A. Neidhardt

Telcordia Technologies, Middlesex, New Jersey, United States

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Publications (4)0.97 Total impact

  • [show abstract] [hide abstract]
    ABSTRACT: Consider a sensor-field deployed to detect intrusions into a security zone, with each sensor monitoring more than one site. We develop an efficient inference algorithm for determining, from the sensor readings, the most probable set of locations where intrusions have occurred. With N potential points of intrusion, there are 2 * *N subsets of points where intrusions could occur, and searching by direct enumeration is not a scalable method. We present an adaptive distributed algorithm that drastically reduces the computational effort by several orders of magnitude by partitioning the problem into virtual `computational domains', where the domains are adapted to the actual sensor readings. The algorithm either finds a provably optimal global solution, or provides a bound on the deviation of the solution from optimality. Its effectiveness is demonstrated on two examples that model several hundred locations being monitored for intrusion, with the possibility of multiple simultaneous breaches. In effect, our distributed approach makes it feasible to solve much larger intrusion-detection problems than can be solved by a centralized algorithm.
    01/2010;
  • Hanan Luss, Arnold L. Neidhardt, K. R. Krishnan
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    ABSTRACT: Businesses often rely on customers that access an automated resource to receive information, service or products. We present an adaptive method for automated authentication with performance guarantee of probabilistic error bounds, referred to as identity verification. A database includes a record of identifiers for each identity. The identifiers are partitioned into groups, where identifiers in the same group are correlated while identifiers in different groups are independent. A claimant requesting access into the system is probed with a sequence of identifiers. The response to an identifier can be a match, no-match, or ambiguous. Each identifier is characterized by prior response probabilities for a legitimate claimant and for an impostor. Impostor’s response probabilities are updated during a session. The method guarantees that the probabilities of accepting an impostor or rejecting a legitimate claimant do not exceed specified parameters. Once a given number of identifiers have been probed and the claimant has been neither accepted nor rejected, the session terminates with an inconclusive decision and the claimant is referred to further manual interrogation. The method computes various performance characteristics such as the probability that a session of a legitimate claimant terminates inconclusively. These characteristics are valuable in the design of an effective record of identifiers for each of the claimants.
    Electronic Commerce Research 01/2009; 9:225-242. · 0.97 Impact Factor
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    ABSTRACT: The benefits of Global Positioning System (GPS) are recognized in numerous military as well as civilian applications. In many situations, however, GPS signals are simply not available or, at best, intermittently observable. This paper describes a novel location tracking system, called self-correcting adaptive tracking system (SATS), which focuses on solving group location problem when GPS is not available. In our location tracking system, we use a tracking mechanism that allows locating group members based on their pair wise distance information. A key innovation of SATS is that we use an adaptive search algorithm to find the new position estimate based on constraints given by the ranged data. In addition, our location tracking system is capable of extracting directional information normally unavailable in ranging system, which allows us to adaptively stabilize the orientation of the group. The SATS methodology has been prototyped and tested as part of an Office of Navy Research (ONR) program.
    Military Communications Conference, 2008. MILCOM 2008. IEEE; 12/2008
  • A. Neidhardt, H. Luss, K.R. Krishnan
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    ABSTRACT: Modern technology can equip small devices (like mobile phones) with sensing-capabilities for various threats, offering a mobile, 'opportunistic' pool of secondary sensors that can be polled to augment the information provided by a pre-deployed set of primary sensors, to reduce uncertainty in threat-detection. We derive an optimal decision-rule for fusing the information from fixed and mobile, accounting for the costs of erroneous decisions. We also formulate a model for an 'equitable' solution to the problem of the optimal positioning of sensors.
    Sensors Applications Symposium, 2008. SAS 2008. IEEE; 03/2008