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Optimizing anomaly detector deployment under evolutionary black-box vulnerability testing

Optimizing anomaly detector deployment under evolutionary bl...

引用

ieee symposium on computational intelligence in security and defense applications, cisda

作者： Hilmi Güneş Kayacik Nur Zincir-Heywood Malcolm Heywood Stefan Burschka Faculty of Computer Science Dalhousie University Canada Swisscom Innovations Inc. Switzerland

This work focuses on testing anomaly detectors from the perspective of a Multi-objective Evolutionary Exploit Generator (EEG). Such a framework provides users of anomaly detection systems two capabilities. Firstly, no knowledge of protected data structures need to be assumed (i.e. the detector is a black-box), where the time, knowledge and availability of tools to perform such an analysis might not be generally available. Secondly, the evolved exploits are then able to demonstrate weaknesses in the ensuing detector parameterization. Therefore, the system administrator can identify the suitable parameters for the effective operation of the detector. EEG is employed against two second generation anomaly detectors, namely pH and pH with schema mask, on four UNIX applications in order to perform a vulnerability assessment and make a comparison between the two detectors.

关键词： Detectors Testing Electroencephalography Buffer overflow Data structures computational intelligence security Counting circuits Delay Abstracts

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Analysis of the 1999 DARPA/Lincoln Laboratory IDS evaluation data with NetADHICT

Analysis of the 1999 DARPA/Lincoln Laboratory IDS evaluation...

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ieee symposium on computational intelligence in security and defense applications, cisda

作者： Carson Brown Alex Cowperthwaite Abdulrahman Hijazi Anil Somayaji Carleton Computer Security Lab School of Computer Science Carleton University Ottawa ONT Canada

The 1999 DARPA/Lincoln Laboratory IDS evaluation data has been widely used in the intrusion detection and networking community, even though it is known to have a number of artifacts. Here we show that many of these artifacts, including the lack of damaged or unusual background packets and uniform host distribution, can be easily extracted using NetADHICT, a tool we developed for understanding networks. In addition, using NetADHICT we were able to identify extreme temporal variation in the data, a characteristic that was not identified in past analyses. These results illustrate the utility of NetADHICT in characterizing network traces for experimental purposes.

关键词： Laboratories Intrusion detection Telecommunication traffic Traffic control Data visualization Protocols Production Testing Military computing computational modeling

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Testing harbour patrol and interception policies using particle-swarm-based learning of cooperative behavior

Testing harbour patrol and interception policies using parti...

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ieee symposium on computational intelligence in security and defense applications, cisda

作者： Tom Flanagan Chris Thornton Jörg Denzinger Department of Computer Science University of Calgary Calgary Canada

We present a general scheme for testing multiagent systems, respectively policies used by them, for unwanted emergent behavior using learning of cooperative behavior via particle swarm systems. By using particle swarm systems in this setting, we are able to create agents interacting/attacking the tested agents that can use parameterised high-level actions. We also can evaluate the quality of an attack using several measures that can be prioritised and used in a multi-objective manner in the search. This solves some general problems of other testing approaches using learning. We instantiate this general scheme to test harbour patrol and interception policies for two Canadian harbours, showing that our approach is able to find problems in these policies.

关键词： System testing Multiagent systems security Particle swarm optimization computational intelligence Fires Humans Navigation Path planning Optimization methods

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New search algorithm for randomly located objects: A non-cooperative agent based approach

New search algorithm for randomly located objects: A non-coo...

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ieee symposium on computational intelligence in security and defense applications, cisda

作者： Dragos Calitoiu Department of Computer Engineering Carleton University Ottawa Canada

In this paper we address the general question of what is the best strategy to search efficiently for randomly located objects (target sites). We propose a new agent based algorithm for searching in an unpredictable environment. The originality of our work consists in applying a non-cooperative strategy, namely the distributed Goore Game model, as opposed to applying the classical collaborative and competitive strategies, or individual strategies. This paper covers only the non-destructive search that occurs when the agent visits the same target many times. The nondestructive search can be performed in either of the two cases: if the target becomes temporarily inactive or if it leaves the area. The proposed algorithm has two versions: one when the agent can move with a step equal to unity and the other when the step of the agent follows a Levy flight distribution. The latter version is inspired by the work of A.M. Reynolds, motivated by biological examples.

