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New Horizons in Search Theory, 4 th Workshop “Investigating ‘Hider Theory’”

New Horizons in Search Theory, 4 th Workshop “Investigating ‘Hider Theory’” Introductory Talking Points by Dr Ralph S Klingbeil Undersea Warfare Analysis Department, Code 60 Naval Undersea Warfare Center Division Newport and Operations Department Navy Warfare Development Command

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New Horizons in Search Theory, 4 th Workshop “Investigating ‘Hider Theory’”

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  1. New Horizons in Search Theory, 4th Workshop “Investigating ‘Hider Theory’” Introductory Talking Points by Dr Ralph S Klingbeil Undersea Warfare Analysis Department, Code 60 Naval Undersea Warfare Center Division Newport and Operations Department Navy Warfare Development Command 27 April 2004

  2. Outline • Hiders and hiding • The search and detection problem

  3. Examples of “Hiders” and “Hiding” • A ballistic missile submarine (SSBN) that does not want to be detected while on deterrence patrol • A downed pilot in enemy-controlled territory who does not want to be found by the enemy but does want to be found by rescue forces • An embezzler who does not want to be discovered for a long time • An in-country terrorist waiting for orders or opportunity to strike within some time duration • An encrypted electronic message that is perhaps buried within a benign or noise transmission • A pollution event; hide who did it and perhaps blame someone else • … “Hider Theory” should shed light on what these examples have in common and what makes them different.

  4. Search and Hide • search – The process of attempting to find desired targets • hide – To use signature reduction, clutter, camouflage, deception, decoys, and evasion to thwart search by an opponent

  5. Some Definitions (DOD/NATO) • camouflage – The use of natural or artificial material on personnel, objects, or tactical positions with the aim of confusing, misleading, or evading the enemy • deception – Those measures designed to mislead the enemy by manipulation, distortion, or falsification of evidence to induce the enemy to react in a manner prejudicial to the enemy’s interests • evasion – The process whereby individuals who are isolated in hostile or unfriendly territory avoid capture with the goal of successfully returning to areas under friendly control • decoy – An imitation in any sense of a person, object, or phenomenon which is intended to deceive enemy surveillance devices or mislead enemy evaluation • clutter (Skolnik) – The conglomeration of unwanted signals received by the searcher’s sensors (from the natural surroundings and sensor dependent) and which can be exploited by the hider

  6. Time • Time is often a key variable; the target may not need to hide forever • A submarine goes away when it runs out of consumables or its mission ends • An embezzler might be satisfied with not being discovered for a decade • An old decoded message may not compromise a mission • …

  7. Outline • Hiders and hiding • The search and detection problem

  8. Operating Characteristic 1 INCREASING CONSPICUITY P(T|t) B CHANCE LINE A 0 0 1 P(T|nt) Forced Decision Confusion Matrix DECISION TARGET NON-TARGET P(T|t) + P(NT|t) = 1 P(T|nt) + P(NT|nt) = 1 actual target P(T|t) P(NT|t) object non-target P(T|nt) P(NT|nt) Operating characteristic curve defines the relationship between P(T|nt) and P(T|nt) Detecting/Classifying Contacts Classical Inference Moving the threshold generates OC curve nt t PDF P(NT|t) P(T|nt) METRIC FOR THE ATTRIBUTE A locatable object must exhibit characteristics that allow the searcher to differentiate it from its surroundings.

  9. CLASSIFICATION DECISION CLASSIFY AS TARGET CLASSIFY AS NON-TARGET True Alarm False Dismissal Target Input Stimulus False Alarm True Dismissal Non-Target Confusion Matrix for Classification

  10. CLASSIFICATION DECISION CLASSIFY AS TARGET CLASSIFY AS NON-TARGET DECISION PENDING True Alarm False Dismissal No Decision Target Input Stimulus False Alarm True Dismissal No Decision Non-Target False Alarm True Dismissal No Decision Background Extended Confusion Matrix

  11. Queueing and Reneging in Search Probability of Classification PCLASS = PACQCLASS * P(T|t) PRIORITY SERVERS The Searcher’s Queueing Problem SERVICED DEPARTURES ARRIVALS QUEUE TOI Non-TOI RENEGE BALK Entering/Exiting Sensor Coverage - Reneging - TARGET TRACK DETECTION RANGE The hider wants the searcher to be very busy doing the wrong thing

  12. Random Search from the Hider’s Point of View • P(T) = 1 – exp( – 2 R V TEFF / A ) • Make detection range R small; reduce signatures • Make searcher reduce speed V due to false contact investigations and fear of counterdetection • Make the search area A as large as possible • Make effective search time TEFF small compared to available search time T • Expose for short times TEFF = TEXP • Hide amongst false contacts TEFF = T / ( 1 + FCR TINV) If it were done, when ‘tis done, Then ‘twere well it were done quickly. Macbeth Act I, Scene 7

  13. SSBN-ASW Game Value of game: max(x) min(y) [ t Σ xi vi / (1 + αi yi) ] Αi = Si Hi / Ai

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