Towards Reversible Cyberattacks

This paper appeared in the Proceedings of the 9th European Conference on Information Warfare and Security, July 2010, Thessaloniki, Greece.Warfare without damage has always been a dream of military planners. Traditional warfare usually leaves persistent side effects in the form of dead and injured people and damaged infrastructure. An appealing feature of cyberwarfare is that it could be more ethical than traditional warfare because its damage could be less and more easily repairable. Damage to data and programs (albeit not physical hardware) can be repaired by rewriting over damaged bits with correct data. However, there are practical difficulties in ensuring that cyberattacks minimize unreversible collateral damage while still being easily repairable by the attacker and not by the victim. We discuss four techniques by which cyberattacks can be potentially reversible. One technique is reversible cryptography, where the attacker encrypts data or programs to prevent their use, then decrypts them after hostilities have ceased. A second technique is to obfuscate the victim's computer systems in a reversible way. A third technique to withhold key data from the victim, while caching it to enable quick restoration on cessation of hostilities. A fourth technique is to deceive the victim so that think they mistakenly think they are being hurt, then reveal the deception at the conclusion of hostilities. We also discuss incentives to use reversible attacks such as legality, better proportionality, lower reparations, and easier ability to use third parties. As an example, we discuss aspects of the recent cyberattacks on Georgia.Approved for public release; distribution is unlimited

Inferring depictions in natural-language captions for efficient access to picture data

This paper appeared in: Information Processing and Management, 30, no. 3 (1994), 379-388.Multimedia data can require significant examination time to find desired features ("content analysis"). An alternative is using natural-language captions to describe the data, and matching captions to English queries. But it is hard to include everything in the caption of a complicated datum, so significant content analysis may still seem required. We discuss linguistic clues in captions, both syntactic and semantic, that can simplify or eliminate content analysis. We introduce the notion of concept depiction and rules for depiction inference. Our approach is implemented in an expert system which demonstrated significant increases in recall in experiments.sponsored by the Naval Ocean Systems Center in San Diego, California, the Naval Air Warfare Center, Weapons Division, in China Lake, California, the U. S. Naval Postgraduate Schoolhttp://archive.org/details/inferringdepicti00roweFunds provided by the Chief for Naval Operations, and the Defense Advanced Research Projects AdministrationApproved for public release; distribution is unlimited

Obtaining Optimal Mobile-Robot Paths with Non-Smooth Anisotropic Cost Functions Using Qualitative-State Reasoning

This paper appeared in the International Journal of Robotics Research, 16, 3 (June 1997), 375-399. The equations were reconstructed in 2007 for better readability.Realistic path-planning problems frequently show anisotropism, dependency of traversal cost or feasibility on the traversal heading. Gravity, friction, visibility, and safety are often anisotropic for mobile robots. Anisotropism often differs qualitatively with heading, as when a vehicle has insufficient power to go uphill or must brake to avoid accelerating downhill. Modeling qualitative distinctions requires discontinuities in either the cost-per-traversal-distance function or its derivatives, preventing direct application of most results of the calculus of variations. We present a new approach to optimal anisotropic path planning that first identifies qualitative states and permissible transitions between them. If the qualitative states are chosen appropriately, our approach replaces an optimization problem with such discontinuities by a set of subproblems without discontinuities, subproblems for which optimization is likely to be faster and less troublesome. Then the state space in the near neighborhood of any particular state can be partitioned into "behavioral regions" representing states optimally reachable by single qualitative "behaviors", sequences of qualitative states in a finite-state diagram. Simplification of inequalities and other methods can find the behavioral regions. Our ideas solve problems not easily solvable any other way, especially those with what we define as "turn-hostile" anisotropism. We illustrate our methods on two examples, navigation on an arbitrarily curved surface with gravity and friction effects (for which we show much better performance than a previously-published program 22 times longer), and flight of a simple missile.This work was supported in part by the U.S. Army Combat Developments Experimentation Center under MIPR ATEC 88-86. This work was also prepared in part in conjunction with research conducted for the Naval Air Systems Commandfunded by the Naval Postgraduate SchoolApproved for public release; distribution is unlimited

