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Fink, Glenn A.

Publications and source records attributed to Fink, Glenn A..

ROTOR: Research to Operations and Operations to Research

PNNL’s Research to Operations/Operations to Research (ROTOR) Program fosters a cybersecurity operations to researcher collaboration, identifying hard problems and challenges for cyber defenders and bringing researcher science disciplines to these challenges. ROTOR allows PNNL’s cyber defenders to better protect the laboratory but also fosters innovation and incubation of solutions for our sponsor missions across DOE, DOD, DHS and the intelligence community. Our sponsors and their missions are faced with many of the same cyber defense challenges that PNNL faces. By using our own laboratory security operations environment as an innovation generator and testing ground, allowing research to be tested and tried, our sponsors are directly benefitted. PNNL is in a unique position to combine our world class research organization with enterprise cybersecurity operations. ROTOR is taking advantage of this to bring PNNL cybersecurity research projects into an operational environment within PNNL’s Cyber Security Operations Center. With ROTOR, PNNL researchers gain the advantage of operational experience and expertise and have an avenue for showcasing research in an operational environment. This helps to advance PNNL research, prove operability of PNNL projects to its sponsors, and provide real-world insight to real-world problems for our cybersecurity research agenda. ROTOR is the conduit for PNNL cybersecurity research to find its way to operational use. PNNL researchers and engineers are informed by real-world operations and operations has access to current PNNL research and engineering capabilities. All of this leads to improved reputation for PNNL as a provider of national security solutions that are tried and tested. To date, ROTOR has collaborated with six projects, enabling each to conduct operational work within the CSOC.

97 MATHEMATICS AND COMPUTING↗

Adversarial Artificial Intelligence: State of the Malpractice

Warfare systems are increasingly being supported by artificial intelligence (AI), and its influence is growing. As AI becomes a warfare enabler it has also become a target. For example, AI-enabled machine vision systems can be trivially deceived by specially formulated camouflage. Many approaches to making AI more resilient to protect against specific attacks fail to generalize. However, attacks often do generalize across models trained for the same task, regardless of architecture or training data. This paper will illustrate the state of the practice in offensive and defensive AI and clarify some myths about AI's triumphs and failures in the real world.

Artificial intelligence, AI, cybersecurity, milita↗

Helping IT and OT Defenders Collaborate

Cyber-physical systems, especially in critical infrastructures, have become primary hacking targets in international conflicts and diplomacy. However, cyber-physical systems present unique challenges to defenders, starting with an inability to communicate. This paper outlines the results of our interviews with information technology (IT) defenders and operational technology (OT) operators and seeks to address lessons learned from them in the structure of our notional solutions. We pre-sent two problems in this paper: (1) the difficulty of coordinat-ing detection and response between defenders who work on the cyber/IT and physical/OT sides of cyber-physical infrastruc-tures, and (2) the difficulty of estimating the safety state of a cyber-physical system while an intrusion is underway but be-fore damage can be effected by the attacker. To meet these chal-lenges, we propose two solutions: (1) a visualization that will enable communication between IT defenders and OT operators, and (2) a machine-learning approach that will estimate the distance from normal the physical system is operating and send information to the visualization.

Cyber Physical Systems, internet of things, visual↗

Overview of Security and Privacy in Cyber-Physical Systems

Cyber-physical systems (CPS) are used across domains to enable process optimization and previously unachievable functionality. The combination of networked digital systems and analog physical processes creates unique characteristics that change how security theory is applied. Neither cyber nor physical security concepts alone can protect CPS because the crossover effects can introduce unexpected vulnerabilities. Physical attacks may allow access to critical assets resulting in damage or compromise of information being processed by the device, while cyber attacks may cause physical malfunctions resulting in real-world consequences. Therefore, security and privacy are key concerns for CPS design, development, and operation. In this chapter, we discuss how CPS security and privacy differ from that of pure cyber or physical systems and what may be done to secure these systems. Our goal is to help designers of emerging CPS to build more secure, privacy-enhanced products in the future.

