SEARCH · Search NASA
Results for “moving target”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Imaging systems and related methods including radar imaging with moving arrays or moving targets
Imaging systems, including radio frequency, microwave and millimeter-wave arrangements, and related methods are described. According to one aspect, an imaging system includes an antenna array, a position capture system configured to generate position information indicative of locations of one of the antenna array and the target at the first and second moments in time, and wherein the one of the antenna array and the target move between the first and second moments in time, a transceiver configured to control the antenna array to emit electromagnetic energy towards the target and to generate an output that is indicative of the received electromagnetic energy, a data acquisition system configured to generate radar data, processing circuitry configured to process the position information and the radar data to generate image data regarding the target, and an interface configured to use the image data to generate visual images regarding the target.
Imaging systems and related methods including radar imaging with moving arrays or moving targets
Imaging systems, including radio frequency, microwave and millimeter-wave arrangements, and related methods are described. According to one aspect, an imaging system includes an antenna array, a position capture system configured to generate position information indicative of locations of one of the antenna array and the target at the first and second moments in time, and wherein the one of the antenna array and the target move between the first and second moments in time, a transceiver configured to control the antenna array to emit electromagnetic energy towards the target and to generate an output that is indicative of the received electromagnetic energy, a data acquisition system configured to generate radar data, processing circuitry configured to process the position information and the radar data to generate image data regarding the target, and an interface configured to use the image data to generate visual images regarding the target.
An Exploration of Moving Target Efficacy and Application
Moving target defense (MTD) is an emerging paradigm in which system defenses dynamically mutate in order to decrease the overall system attack surface. Though the initial concept is promising, implementations have not been widely adopted. The field has been actively researched for over ten years, and has only produced a small amount of extensively adopted defenses, most notably, address space layout randomization (ASLR). This is despite the fact that there currently exist a variety of moving target implementations and proofs-of-concept. We suspect that this results from the moving target controls breaking critical system dependencies from the perspectives of users and administrators, as well as making things more difficult for attackers. As a result, the impact of the controls on overall system security is not sufficient to overcome the inconvenience imposed on legitimate system users. In this paper, we analyze a successful MTD approach. We study the control's dependency graphs, showing how we use graph theoretic and network properties to predict the effectiveness of the selected control. Then, with this framework in place, the dynamic nature of some Moving Target Defenses opens the possibility of modeling them with dynamic systems approaches, such as state space representations familiar from control and systems theory. We then use this approach to develop state space models for Moving Target Defenses, provide an analysis of their properties, and suggest approaches for using them.
SU-G-JeP4-05: Effects of Irregular Respiratory Motion On the Positioning Accuracy of Moving Target with Free Breathing Cone-Beam Computerized Tomography
Purpose: Average or maximum intensity projection (AIP or MIP) images derived from 4DCT images are often used as a reference image for target alignment when free breathing Cone-beam CT (FBCBCT) is used for positioning a moving target at treatment. This method can be highly accurate if the patient has stable respiratory motion. However, a patient’s breathing pattern often varies irregularly. The purpose of this study is to investigate the effect of irregular respiration on the positioning accuracy of a moving target with FBCBCT. Methods: Eight patients’ respiratory motion curves were selected to drive a Quasar phantom with embedded cubic and spherical targets. A 4DCT of the moving phantom was acquired on a CT scanner (Philips Brilliance 16) equipped with a Varian RPM system. The phase binned 4DCT images and the corresponding MIP and AIP images were transferred into Eclipse for analysis. CBCTs of the phantom driven by the same breathing curves were acquired on a Varian TrueBeam and fused such that the zero positions of moving targets are the same on both CBCT and AIP images. The sphere and cube volumes and centrioid differences (alignment error) determined by MIP, AIP and FBCBCT images were compared. Results: Compared to the volume determined by FBCBCT, the volumes of cube and sphere in MIP images were 22.4%±8.8% and 34.2%±6.2% larger while the volumes in AIP images were 7.1%±6.2% and 2.7%±15.3% larger, respectively. The alignment errors for the cube and sphere with center-center matches between MIP and FBCBCT were 3.5±3.1mm and 3.2±2.3mm, and the alignment errors between AIP and FBCBCT were 2.1±2.6mm and 2.1±1.7mm, respectively. Conclusion: AIP images appear to be superior reference images than MIP images. However, irregular respiratory motions could compromise the positioning accuracy of a moving target if the target center-center match is used to align FBCBCT and AIP images.
