Automating Mobile Device File Format Analysis

Forensic tools assist examiners in extracting evidence from application files from mobile devices. If the file format for the file of interest is known, this process is straightforward, otherwise it requires the examiner to manually reverse engineer the data structures resident in the file. This research presents the Automated Data Structure Slayer (ADSS), which automates the process to reverse engineer unknown file for- mats of Android applications. After statically parsing and preparing an application, ADSS dynamically runs it, injecting hooks at selected methods to uncover the data structures used to store and process data before writing to media. The resultant association between application semantics and bytes in a file reveal the structure and file format. ADSS has been successfully evaluated against Uber and Discord, both popular Android applications, and reveals the format used by the respective proprietary application files stored on the filesystem

The Addict in Us all.

In this paper, we contend that the psychology of addiction is similar to the psychology of ordinary, non-addictive temptation in important respects, and explore the ways in which these parallels can illuminate both addiction and ordinary action. The incentive salience account of addiction proposed by Robinson and Berridge (1-3) entails that addictive desires are not in their nature different from many of the desires had by non-addicts; what is different is rather the way that addictive desires are acquired, which in turn affects their strength. We examine these "incentive salience" desires, both in addicts and non-addicts, contrasting them with more cognitive desires. On this account, the self-control challenge faced by addicted agents is not different in kind from that faced by non-addicted agents - though the two may, of course, differ greatly in degree of difficulty. We explore a general model of self-control for both the addict and the non-addict, stressing that self-control may be employed at three different stages, and examining the ways in which it might be strengthened. This helps elucidate a general model of intentional action.This is the final published version. It first appeared at http://journal.frontiersin.org/Journal/10.3389/fpsyt.2014.00139/abstract

Secondary Structures in Long Compact Polymers

Compact polymers are self-avoiding random walks which visit every site on a lattice. This polymer model is used widely for studying statistical problems inspired by protein folding. One difficulty with using compact polymers to perform numerical calculations is generating a sufficiently large number of randomly sampled configurations. We present a Monte-Carlo algorithm which uniformly samples compact polymer configurations in an efficient manner allowing investigations of chains much longer than previously studied. Chain configurations generated by the algorithm are used to compute statistics of secondary structures in compact polymers. We determine the fraction of monomers participating in secondary structures, and show that it is self averaging in the long chain limit and strictly less than one. Comparison with results for lattice models of open polymer chains shows that compact chains are significantly more likely to form secondary structure.Comment: 14 pages, 14 figure

Security Analysis of the Masimo MightySat: Data Leakage to a Nosy Neighbor

Embedded technology known as the Internet of Things (IoT) has been integrated into everyday life, from the home, to the farm, industry, enterprise, the battlefield, and even for medical devices. With the increased use of networked devices comes an increased attack surface for malicious actors to gather and inject data, putting the privacy of users at risk. This research considers the Masimo MightySat fingertip pulse oximeter and the companion Masimo Professional Health app from a security standpoint, analyzing the Bluetooth Low Energy (BLE) communication from the device to the application and the data leakage between the two. It is found that with some analysis of a personally owned Masimo MightySat Rx through the use of an Ubertooth BLE traffic sniffer, static analysis of the HCI\_snoop.log and application data, and dynamic analysis of the app, data could be reasonably captured for another MightySat and interpret it to learn user health data

Application of CFD Analysis to Design Support and Problem Resolution for ASRM and RSRM

The use of Navier-Stokes CFD codes to predict the internal flow field environment in a solid rocket motor is a very important analysis element during the design phase of a motor development program. These computational flow field solutions uncover a variety of potential problems associated with motor performance as well as suggesting solutions to these problems. CFD codes have also proven to be of great benefit in explaining problems associated with operational motors such as in the case of the pressure spike problem with the STS-54B flight motor. This paper presents results from analyses involving both motor design support and problem resolution. The issues discussed include the fluid dynamic/mechanical stress coupling at field joints relative to significant propellant deformations, the prediction of axial and radial pressure gradients in the motor associated with motor performance and propellant mechanical loading, the prediction of transition of the internal flow in the motor associated with erosive burning, the accumulation of slag at the field joints and in the submerged nozzle region, impingement of flow on the nozzle nose, and pressure gradients in the nozzle region of the motor. The analyses presented in this paper have been performed using a two-dimensional axisymmetric model. Fluent/BFC, a three dimensional Navier-Stokes flow field code, has been used to make the numerical calculations. This code utilizes a staggered grid formulation along with the SIMPLER numerical pressure-velocity coupling algorithm. Wall functions are used to represent the character of the viscous sub-layer flow, and an adjusted k-epsilon turbulence model especially configured for mass injection internal flows, is used to model the growth of turbulence in the motor port. Conclusions discussed in this paper consider flow field effects on the forward, center, and aft propellant grains except for the head end star grain region of the forward propellant segment. The field joints and the submerged nozzle are discussed as well. Conclusions relative to both the design evaluation of the ASRM and the RSRM scenarios explaining the pressure spikes were based on the flow field solutions presented in this paper

