Synthesis of Obfuscation Policies to Ensure Privacy and Utility

We consider the problem of privacy enforcement for dynamic systems using the technique of obfuscation. Our approach captures the trade-off between privacy and utility, in a formal reactive framework. Specifically, we model a dynamic system as an automaton or labeled transition system with predefined secret behaviors. The system generates event strings for some useful computation (utility). At the same time, it must hide its secret behaviors from any outside observer of its behavior (privacy). We formally capture both privacy and utility specifications within the model of the system. We propose as obfuscation mechanism for privacy enforcement the use of edit functions that suitably alter the output behavior of the system by inserting, deleting, or replacing events in its output strings. The edit function must hide secret behaviors by making them observationally equivalent to non-secret behaviors, while at the same time satisfying the utility requirement on the output strings. We develop algorithmic procedures that synthesize a correct-by-construction edit function satisfying both privacy and utility specifications. The synthesis procedure is based on the solution of a game where the edit function must react to the system moves by suitable output editing. After presenting an explicit algorithm for solving for the winning strategies of the game, we present two complementary symbolic implementations to address scalability of our methodology. The first symbolic implementation uses a direct encoding of the explicit algorithm using binary decision diagrams (BDDs). The second symbolic implementation reframes the synthesis of edit functions as a supervisory control problem and then applies a recently-developed tool for solving supervisory control problems using BDDs. Experimental results comparing the two symbolic implementations are provided.     

Spatially oversampled TDC with digital resolution enhancement

A digital resolution enhancement technique for time-to-digital converters (TDC) is proposed. This involves a simultaneous multi-channel measurement of a time interval with low complexity TDC of varying low resolutions. The coarse outputs of each converter are digitally post-processed to obtain an output whose precision is much better than that of the individual converters. Three post-processing algorithms are proposed and their limitations in presence of converter non-idealities are analyzed. A prototype system with 8 channels is implemented in 90 nm CMOS. 40MS/s output of each channel is algorithmically combined to obtain over 2.2–3X measured improvement in the resolution in 4/6/8 channel modes, validating the system principle. The chip occupies 0.3 mm² and draws up to a maximum of 4 mA from a 1.2 V supply.     

Beneficiation Studies on Recovery of Secondary Sources of Iron from Ferrigenous Alluvial Sands

Beneficiation studies were carried out on iron bearing alluvial sand to recover iron values for pelletisation. The studies include detailed mineralogical characterization, physical and chemical characteristics, beneficiation studies including grinding, magnetic and high tension separation. The results of these investigations indicate that the samples contain 50.2% Fe and 8.2% SiO₂ on average. The mineralogical studies reveal that the sand contains dominantly heavy minerals with small amount of quartz. The heavy minerals are magnetite and ilmenite with small quantities of amphibole and pyroxene group minerals. Detailed beneficiation studies carried out by various techniques indicated that the iron content can be upgraded by simple low intensity wet magnetic separation after grinding the sample to below 210 microns. A product with 62.7% Fe can be obtained at 65.5% yield. The product obtained can be used for pelletisation by blending with suitable high grade iron concentrate.     

Effect of indirubin‐3‐monoxime against lung cancer as evaluated by histological and transmission electron microscopic studies

The aim of this study is to evaluate the antitumor effect of indirubin‐3‐monoxime and its mode of action in benzo(α)pyrene [B(α)P] induced lung cancer in A/J mice. Light microscopic examination of lung sections of [B(α)P] induced lung cancer mice revealed the presence of adenocarcinoma characterized by extensive proliferation of alveolar epithelium and loss of alveolar spaces. The control lung tissue showed a normal architecture with clear alveolar spaces. Interestingly the indirubin‐3‐monoxime treated groups showed the reduced adenocarcinoma with appearance of alveolar spaces. Transmission Electron Microscopic (TEM) studies of lung sections of [B(α)P] induced lung cancer mice showed the presence of phaemorphic cells with dense granules and increased mitochondria. The lung sections of mice treated with indirubin‐3‐monoxime showed the presence of shrunken, fragmented, and condensed nuclei implying apoptosis. The effects were dose dependent and prominent in 10 mg/kg/5 d/week groups suggesting the therapeutic role of indirubin analogue against this deadly human malignancy. Here, our results indicate that indirubin‐3‐monoxime brings antitumor effect against [B(α)P] induced lung cancer by its apoptotic action in A/J mice. Microsc. Res. Tech. 73:1053–1058, 2010. © 2010 Wiley‐Liss, Inc.     

Implementation of hybrid ANN–PSO algorithm on FPGA for harmonic estimation

Harmonic estimation is the main process in active filters for harmonic reduction. A hybrid Adaptive Neural Network–Particle Swarm Optimization (ANN–PSO) algorithm is being proposed for harmonic isolation. Originally Fourier Transformation is used to analyze a distorted wave. In order to improve the convergence rate and processing speed an Adaptive Neural Network Algorithm called Adaline has then been used. A further improvement has been provided to reduce the error and increase the fineness of harmonic isolation by combining PSO algorithm with Adaline algorithm. The inertia weight factor of PSO is combined along with the weight factor of Adaline and trained in Neural Network environment for better results. ANN–PSO provides uniform convergence with the convergence rate comparable that of Adaline algorithm. The proposed ANN–PSO algorithm is implemented on an FPGA. To validate the performance of ANN–PSO; results are compared with Adaline algorithm and presented herein.     

A Study on the Effectiveness of SNMP OID Compression

Simple Network Management Protocol (SNMP) is a popular management protocol. It uses fully distinguished ID for every object sent or received in a message contributing to redundancy. Compression algorithms are proposed to eliminate such redundancies. This paper presents an analysis to understand the effectiveness of such compression algorithms. This analysis provides some interesting results and requirements for OID compression algorithms in general. This paper also presents an algorithm that makes use of the results of this analysis.     

Safe Autonomy Under Perception Uncertainty Using Chance-Constrained Temporal Logic

Autonomous vehicles have found wide-ranging adoption in aerospace, terrestrial as well as marine use. These systems often operate in uncertain environments and in the presence of noisy sensors, and use machine learning and statistical sensor fusion algorithms to form an internal model of the world that is inherently probabilistic. Autonomous vehicles need to operate using this uncertain world-model, and hence, their correctness cannot be deterministically specified. Even once probabilistic correctness is specified, proving that an autonomous vehicle will operate correctly is a challenging problem. In this paper, we address these challenges by proposing a correct-by-synthesis approach to autonomous vehicle control. We propose a probabilistic extension of temporal logic, named Chance Constrained Temporal Logic (C2TL), that can be used to specify correctness requirements in presence of uncertainty. C2TL extends temporal logic by including chance constraints as predicates in the formula which allows modeling of perception uncertainty while retaining its ease of reasoning. We present a novel automated synthesis technique that compiles C2TL specification into mixed integer constraints, and uses second-order (quadratic) cone programming to synthesize optimal control of autonomous vehicles subject to the C2TL specification. We also present a risk distribution approach that enables synthesis of plans with lower cost without increasing the overall risk. We demonstrate the effectiveness of the proposed approach on a diverse set of illustrative examples.