关键词： Voting Collaborative work Radar detection computational intelligence security Terminology Learning automata Artificial intelligence Helium Plastics

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Face Recognition System Using Ant Colony Optimization-Based Selected Features

Face Recognition System Using Ant Colony Optimization-Based ...

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ieee symposium on computational intelligence in security and defense applications, cisda

作者： Hamidreza Rashidy Kanan Karim Faez Mehdi Hosseinzadeh Image Processing and Pattern Recognition Laboratory Electrical Engineering Department Tehran Polytechnic Amirkabir University of Technology슠 Tehran Iran Department of Computer Engineering University of Isfahan Isfahan Iran

Feature selection (FS) is a most important step which can affect the performance of pattern recognition system. This paper presents a novel feature selection method that is based on ant colony optimization (ACO). ACO algorithm is inspired of ant's social behavior in their search for the shortest paths to food sources. In the proposed algorithm, classifier performance and the length of selected feature vector are adopted as heuristic information for ACO. So, we can select the optimal feature subset without the priori knowledge of features. Simulation results on face recognition system and ORL database show the superiority of the proposed algorithm

关键词： Face recognition Ant colony optimization Discrete wavelet transforms Pattern recognition Artificial intelligence Particle swarm optimization computational intelligence Computer security Application software Image processing

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Face Recognition using Gaborface-based 2DPCA and (2D)2PCA Classification with Ensemble and Multichannel Model

Face Recognition using Gaborface-based 2DPCA and (2D)2PCA Cl...

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ieee symposium on computational intelligence in security and defense applications, cisda

作者： Lin Wang Yongping Li Chengbo Wang Hongzhou Zhang Shanghai Institute of Applied Physics Chinese Academy and Sciences Shanghai China

This paper introduces Gaborface-based 2DPCA and (2D) 2 PCA classification method based on 2D Gaborface matrices rather than transformed ID feature vectors. Two kinds of strategies to use the bank of Gaborfaces are proposed: ensemble Gaborface representation (EGFR) and multichannel Gaborface representation (MGFR). The feasibility of our method is proved with the experimental results on the ORL and Yale databases. In particular, the MGFR-based (2D) 2 PCA method achieves 100% recognition accuracy for ORL database, and 98.89% accuracy for Yale database with five training samples per class

关键词： Face recognition Gabor filters Sampling methods Databases Image sampling Filter bank computational intelligence Principal component analysis Convolution Image coding

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Evaluating model drift in machine learning algorithms

Evaluating model drift in machine learning algorithms

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ieee symposium on computational intelligence in security and defense applications, cisda

作者： Kevin Nelson George Corbin Mark Anania Matthew Kovacs Jeremy Tobias Misty Blowers BAE Systems Rome NY USA Air Force Research Laboratory Rome NY USA

Machine learning is rapidly emerging as a valuable technology thanks to its ability to learn patterns from large data sets and solve problems that are impossible to model using conventional programming logic. As machine learning techniques become more mainstream, they are being applied to a wider range of application domains. These algorithms are now trusted to make critical decisions in secure and adversarial environments such as healthcare, fraud detection, and network security, in which mistakes can be incredibly costly. They are also a critical component to most modern autonomous systems. However, the data driven approach utilized by these machine learning methods can prove to be a weakness if the data on which the models rely are corrupted by either nefarious or accidental means. Models that utilize on-line learning or periodic retraining to learn new patterns and account for data distribution changes are particularly susceptible to corruption through model drift. In modeling this type of scenario, specially crafted data points are added to the training set over time to adversely influence the system, inducing model drift which leads to incorrect classifications. Our work is focused on exploring the resistance of various machine learning algorithms to such an approach. In this paper we present an experimental framework designed to measure the susceptibility of anomaly detection algorithms to model drift. We also exhibit our preliminary results using various machine learning algorithms commonly found in intrusion detection research.