A Coupled CFD/FEM Structural Analysis to Determine Deformed Shapes of the RSRM Inhibitors

Recent trends towards an increase in the stiffness of the acrylonitrile butadiene rubber (NBR) insulation material used in the construction of the redesigned solid rocket motor (RSRM) propellant inhibitors prompted questions about possible effects on RSRM performance. The specific objectives of the computational fluid dynamics (CFD) task included: (1) the definition of pressure loads to calculate the deformed shape of stiffer inhibitors, (2) the calculation of higher port velocities over the inhibitors to determine shifts in the vortex shedding or edge tone frequencies, and (3) the quantification of higher slag impingement and collection rates on the inhibitors and in the submerged nose nozzle cavity

ADS-B Classification using Multivariate Long Short-term Memory–fully Convolutional Networks and Data Reduction Techniques

Researchers typically increase training data to improve neural net predictive capabilities, but this method is infeasible when data or compute resources are limited. This paper extends previous research that used long short-term memory–fully convolutional networks to identify aircraft engine types from publicly available automatic dependent surveillance-broadcast (ADS-B) data. This research designs two experiments that vary the amount of training data samples and input features to determine the impact on the predictive power of the ADS-B classification model. The first experiment varies the number of training data observations from a limited feature set and results in 83.9% accuracy (within 10% of previous efforts with only 25% of the data). The findings show that feature selection and data quality lead to higher classification accuracy than data quantity. The second experiment accepted all ADS-B feature combinations and determined that airspeed, barometric pressure, and vertical speed had the most impact on aircraft engine type prediction

The Space System for the High Energy Transient Experiment

The High Energy Transient Experiment (HETE) is an astrophysics project funded by NASA and led by the Center for Space Research (CSR) at the Massachusetts Institute of Technology (MIT). It has for principal goal the detection and precise localization of the still mysterious sources of gamma ray bursts. The project is original in many respects. HETE will provide simultaneous observations of bursts in the gamma, X-ray and UV ranges from the same small (250 Ibms) space platform. A network of ground stations around the world will diffuse in real time key information derived from HETE observations to many ground observatories, allowing quick follow-on observations with ground instruments. The whole project is entirely managed by MIT, under top level NASA supervision, and satellite and ground stations will be remotely operated from CSA. The HETE system development is conducted with a small budget and under a short schedule

SRM Internal Flow Test and Computational Fluid Dynamic Analysis

During the four year period of performance for NASA contract, NASB-39095, ERC has performed a wide variety of tasks to support the design and continued development of new and existing solid rocket motors and the resolution of operational problems associated with existing solid rocket motor's at NASA MSFC. This report summarizes the support provided to NASA MSFC during the contractual period of performance. The report is divided into three main sections. The first section presents summaries for the major tasks performed. These tasks are grouped into three major categories: full scale motor analysis, subscale motor analysis and cold flow analysis. The second section includes summaries describing the computational fluid dynamics (CFD) tasks performed. The third section, the appendices of the report, presents detailed descriptions of the analysis efforts as well as published papers, memoranda and final reports associated with specific tasks. These appendices are referenced in the summaries. The subsection numbers for the three sections correspond to the same topics for direct cross referencing

Traffic Collision Avoidance System: False Injection Viability

Safety is a simple concept but an abstract task, specifically with aircraft. One critical safety system, the Traffic Collision Avoidance System II (TCAS), protects against mid-air collisions by predicting the course of other aircraft, determining the possibility of collision, and issuing a resolution advisory for avoidance. Previous research to identify vulnerabilities associated with TCAS’s communication processes discovered that a false injection attack presents the most comprehensive risk to veritable trust in TCAS, allowing for a mid-air collision. This research explores the viability of successfully executing a false injection attack against a target aircraft, triggering a resolution advisory. Monetary constraints precluded access to a physical TCAS unit; instead, this research creates a novel program, TCAS-False Injection Environment (TCAS-FIE), that incorporates real-world distributed computing systems to simulate a ground-based attacker scenario which explores how a false injection attack could target an operational aircraft. TCAS-FIEs’ simulation models are defined by parameters to execute tests that mimic real-world TCAS units during Mode S message processing. TCAS-FIE simulations execute tests over applicable ranges (5–30 miles), altitudes (25–45K ft), and bearings standard for real-world TCAS tracking. The comprehensive tests compare altitude, measure range closure rate, and measure signal strength from another aircraft to determine the delta in bearings over time. In the attack scenario, the ground-based adversary falsely injects a spoofed aircraft with characteristics matching a Boeing 737-800 aircraft, targeting an operational Boeing 737-800 aircraft. TCAS-FIE completes 555,000 simulations using the various ranges, altitudes, and bearings. The simulated success rate to trigger a resolution advisory is 32.63%, representing 181,099 successful resolution advisory triggers out of 555,000 total simulations. The results from additional analysis determine the required ranges, altitudes, and bearing parameters to trigger future resolution advisories, yielding a predictive threat map for aircraft false injection attacks. The resulting map provides situational awareness to pilots in the event of a real-world TCAS anomaly