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Automated Vulnerability Testing via Executable Attack Graphs. 2020 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). :1–10.
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2020. Cyber risk assessments are an essential process for analyzing and prioritizing security issues. Unfortunately, many risk assessment methodologies are marred by human subjectivity, resulting in non-repeatable, inconsistent findings. The absence of repeatable and consistent results can lead to suboptimal decision making with respect to cyber risk reduction. There is a pressing need to reduce cyber risk assessment uncertainty by using tools that use well defined inputs, producing well defined results. This paper presents Automated Vulnerability and Risk Analysis (AVRA), an end-to-end process and tool for identifying and exploiting vulnerabilities, designed for use in cyber risk assessments. The approach presented is more comprehensive than traditional vulnerability scans due to its analysis of an entire network, integrating both host and network information. AVRA automatically generates a detailed model of the network and its individual components, which is used to create an attack graph. Then, AVRA follows individual attack paths, automatically launching exploits to reach a particular objective. AVRA was successfully tested within a virtual environment to demonstrate practicality and usability. The presented approach and resulting system enhances the cyber risk assessment process through rigor, repeatability, and objectivity.
Countering Cybersecurity and Counterfeit Material Threats in Test Systems. 2019 IEEE AUTOTESTCON. :1–5.
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2019. Automatic test systems designed to validate the performance of military and aerospace products have always been held to a higher standard; moreover, emerging threats to data security and instrumentation integrity continue to raise this bar. Engineers are faced with growing pressure to not only ensure that the unit under test (UUT) meets all design criteria, but that it remains safe from malicious attacks aimed at gaining access to test parameters or results, controlling of test sequences and functionality, downloading malware, or impacting functionality by way of counterfeit parts installed in instrumentation. This paper will delve into the cybersecurity issue from the perspective of the test development environment, including the use of test executives, and the challenges associated with minimizing impact to data integrity and access to control. An undetected data breach on military / aerospace automated test equipment (ATE) holds significance beyond just the test system, since mission critical electronics associated with avionics, radar, electronic warfare and missile assemblies must also be protected. One topic discussed will be the impact of adopting methods and procedures detailed in the Department of Defense's (DoD) Application Security Technical Implementation Guide, which is based on NIST documents and details how to manage and maintain a secure software-based system such as an ATE system. Another aspect of cybersecurity that is often overlooked in the world of commercial-off-the-shelf (COTS) instrumentation and switching systems is the potential impact on the UUT from substandard counterfeit parts and those embedded with malware. Concerns with counterfeit material can encompass a range of threats including the re-purposing of used parts and new knockoff parts with substandard operating characteristics represented and sold as new hardware. One of the most concerning aspects, parts intentionally infected with malware, can pose a significant risk to personnel and national security. We will discuss various strategies aimed at countering these threats, including the adoption of policies and procedures outlined in AS9100D and AS5553, which can mitigate these risks.
An Open Source Approach to Automating Surveillance and Compliance of Automatic Test Systems. 2019 IEEE AUTOTESTCON. :1–8.
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2019. With the disconnected nature of some Automatic Test Systems, there is no possibility for a centralized infrastructure of sense and response in Cybersecurity. For scalability, a cost effective onboard approach will be necessary. In smaller companies where connectivity is not a concern, costly commercial solutions will impede the implementation of surveillance and compliance options. In this paper we propose to demonstrate an open source strategy using freely available Security Technical Implementation Guidelines (STIGs), internet resources, and supporting software stacks, such as OpenScap, HubbleStack, and (ElasticSearch, Logstash, and Kibana (ElasticStack)) to deliver an affordable solution to this problem. OpenScap will provide tools for managing system security and standards compliance. HubbleStack will be employed to automate compliance via its components: NOVA (an auditing engine), Nebula (osquery integration), Pulsar (event system) and Quasar (reporting system). Our intention is utilize NOVA in conjunction with OpenScap to CVE (Common Vulnerabilities and Exposures) scan and netstat for open ports and processes. Additionally we will monitor services and status, firewall settings, and use Nebula's integration of Facebook's osquery to detect vulnerabilities by querying the Operating System. Separately we plan to use Pulsar, a fast file integrity manger, to monitor the integrity of critical files such as system, test, and Hardware Abstraction Layer (HAL) software to ensure the system retains its integrity. All of this will be reported by Quasar, HubbleStack's reporting engine. We will provide situational awareness through the use of the open source Elastic Stack. ElasticSearch is a RESTful search and analytics engine. Logstash is an open source data processing pipeline that enables the ingestion of data from multiple sources sending it through extensible interfaces, in this case ElasticSearch. Kibana supports the visualization of data. Essentially Elastic Stack will be the presentation layer, HubbleStack will be the broker of the data to Elastic Stash, with the other HubbleStack components feeding that data. All of the tools involved are open source in nature, reducing the cost to the overhead required to keep configurations up to date, training on use, and analytics required to review the outputs.