Analysis of Network Address Shuffling as a Moving Target Defense
Address shuffling is a type of moving target defense that prevents an attacker from reliably contacting a system by periodically remapping network addresses. Although limited testing has demonstrated it to be effective, little research has been conducted to examine the theoretical limits of address shuffling. As a result, it is difficult to understand how effective shuffling is and under what circumstances it is a viable moving target defense. This paper introduces probabilistic models that can provide insight into the performance of address shuffling. These models quantify the probability of attacker success in terms of network size, quantity of addresses scanned, quantity of vulnerable systems, and the frequency of shuffling. Theoretical analysis will show that shuffling is an acceptable defense if there is a small population of vulnerable systems within a large network address space, however shuffling has a cost for legitimate users. These results will also be shown empirically using simulation and actual traffic traces.
Voltage Stability Constrained Moving Target Defense Against Net Load Redistribution Attacks
Moving target defense (MTD) using distributed flexible AC transmission system (D-FACTS) devices is a promising defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation. However, all existing studies myopically perturb the reactance of D-FACTS lines without considering the system voltage stability. In this paper, we first illustrate voltage instability induced by MTDs in a three-bus system. To address this issue, we further propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow and voltage stability indices. We mathematically derive the sensitivity matrix of voltage stability index to line impedance, on which an optimization problem for maximizing voltage stability index is formulated. This framework is tested on the IEEE 14-bus and the IEEE 118-bus transmission systems, in which net load redistribution attacks are launched by sophisticated attackers. Here, the simulation results show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. We conduct case studies with and without the proposed framework under different MTD planning and operational methods. The impacts of the proposed two methods on attack detection effectiveness and system economic metrics are also revealed.
Optimal D-FACTS Placement in Moving Target Defense Against False Data Injection Attacks
Moving target defense (MTD) is a defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation using distributed flexible AC transmission system (D-FACTS) devices. However, existing studies neglect to address a fundamental yet critical issue, i.e., the D-FACTS placement, by assuming that all lines are equipped with D-FACTS devices. Here, to tackle this problem, we first derive analytical necessary conditions and requirements on the D-FACTS placement for a complete MTD. Further, we propose sufficient conditions using a graph theory-based topology analysis to ensure that the MTD under the proposed D-FACTS placement has the maximum rank of its composite matrix, which is indicative of the MTD effectiveness. Based on the analytical conditions, we design D-FACTS placement algorithms by using the minimum number of D-FACTS devices to achieve the maximum MTD effectiveness. A novel MTD-based ACOPF model, in which the reactance of D-FACTS lines is introduced as decision variables, is proposed to find a trade-off between the system loss and the MTD effectiveness. Numerical results on 6-bus, IEEE 14-bus, and IEEE 118-bus systems show the efficacy of MTDs using the proposed D-FACTS placement algorithms in maximizing the composite matrix rank and detecting FDI attacks.
A Moving Target Environment for Computer Configurations Using Genetic Algorithms
Moving Target (MT) environments for computer systems provide security through diversity by changing various system properties that are explicitly defined in the computer configuration. Temporal diversity can be achieved by making periodic configuration changes; however in an infrastructure of multiple similarly purposed computers diversity must also be spatial, ensuring multiple computers do not simultaneously share the same configuration and potential vulnerabilities. Given the number of possible changes and their potential interdependencies discovering computer configurations that are secure, functional, and diverse is challenging. This paper describes how a Genetic Algorithm (GA) can be employed to find temporally and spatially diverse secure computer configurations. In the proposed approach a computer configuration is modeled as a chromosome, where an individual configuration setting is a trait or allele. The GA operates by combining multiple chromosomes (configurations) which are tested for feasibility and ranked based on performance which will be measured as resistance to attack. The result of successive iterations of the GA are secure configurations that are diverse due to the crossover and mutation processes. Simulations results will demonstrate this approach can provide at MT environment for a large infrastructure of similarly purposed computers by discovering temporally and spatially diverse secure configurations.
