J. Todd McDonald

Intellectual Property Protection in Additive Layer Manufacturing: Requirements for Secure Outsourcing

Additive Layer Manufacturing (ALM) is a new technology to produce 3D objects adding layer by layer. Agencies and companies like NASA, ESA, and SpaceX are exploring a broad range of application areas of ALM, which includes printing of device components, replacement parts, houses, and even food. They expect that this technology will greatly reduce production costs, manufacturing time, and necessary storage space. The broad variety of application areas and the high grade of computerization of this manufacturing process will inevitably make ALM an attractive target of various attacks. This research examines the problem of Intellectual Property (IP) protection in the case of outsourcing the ALM manufacturing process. We discuss the existing process and introduce a new model for the outsourcing of ALM-based production. For the proposed outsourcing model, focusing on IP protection, we present a risk assessment, specify requirements addressing mitigation of the identified risks, and outline approaches to implement the specified requirements. The fulfillment of the specified requirements will enable secure outsourcing of ALM production.

Software issues in digital forensics

Whether we accept it or not, computer systems and the operating systems that direct them are at the heart of major forms of malicious activity. Criminals can use computers as the actual target of their malicious activity (stealing funds electronically from a bank) or use them to support the conduct of criminal activity in general (using a spreadsheet to track drug shipments). In either case, law enforcement needs the ability (when required) to collect evidence from such platforms in a reliable manner that preserves the fingerprints of criminal activity. Though such discussion touches on privacy issues and rules of legal veracity, we focus purely on technological support in this paper. Specifically, we examine and set forth principles of operating system (OS) design that may significantly increase the success of (future) forensic collection efforts. We lay out several OS design attributes that synergistically enhance forensics activities. Specifically, we pose the use of circuit encryption techniques to provide an additional layer of protection above hardware-enforced approaches. We conclude by providing an overarching framework to incorporate these enhancements within the context of OS design.

Application Security Models for Mobile Agent Systems

Mobile agents are a distributed computing paradigm based on mobile autonomous programs. Mobile applications must balance security requirements with available security mechanisms in order to meet application level security goals. We introduce a trust framework to reason about application security requirements, trust expression, and agent protection mechanisms. We develop application security models that capture initial trust relationships and consider their use for mobile agent security.

Increasing stability and distinguishability of the digital fingerprint in FPGAs through input word analysis

Field Programmable Gate Arrays (FPGAs) have become increasingly popular in circuit development due to their rapid development times and low costs. With their increased use, the need to protect their Intellectual Property (IP) becomes more urgent. The digital fingerprint accomplishes this by creating a unique identification (ID) for each FPGA. In this research, we propose methods to dramatically increase the stability and robustness of the digital fingerprint ID by the proper choice of input sequences. We also show that by properly choosing the input word, we can significantly increase the DF resistance to operating temperature changes.

Deterministic circuit variation for anti-tamper applications

The electric power grid underlying our national infrastructure faces various challenges from adversaries that may exploit weaknesses gained through tampering and malicious reverse engineering. In this paper we describe a method for frustrating such adversaries based on polymorphic generation of circuit hardware with specific hiding properties in mind. We introduce component fusion as a technique for generating functionally equivalent variations of target logic that merge and blur the boundary between constituent components. We show how both random and deterministic variation can be combined to produce circuits that are efficient within allowable bounds while driving up cost of malicious tamper efforts.

Using logic-based reduction for adversarial component recovery

A current means to protect intellectual property embedded in both circuits and software involves creating a functionally equivalent variant with subjective qualities related to difficulty of reverse engineering. In this paper, we consider the problem of protection in a smaller, generalized class of programs based on Boolean logic primitives. We consider Boolean logic reduction as one means to quantify hardness of undoing structural transformations designed to impede reverse engineering. We detail our experiences in using both commercial synthesis tools and organic red-team tools that simplify transformations using known basic logic patterns. Using simple component recovery on candidate circuits, we show how specific variation methods impact adversarial analysis and posit relationships between specific transformations and corresponding difficulty of reversal.

Probing the Limits of Virtualized Software Protection

Virtualization is becoming a prominent field of research not only in distributed systems, but also in software protection and obfuscation. Software virtualization has given rise to advanced techniques that may provide intellectual property protection and anti-cloning resilience. We present results of an empirical study that answers whether integrity of execution can be preserved for process-level virtualization protection schemes in the face of adversarial analysis. Our particular approach considers exploits that target the virtual execution environment itself and how it interacts with the underlying host operating system and hardware. We give initial results that indicate such protection mechanisms may be vulnerable at the level where the virtualized code interacts with the underlying operating system. The resolution of whether such attacks can undermine security will help create better detection and analysis methods for malware that also employ software virtualization. Our findings help frame research for additional mitigation techniques using hardware-based integration or hybrid virtualization techniques that can better defend legitimate uses of virtualized software protection.

A Systems Approach to Cyber Assurance Education

The demand for cybersecurity professions faces continual shortages. Real-world cyber threats continue to drive this demand as we face a daily barrage of attacks on our critical infrastructure, national, and private industry assets. To meet this demand, many cybersecurity and information assurance educational programs have emerged. These programs range from specialized tracks within traditional academic programs to specialized degree titles developed solely for the purpose of producing cyber capable graduates. In this paper we document curriculum development that focuses on a systems level approach to cyber assurance education. This program incorporates both hardware and software aspects to ensure cyber security graduates are produced that can address adversaries that target complete system implementations.

Exploring security in ZigBee networks

ZigBee networks have become popular for their low cost, low power, and ease of implementation. The ZigBee protocol has particularly become prevalent for home automation and controlling devices such as door locks and garage door openers. Preventing attacks and reducing vulnerabilities is imperative in cases where there can be high financial losses due to poor security implementations. For systems where low power and cost are desirable, but security is a priority, the application developer must be extremely cautious in the design of their network. This paper surveys security issues and vulnerabilities in the ZigBee specification and current key management schemes proposed for these networks.

Forewarning of epileptic events from scalp EEG

This paper addresses epileptic event forewarning. One novel contribution is the use of graph theoretic measures to detect condition change from time-delay-embedding states. Another novel contribution is better forewarning of the epileptic events from two channels of scalp EEG, with a total true rate of 58/60 (sensitivity = 39/40, specificity = 19/20). Challenges include statistical validation in terms of true positives and true negatives; actionable forewarning in terms of time before the event; detection of the event to reset the forewarning algorithm; and implementation in a practical device.