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Generating mimicry attacks using genetic programming: A benchmarking study

Generating mimicry attacks using genetic programming: A benc...

引用

ieee symposium on computational intelligence in Cyber Security, CICS

作者： H. Gunes Kayacik A. Nur Zincir-Heywood Malcolm I. Heywood Stefan Burschka Faculty of Computer Science Dalhousie University Halifax NS Canada Software & Security Technologies Swisscom Innovations Switzerland

Mimicry attacks have been the focus of detector research where the objective of the attacker is to generate multiple attacks satisfying the same generic exploit goals for a given vulnerability. In this work, multi-objective Genetic programming is used to establish a ldquoblack-boxrdquo approach to mimicry attack generation. No knowledge is made of internal data structures of the target anomaly detector, only the anomaly rate reported by the detector. Such a ldquoblack boxrdquo methodology enables a vulnerability testing approach where both open-source and commodity anomaly detection systems can be tested. The approach successfully identifies exploits when benchmarked over four detectors and four applications.

关键词： Genetic programming Detectors System testing Data structures Intrusion detection Feedback Buffer overflow Gain control Computer science Technological innovation

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Fuzzy Logic control and Fault Detection in Centralized Chilled Water System

Fuzzy Logic Control and Fault Detection in Centralized Chill...

引用

ieee symposium Series on computational intelligence (SSCI)

作者： Noor Asyikin Sulaiman Mohd Fauzi Othman Hayati Abdullah Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Skudai Johor Malaysia Electronic System Engineering Department Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Centre of Electrical Energy System (CEES) Universiti Teknologi Malaysia Skudai Johor Malaysia

The objective of this work is to develop and implement a fuzzy controller and fuzzy fault detection for centralized chilled water system. Both controller and fault detector are implemented in supply air dampers of air handling unit (AHU). A few cases are tested in this paper to investigate the effectiveness of the developed systems. All simulation is carried out using MATLAB/SIMULINK. Results illustrate that the fuzzy controller is able to maintain rooms' temperature according to desired temperature whereas the fault detection can detect unusual behavior in supply air flow rate.

关键词： Shock absorbers Fault detection Fuzzy logic Water heating Niobium Atmospheric modeling

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Data Augmentation for Vulnerability Detection Based on Code Refactoring and Mixup 35

Data Augmentation for Vulnerability Detection Based on Code ...

引用

35th ieee International symposium on Software Reliability Engineering Workshops, ISSREW 2024

作者： Xing, Ying Huang, Jiaqi Wang, Guilong You, Yehao Yang, Bin Li, Xiaofeng Luo, Yixing Beijing University of Posts and Telecommunications School of Intelligent Engineering and Automation Beijing China Beijing University of Posts and Telecommunications School of Artifcial Intelligence Beijing China Yunnan Key Laboratory of Software Engineering Yunnan China China Unicom Research Institute Beijing China Beijing Institute of Control Engineering Software Development Center Beijing China

ISBN: (纸本)9798350367041

In recent years, the number of software vulnerabilities has gradually increased, posing a threat to the security of software, and identifying whether there are vulnerabilities in software is crucial for assuring its quality. With the development of deep learning, vulnerability detection based on deep learning has achieved good results. However, real-world software vulnerability datasets often suffer from class imbalance and a lack of labeled data, limiting the performance of deep learning models. Therefore, this paper proposes a data augmentation method to alleviate these two problems. Firstly, we treats samples with vulnerabilities in the dataset as code, and generates more samples with vulnerabilities through code refactoring to alleviate class imbalance issues. Secondly, we use the mixup method to perform linear interpolation on the embedding vectors which represent codes, and add the interpolated vectors into the training set, thereby increasing the amount of labeled training data. To evaluate our method, we conducted experiments on three projects of the Promise dataset. The experimental results show that our data augmentation method can effectively improve the effect of vulnerability detection. © 2024 ieee.

关键词： Adversarial machine learning

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Induced Generalized Ordered Weighted Logarithmic Aggregation Operators

Induced Generalized Ordered Weighted Logarithmic Aggregation...

引用

ieee symposium Series on computational intelligence

作者： Victor G. Alfaro-Garcia Anna M. Gil-Lafuente José M. Merigó Dept. of Business Administration University of Barcelona Barcelona Spain Dept. of Management Control and Information Systems University of Chile Santiago Chile

ISBN: (纸本)9781509042418

We present the induced generalized ordered weighted logarithmic aggregation (IGOWLA) operator. It is an extension of the generalized ordered weighted logarithmic aggregation (GOWLA) operator. The IGOWLA operator uses order-induced variables that modify the reordering mechanism of the arguments to be aggregated. The main advantage of the induced process is the consideration of the complex attitude of the decision makers. We study some properties of the IGOWLA operator, such as idempotency, commutativity, boundedness and monotonicity. Finally we present an illustrative example of a group decision-making procedure using a multi-person analysis and the IGOWLA operator in the area of innovation management.

关键词： OWA operator logarithmic aggregation operators induced aggregation operators group decision-making

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A novel computationally intelligent architecture for identification and control of nonlinear systems

A novel computationally intelligent architecture for identif...