Bio-Inspired Approaches to Moving-Target Defense Strategies (Final Report)
This report records the work and contributions of the NITRD-funded Bio-Inspired Approaches to Moving-Target Defense Strategies project performed by Pacific Northwest National Laboratory under the technical guidance of the National Security Agency’s R6 division. The project has incorporated a number of bio-inspired cyber defensive technologies within an elastic framework provided by the Digital Ants. This project has created the first scalable, real-world prototype of the Digital Ants Framework (DAF) and integrated five technologies into this flexible, decentralized framework: (1) Ant-Based Cyber Defense (ABCD), (2) Behavioral Indicators, (3) Bioinformatic Classification, (4) Moving-Target Reconfiguration, and (5) Ambient Collaboration. The DAF can be used operationally to decentralize many such data intensive applications that normally rely on collection of large amounts of data in a central repository. In this work, we have shown how these component applications may be decentralized and may perform analysis at the edge. Operationally, this will enable analytics to scale far beyond current limitations while not suffering from the bandwidth or computational limitations of centralized analysis. This effort has advanced the R6 Cyber Security research program to secure digital infrastructures by developing a dynamic means to adaptively defend complex cyber systems. We hope that this work will benefit both our client’s efforts in system behavior modeling and cyber security to the overall benefit of the nation.
Evolutionary Drift Models for Moving Target Defense
One of the biggest challenges faced by cyber defenders is that attacks evolve more rapidly than our ability to recognize them. We propose a moving target defense concept in which the means of detection is set in motion. This is done by moving away from static signature-based detection and instead adopting biological modeling techniques that describe families of related sequences. We present here one example for how to apply evolutionary models to cyber sequences, and demonstrate the feasibility of this technique on analysis of a complex, evolving software project. Specifically, we applied sequence-based and profile-based evolutionary models and report the ability of these models to recognize highly volatile code regions. We found that different drift models reliably identify different types of evolutionarily related code regions. The impact is that these (and possibly other) evolutionary models could be used in a moving target defense in which the "signature" being used to detect sequence-based behaviors is not a fixed signature but one that can recognize new variants of a known family based on multiple evolutionary models.
Moving target defense for a serial communications system
A moving target defense scheme for a serial communications system is disclosed herein. A bus controller generates and broadcasts a nonce to remote terminals over a bus. The bus controller and the remote terminals generate a randomized sequence based upon the nonce and a shared secret that is shared between the bus controller and the remote terminals. The bus controller broadcasts first messages over the bus on first addresses that are derived from first portions of the randomized sequence. The remote terminals listen for the first messages that are broadcast over the bus on the first addresses. The bus controller broadcasts a shift message that causes the remote terminals to listen for second messages that are broadcast over the bus on second addresses that are derived from second portions of the randomized sequence.
Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration
This paper introduces Moving Target Defense (MTD) in distribution system against False Data Injection (FDI) attacks on the supervisory control and data acquisition (SCADA) system. Based on the AC power flow model, a hidden MTD (HMTD) strategy is constructed in combination with network reconfiguration by minimizing the system loss and line power flow differences before and after the HMTD. The proposed HMTD-based network reconfiguration is formulated as a mixed-integer nonlinear programming (MINLP) problem. A refined Genetic Algorithm (GA) is proposed to solve it. Numerical test is conducted in a modified IEEE-66 bus system. The simulation results show that the proposed model reduces the power loss introduced by the HMTD as well as yields a stealthy MTD to the attackers. The impact of HMTD on the system performance is also compared with that of the existing MTD strategies.