Counterplanning Deceptions to Foil Cyber-Attack Plans

Proceedings of the 2003 IEEE Workshop in Information Assurance, West Point, NY, June 2003Tactics involving deception are important in military strategies. We have been exploring deliberate deception in defensive tactics by information systems under cyber-attack as during information warfare. We have developed a tool to systematically "counterplan" or find ways to foil a particular attack plan. Our approach is to first find all possible atomic "ploys" that can interfere with the plan. Ploys are simple deceits the operating system can do such as lying about the status of a file. We analyze ploys as to the degree of difficulty they cause to the plan wherever they can be applied. We then formulate a "counterplan" by selecting the most cost-effective set of ploys and assign appropriate presentation methods for them, taking into account the likelihood that, if we are not careful, the attacker will realize they are being deceived and will terminate our game with them. The counterplan can be effected by a modified operating system. We have implemented our counterplanner in a tool MECOUNTER that uses multi-agent planning coupled with some novel inference methods to efficiently find a best counterplan. We apply the tool to an example of a rootkit-installation plan and discuss the results.supported by the U.S. Department of Justice Office of Justice Programs and Office for Domestic PreparednessApproved for public release; distribution is unlimited

Statistical versus symbolic parsing for captioned-information retrieval / Workshop on the Balancing Act, ACL-94, Las Cruces NM, July 1994

Workshop on the Balancing Act, ACL-94, Las Cruces NM, July 1994We discuss implementation issues of MARIE-1, a mostly symbolic parser fully implemented, and MARIE-2, a more statistical parser partially implemented. They address a corpus of 100,000 picture captions. We argue that the mixed approach of MARIE-2 should be better for this corpus because its algorithms (not data) are simpler.This work was sponsored by DARPA as part of the I3 Project under AO 8939. Copyright is held by the ACL.This work was sponsored by DARPA as part of the I3 Project under AO 8939. Copyright is held by the ACL

Privacy Concerns with Digital Forensics

The article of record as published may be found at https://doi.org/10.4018/978-1-4666-9905-2.ch00

Understanding of Navy Technical Language via Statistical Parsing

A key problem in indexing technical information is the interpretation of technical words and word senses, expressions not used in everyday language. This is important for captions on technical images, whose often pithy descriptions can be valuable to decipher. We describe the natural-language processing for MARIE-2, a natural-language information retrieval system for multimedia captions. Our approach is to provide general tools for lexicon enhancement with the specialized words and word senses, and to learn word usage information (both on word senses and word-sense pairs) from a training corpus with a statistical parser. Innovations of our approach are in statistical inheritance of binary co-occurrence probabilities and in weighting of sentence subsequences. MARIE-2 was trained and tested on 616 captions (with 1009 distinct sentences) from the photograph library of a Navy laboratory. The captions had extensive nominal compounds, code phrases, abbreviations, and acronyms, but few verbs, abstract nouns, conjunctions, and pronouns. Experimental results fit a processing time in seconds of 0.0858n2.876 and a number of tries before finding the best interpretation of 1.809n1.668 where n is the number of words in the sentence. Use of statistics from previous parses definitely helped in reparsing the same sentences, helped accuracy in parsing of new sentences, and did not hurt time to parse new sentences. Word-sense statistics helped dramatically; statistics on word-sense pairs generally helped but not always

Testing Multiple Credit/Blame Assignment Methods for Learning

NPS NRP Project PosterTesting Multiple Credit/Blame Assignment Methods for LearningN2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Testing Multiple Credit/Blame Assignment Methods for Learning

NPS NRP Executive SummaryTesting Multiple Credit/Blame Assignment Methods for LearningN2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.