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1. Using Semantic-Web Technologies for Situation Assessments of Ethical Hacking High-Value Targets

   https://doi.org/10.34190/EWS.21.070  

   Suresh, S. ; Fisher, R. ; Patole, R. ; Zeyher, A. ; Heverin, T. ( June 2021 , European Conference on Cyber Warfare and Security)

   Ethical hacking consists of scanning for targets, evaluating the targets, gaining access, maintaining access, and clearing tracks. The evaluation of targets represents a complex task due to the number of IP addresses, domain names, open ports, vulnerabilities, and exploits that must be examined. Ethical hackers synthesize data from various hacking tools to determine targets that are of high value and that are highly susceptible to cyber-attacks. These tasks represent situation assessment tasks. Previous research considers situation assessment tasks to be tasks that involve viewing an initial set of information about a problem and subsequently piecing together more information to solve the problem. Our research used semantic-web technologies, including ontologies, natural language processing (NLP), and semantic queries, to automate the situation assessment tasks conducted by ethical hackers when evaluating targets. More specifically, our research focused on automatically identifying education organizations that use industrial control system protocols which in turn have highly exploitable vulnerabilities and known exploits. We used semantic-web technologies to reduce an initial dataset of 126,636 potential targets to 155 distinct targets with these characteristics. Our research adds to previous research on situation assessment by showing how semantic-web technologies can be used to reduce the complexity of situation assessment tasks. 

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2. Exploring Ontologies for Mitigation Selection of Industrial Control System Vulnerabilities

   https://doi.org/https://doi.org/10.34190/iccws.17.1.32  

   Heverin, T. ; Cordano, M. ; Zeyher, A. ; Lashner, M. ; Suresh, S. ( March 2022 , 17th International Conference on Cyber Warfare and Security)

   Mitigating vulnerabilities in industrial control systems (ICSs) represents a highly complex task. ICSs may contain an abundance of device types, all with unique software and hardware components. Upon discovering vulnerabilities on ICS devices, cyber defenders must determine which mitigations to implement, and which mitigations can apply across multiple vulnerabilities. Cyber defenders need techniques to optimize mitigation selection. This exploratory research paper shows how ontologies, also known as linked-data models, can potentially be used to model ICS devices, vulnerabilities, and mitigations, as well as to identify mitigations that can remediate or mitigate multiple vulnerabilities. Ontologies can be used to reduce the complexity of a cyber defender’s role by allowing for insights to be drawn, especially in the ICS domain. Data are modelled from the Common Platform Enumeration (CPE), the National Vulnerability Database (NVD), standardized list of controls from the National Institute of Standards and Technology (NIST), and ICS Cyber Emergency Response Team (CERT) advisories. Semantic queries provide the techniques for mitigation prioritization. A case study is described for a selected programmable logic controller (PLC), its known vulnerabilities from the NVD, and recommended mitigations from ICS CERT. Overall, this research shows how ontologies can be used to link together existing data sources, to run queries over the linked data, and to allow for new insights to be drawn for mitigation selection. 

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3. An Ontology-Based Framework for Formal Verification of Safety and Security Properties of Control Logics

   https://doi.org/10.1109/ECAI54874.2022.9847508  

   Neupane, Ramesh ; Mehrpouyan, Hoda ( June 2022 , 2022 14th International Conference on Electronics, Computers and Artificial Intelligence (ECAI))

   Any safety issues or cyber attacks on an Industrial Control Systems (ICS) may have catastrophic consequences on human lives and the environment. Hence, it is imperative to have resilient tools and mechanisms to protect ICS. To verify the safety and security of the control logic, complete and consistent specifications should be defined to guide the testing process. Second, it is vital to ensure that those requirements are met by the program control algorithm. In this paper, we proposed an approach to formally define the system specifications, safety, and security requirements to build an ontology that is used further to verify the control logic of the PLC software. The use of ontology allowed us to reason about semantic concepts, check the consistency of concepts, and extract specifications by inference. For the proof of concept, we studied part of an industrial chemical process to implement the proposed approach. The experimental results in this work showed that the proposed approach detects inconsistencies in the formally defined requirements and is capable of verifying the correctness and completeness of the control logic. The tools and algorithms designed and developed as part of this work will help technicians and engineers create safer and more secure control logic for ICS processes. 