A method of dose reconstruction for moving targets compatible with dynamic treatments
Purpose: To develop a method that allows a commercial treatment planning system (TPS) to perform accurate dose reconstruction for rigidly moving targets and to validate the method in phantom measurements for a range of treatments including intensity modulated radiation therapy (IMRT), volumetric arc therapy (VMAT), and dynamic multileaf collimator (DMLC) tracking. Methods: An in-house computer program was developed to manipulate Dicom treatment plans exported from a TPS (Eclipse, Varian Medical Systems) such that target motion during treatment delivery was incorporated into the plans. For each treatment, a motion including plan was generated by dividing the intratreatment target motion into 1 mm position bins and construct sub-beams that represented the parts of the treatment that were delivered, while the target was located within each position bin. For each sub-beam, the target shift was modeled by a corresponding isocenter shift. The motion incorporating Dicom plans were reimported into the TPS, where dose calculation resulted in motion including target dose distributions. For experimental validation of the dose reconstruction a thorax phantom with a moveable lung equivalent rod with a tumor insert of solid water was first CT scanned. The tumor insert was delineated as a gross tumor volume (GTV), and a planning target volume (PTV) was formed by adding margins. A conformal plan, two IMRT plans (step-and-shoot and sliding windows), and a VMAT plan were generated giving minimum target doses of 95% (GTV) and 67% (PTV) of the prescription dose (3 Gy). Two conformal fields with MLC leaves perpendicular and parallel to the tumor motion, respectively, were generated for DMLC tracking. All treatment plans were delivered to the thorax phantom without tumor motion and with a sinusoidal tumor motion. The two conformal fields were delivered with and without portal image guided DMLC tracking based on an embedded gold marker. The target dose distribution was measured with a radiochromic film in the moving rod and compared with the reconstructed doses using gamma tests. Results: Considerable interplay effects between machine motion and target motion were observed for the treatments without tracking. For nontracking experiments, the mean 2 mm/2% gamma pass rate over all investigated scenarios was 99.6% between calculated and measured doses. For tracking experiments, the mean gamma pass rate was 99.4%. Conclusions: A method for accurate dose reconstruction for moving targets with dynamic treatments was developed and experimentally validated in a variety of delivery scenarios. The method is suitable for integration into TPSs, e.g., for reconstruction of the dose delivered to moving tumors or calculation of target doses delivered with DMLC tracking.
Stream splitting moving target defense
Systems and methods for utilizing stream splitting Moving Target Defense (MTD) to provide enhanced computer system communication system security by splitting a data stream in to a plurality of paths is described. In some implementations, Stream splitting MTD, involves splitting a single data stream (e.g., TCP stream) into a plurality of discrete units, then sending and receiving those discrete units from and to different (ideally geographically disparate) receiving servers, with the stream being reassembled on the receiving end. The plurality of discrete units of data include resequencing data. The size of each discrete unit may vary depending on the specific implementation, even down to small unit sizes (e.g., a single packet).
Load Margin Constrained Moving Target Defense against False Data Injection Attacks
Cyber physical security of power systems with high penetration of renewable generation has attracted attention from researchers. One critical issue is that cyber-physical attacks, disguised as uncertain renewable generation, can target conventional power system state estimation (SE). Moving target defense (MTD) is a promising defense strategy to detect stealthy false data injection (FDI) attacks against SE. However, all existing studies myopically perturb the reactance of transmission lines equipped with distributed flexible AC transmission system (D-FACTS) devices without adequately considering the system voltage stability. Exacerbated by the renewable generation uncertainty, existing MTD may cause voltage instability when the power grid is under stress. To address this issue, we propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow. We utilize the sensitivity matrix of power injection to line impedance, on which an optimization problem for maximizing load margin is formulated. This framework is validated on the IEEE 14-bus system and the IEEE 118-bus system, in which net load redistribution attacks are launched by sophisticated attackers. Steady-state simulations and dynamic simulations on PSS/E show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. The impact of the proposed method on attack detection effectiveness is also revealed.
Evaluating Moving Target Defense with PLADD
This project evaluates the effectiveness of moving target defense (MTD) techniques using a new game we have designed, called PLADD, inspired by the game FlipIt. PLADD extends FlipIt by incorporating what we believe are key MTD concepts. We have analyzed PLADD and proven the existence of a defender strategy that pushes a rational attacker out of the game, demonstrated how limited the strategies available to an attacker are in PLADD, and derived analytic expressions for the expected utility of the game’s players in multiple game variants. We have created an algorithm for finding a defender’s optimal PLADD strategy. We show that in the special case of achieving deterrence in PLADD, MTD is not always cost effective and that its optimal deployment may shift abruptly from not using MTD at all to using it as aggressively as possible. We believe our effort provides basic, fundamental insights into the use of MTD, but conclude that a truly practical analysis requires model selection and calibration based on real scenarios and empirical data. We propose several avenues for further inquiry, including (1) agents with adaptive capabilities more reflective of real world adversaries, (2) the presence of multiple, heterogeneous adversaries, (3) computational game theory-based approaches such as coevolution to allow scaling to the real world beyond the limitations of analytical analysis and classical game theory, (4) mapping the game to real-world scenarios, (5) taking player risk into account when designing a strategy (in addition to expected payoff), (6) improving our understanding of the dynamic nature of MTD-inspired games by using a martingale representation, defensive forecasting, and techniques from signal processing, and (7) using adversarial games to develop inherently resilient cyber systems.