关键词： Training Hidden Markov models Data models Machine learning algorithms Algorithm design and analysis Image color analysis security

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Cloud-based collaborative creation and simulation of courses of action: Creation of a prototype web application using new HTML5 features

Cloud-based collaborative creation and simulation of courses...

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ieee symposium on computational intelligence in security and defense applications, cisda

作者： Eric Torunski CAE Inc. University of Ottawa Ottawa Canada

There are many domains that require predefined plans of action in response to certain events. For example, emergency responders have response plans for emergencies such as airplane crashes or other mass casualty incidents, and militaries have plans for disaster relief. In creating these plans, there is a great deal of collaboration required in creation, testing, and training people involved in plan execution. These response plans can be tested in simulations to model their effectiveness and so that domain experts can see potential problems. This paper presents a novel approach for creating such response plans as a collaborative simulation in the cloud.

关键词： computational modeling Planning Data models Cloud computing Helicopters Collaboration

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Simulation analysis on destabilization of complex adaptive organizations

Simulation analysis on destabilization of complex adaptive o...

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ieee symposium on computational intelligence in security and defense applications, cisda

作者： Il-Chul Moon KAIST Daejeon South Korea

Many adversarial organizations, such as organized crime groups, terrorist networks, and the like, are complex adaptive organizations. Therefore, strategies against them should consider the natures of complexity and adaptivity. However, such natures create nonlinear effects that are difficult to predict. To mitigate those difficulties, I utilize agent-based simulations that could possibly capture unexpected responses coming from our interventions into their organizations. This paper presents a simulation analysis example of an action against a terrorist group. Particularly, this example points out three critical aspects of simulation analysis. First, this simulation example shows how to setup a simulation analysis to anticipate an intervention's results. Second, this example illustrates various results making analysis useful. Third, this example describes statistical processing of the results. I expect that the three points will advance the current practices of simulation analysis on complex adaptive organizations.

关键词： Analytical models computational modeling Humans Personnel Testing Adaptive systems computational intelligence security Moon Complex networks

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Semi-autonomous management of multiple ad-hoc teams of UAVs

Semi-autonomous management of multiple ad-hoc teams of UAVs

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ieee symposium on computational intelligence in security and defense applications, cisda

作者： Richard Loe Christopher Maracchion Andrew Drozd ANDRO Computational Solutions Rome NY USA

A Distributed Battle Manager (DBM) system based on Concurrent MACro Partially Observable Markov Decision Processes (CMAC-POMDP) is proposed to manage multiple competing missions. Implementation details are presented for a semi-autonomous management of multiple ad-hoc teams of UAVs operating under extreme uncertainty in a contested environment. The proposed solution is semi-autonomous since command and control teams perform target confirmation, weapon selection, weapon release, and bomb damage assessment. Our proposed approach decomposes the resource management requirements into specialized mission timelines. There would be one adaptive mission timeline for each system objective, and each timeline would be represented by a POMDP. At any time, the DBM would be controlling multiple concurrent timelines that are competing for system resources. Each timeline is solved independently to obtain the optimal MDP solution parameters. These solution parameters are then combined using linear programming with constraints to obtain a suboptimal system solution. The resulting suboptimal solutions provide satisfactory real-time system performance. Under extreme uncertainty, it is preferable to maximize robustness utilizing an adequately performing solution as opposed to finding an optimal but brittle solution. Performance results of the core CMAC-POMDP algorithm are presented for a system implemented to manage multiple heterogeneous sensors addressing multiple simultaneous threats. This simpler resource management system utilizes the same timeline for all of the threats. Simulations demonstrate better than real-time performance even for large numbers of threats. Furthermore, computational requirements are shown to grow linearly with the number of threats. Extension to multiple simultaneous timelines for the DBM system is straightforward.

关键词： Sensor systems Target tracking Markov processes Weapons Timing Planning

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