Cyber-physical systems, security, privacy↗

Differentially Private Distributed Sensing

The growth of the Internet of Things (IoT) creates the possibility of decentralized systems of sensing and actuation, potentially on a global scale. IoT devices connected to cloud networks can offer Sensing and Actuation as a Service (SAaaS) enabling networks of sensors to grow to a global scale. But extremely large sensor networks can violate privacy, especially in the case where IoT devices are mobile and connected directly to the behaviors of people. The thesis of this paper is that by adapting differential privacy (adding statistically appropriate noise to query results) to groups of geographically distributed sensors privacy could be maintained without ever sending all values up to a central curator and without compromising the overall accuracy of the data collected. This paper outlines such a scheme and performs an analysis of differential privacy techniques adapted to edge computing in a simulated sensor network where ground truth is known. The positive and negative outcomes of employing differential privacy in distributed networks of devices are discussed and a brief research agenda is presented.

Differential Privacy↗

Security and Privacy in Cyber-Physical Systems

As you have seen from the previous chapters, cyber-physical systems (CPS) are broadly used across technology and industrial domains. While these systems enable process optimization and efficiency and allow previously impossible functionality, security and privacy are key concerns for their design, development, and operation. CPS have been key components utilized in some of the highest publicized security breaches over the last decade. In this chapter, we will look over the CPS described in the previous chapters from a security perspective. In this chapter, we explain classical information and physical security fundamentals in the context of CPS and contextualize them across application domains. We give examples where the interplay of functionality and diverse communication can introduce unexpected vulnerabilities and produce larger impacts. We will discuss how CPS security and privacy is inherently different from that of pure cyber or physical systems and what may be done to secure these systems, considering their emergent cyber-physical properties. Finally, we will discuss security and privacy implications of merging infrastructural and personal CPS. Our hope is to impart the knowledge of what CPS security and privacy are, why they are important, and explain existing processes and challenges.

Cyber-physical systems↗

Behavior-dependent Routing: Responding to Anomalies with Automated Low-cost Measures

This is a conference paper submission describing research and software implementation of a cybersecurity concept that uses behavior models to trigger changes in routing of network traffic. As user behavior deviates more and more from baseline models, traffic is routed through more elevated layers of analysis and control.

information flow controls↗

Security and Privacy Grand Challenges for the Internet of Things

Abstract— The growth of the Internet of Things (IoT) is driven by market pressures, and while security is being considered, the relationship between the unintended consequences of billions of such devices connecting to the Internet cannot be described with existing mathematical methods. The possibilities for illicit surveillance through lifestyle analysis, unauthorized access to information, and new attack vectors will continue to increase by 2020, when up-to 50 billion devices may be connected. This paper discusses various kinds of vulnerabilities that can be expected to arise, and presents a research agenda for mitigating the worst of the impacts. We hope to draw research attention to the potential dangers of IoT so that many of these problems can be avoided.

grand challenge↗

Quantifying Cyber-Resilience Against Resource-Exhaustion Attacks

Resilience in the information sciences is notoriously difficult to define much less to measure. But in mechanical engi- neering, the resilience of a substance is mathematically defined as the area under the stress vs. strain curve. We took inspiration from mechanics in an attempt to define resilience precisely for information systems. We first examine the meaning of resilience in language and engineering terms and then translate these definitions to information sciences. Then we tested our definitions of resilience for a very simple problem in networked queuing systems. We discuss lessons learned and make recommendations for using this approach in future work.

cyber security↗

Defense on the Move: Ant-Based Cyber Defense

Many common cyber defenses (like firewalls and IDS) are as static as trench warfare allowing the attacker freedom to probe them at will. The concept of Moving Target Defense (MTD) adds dynamism to the defender side, but puts the systems to be defended themselves in motion, potentially at great cost to the defender. An alternative approach is a mobile resilient defense that removes attackers’ ability to rely on prior experience without requiring motion in the protected infrastructure itself. The defensive technology absorbs most of the cost of motion, is resilient to attack, and is unpredictable to attackers. The Ant-Based Cyber Defense (ABCD) is a mobile resilient defense providing a set of roaming, bio-inspired, digital-ant agents working with stationary agents in a hierarchy headed by a human supervisor. The ABCD approach provides a resilient, extensible, and flexible defense that can scale to large, multi-enterprise infrastructures like the smart electric grid.

Cyber Security↗