs are able to ensure a decidable reasoning. An alert correlation prototype is presented using this ontology, and an illustrative attack scenario is carried out to show the usefulness of the proposed ontology.