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4. Architectural Security Weaknesses in Industrial Control Systems (ICS) an Empirical Study Based on Disclosed Software Vulnerabilities

   https://doi.org/10.1109/ICSA.2019.00012  

   Gonzalez, Danielle ; Alhenaki, Fawaz ; Mirakhorli, Mehdi ( March 2019 , 2019 IEEE International Conference on Software Architecture (ICSA))

   Industrial control systems (ICS) are systems used in critical infrastructures for supervisory control, data acquisition, and industrial automation. ICS systems have complex, component-based architectures with many different hardware, software, and human factors interacting in real time. Despite the importance of security concerns in industrial control systems, there has not been a comprehensive study that examined common security architectural weaknesses in this domain. Therefore, this paper presents the first in-depth analysis of 988 vulnerability advisory reports for Industrial Control Systems developed by 277 vendors. We performed a detailed analysis of the vulnerability reports to measure which components of ICS have been affected the most by known vulnerabilities, which security tactics were affected most often in ICS and what are the common architectural security weaknesses in these systems. Our key findings were: (1) Human-Machine Interfaces, SCADA configurations, and PLCs were the most affected components, (2) 62.86% of vulnerability disclosures in ICS had an architectural root cause, (3) the most common architectural weaknesses were “Improper Input Validation”, followed by “Im-proper Neutralization of Input During Web Page Generation” and “Improper Authentication”, and (4) most tactic-related vulnerabilities were related to the tactics “Validate Inputs”, “Authenticate Actors” and “Authorize Actors”. 

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5. LINKING EXPLOITS FROM THE DARK WEB TO KNOWN VULNERABILITIES FOR PROACTIVE CYBER THREAT INTELLIGENCE: AN ATTENTION-BASED DEEP STRUCTURED SEMANTIC MODEL1

   Samtani, S ; Chai, Y ; and Chen, H. ( June 2022 , MIS quarterly)

   Black hat hackers use malicious exploits to circumvent security controls and take advantage of system vulnerabilities worldwide, costing the global economy over $450 billion annually. While many organizations are increasingly turning to cyber threat intelligence (CTI) to help prioritize their vulnerabilities, extant CTI processes are often criticized as being reactive to known exploits. One promising data source that can help develop proactive CTI is the vast and ever-evolving Dark Web. In this study, we adopted the computational design science paradigm to design a novel deep learning (DL)-based exploit-vulnerability attention deep structured semantic model (EVA-DSSM) that includes bidirectional processing and attention mechanisms to automatically link exploits from the Dark Web to vulnerabilities. We also devised a novel device vulnerability severity metric (DVSM) that incorporates the exploit post date and vulnerability severity to help cybersecurity professionals with their device prioritization and risk management efforts. We rigorously evaluated the EVA-DSSM against state-of-the-art non-DL and DL-based methods for short text matching on 52,590 exploit-vulnerability linkages across four testbeds: web application, remote, local, and denial of service. Results of these evaluations indicate that the proposed EVA-DSSM achieves precision at 1 scores 20% - 41% higher than non-DL approaches and 4% - 10% higher than DL-based approaches. We demonstrated the EVA-DSSM’s and DVSM’s practical utility with two CTI case studies: openly accessible systems in the top eight U.S. hospitals and over 20,000 Supervisory Control and Data Acquisition (SCADA) systems worldwide. A complementary user evaluation of the case study results indicated that 45 cybersecurity professionals found the EVA-DSSM and DVSM results more useful for exploit-vulnerability linking and risk prioritization activities than those produced by prevailing approaches. Given the rising cost of cyberattacks, the EVA-DSSM and DVSM have important implications for analysts in security operations centers, incident response teams, and cybersecurity vendors. 

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