引用

ieee International Conference on Robotics and automation (ICRA)

作者： M.O. Efe O. Kaynak I.J. Rudas Mechatronics Research and Application Center Bogaziçi University Istanbul Turkey Department of Information Technology Banki Donat Polytechnic Budapest Hungary

In this study, a novel method for identification and control of nonlinear systems is developed. The method proposed realizes the dynamics of a system by employing the Runge-Kutta method at the upper level. The intermediate level of the strategy constructs the architecture utilizing an adaptive neuro fuzzy inference system. The overall system is able to imitate the behavior of a complex dynamic system with a few rules or to control the system with high accuracy. The proposed method has been applied to a two degrees of freedom direct drive SCARA robot.

关键词： computational intelligence Competitive intelligence Computer architecture Nonlinear control systems control systems Nonlinear systems Neural networks Fuzzy systems Robots Manipulators

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Measuring Data Quality for Dataset Selection in Offline Reinforcement Learning

Measuring Data Quality for Dataset Selection in Offline Rein...

引用

ieee symposium Series on computational intelligence (SSCI)

作者： Phillip Swazinna Steffen Udluft Thomas Runkler Siemens Technology & Technical University of Munich Munich Germany Siemens Technology Munich Germany

ISBN: (纸本)9781728190495

Recently developed offline reinforcement learning algorithms have made it possible to learn policies directly from pre-collected datasets, giving rise to a new dilemma for practitioners: Since the performance the algorithms are able to deliver depends greatly on the dataset that is presented to them, practitioners need to pick the right dataset among the available ones. This problem has so far not been discussed in the corresponding literature. We discuss ideas how to select promising datasets and propose three very simple indicators: Estimated relative return improvement (ERI) and estimated action stochasticity (EAS), as well as a combination of the two (COI), and empirically show that despite their simplicity they can be very effectively used for dataset selection.

关键词： Correlation Data integrity Industrial control Current measurement Decision making Reinforcement learning Benchmark testing

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Machine learning based encrypted traffic classification: Identifying SSH and Skype

Machine learning based encrypted traffic classification: Ide...

引用

ieee symposium on computational intelligence in Security and Defense Applications, CISDA

作者： Riyad Alshammari A. Nur Zincir-Heywood Dalhousie University Halifax NS Canada

The objective of this work is to assess the robustness of machine learning based traffic classification for classifying encrypted traffic where SSH and Skype are taken as good representatives of encrypted traffic. Here what we mean by robustness is that the classifiers are trained on data from one network but tested on data from an entirely different network. To this end, five learning algorithms - adaboost, support vector machine, Nai¿e Bayesian, RIPPER and C4.5 - are evaluated using flow based features, where IP addresses, source/destination ports and payload information are not employed. Results indicate the C4.5 based approach performs much better than other algorithms on the identification of both SSH and Skype traffic on totally different networks.

关键词： Machine learning Cryptography Telecommunication traffic Traffic control Payloads Bayesian methods Robustness Support vector machines Support vector machine classification Financial management

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ExSAIS: Workshop on Extreme Scaling of AI for Science Message from the workshop chairs

ExSAIS: Workshop on Extreme Scaling of AI for Science Messag...

引用

ieee International symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Svitlana Volkova Robert Rallo

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

ExSAIS: Workshop on Extreme Scaling of AI for Science, brings together researchers in Artificial intelligence (AI) and High Performance Computing (HPC) to enable scientific discovery at scale. The evolution of machine perception to machine learning and reasoning, and ultimately machine intelligence, has a potential to significantly impact acceleration and advancement of autonomous scientific discovery and the operation of scientific instruments. While machine reasoning will enable intelligent systems to better understand and interact with their physical world, machine intelligence through modeling, simulation and automation, closes the gap between experiments, extreme computing, and scientific discovery. In order to usher in this new era of autonomous science, advances in several areas of artificial intelligence and other disciplines e.g., high-performance computing, data engineering need to come together.

关键词： Conferences Artificial intelligence Distributed processing computational modeling Machine intelligence Instruments High performance computing

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Advanced Remote Tower project validation results

Advanced Remote Tower project validation results

引用

11th IFAC/IFIP/IFORS/IEA symposium on Analysis, Design, and Evaluation of Human-Machine Systems, HMS 2010

作者： Van Schaik, F.J. Roessingh, J.J.M. Bengtsson, J. Lindqvist, G. Fält, K. National Aerospace Laboratory NLR Amsterdam Netherlands Luftfartsverket LFV Malmö - Sturup Sweden Saab Security Systems AB Järfälla Sweden

ISBN: (纸本)9783902661944

The Advanced Remote Tower project (ART) studies enhancements to an existing LFV prototype facility for a remotely operated tower: projection on a 360 degrees panorama screen, adding synthesized geographic information and meteorological information, video tracking, fusion of video and radar tracks, labelling, visibility enhancement and surveillance operations with a remotely controlled Pan Tilt Zoom camera. The ART functions have been embedded in the existing Swedish test facility for remote tower operations in Malmö airport Sturup observing Ängelholm traffic about 100 km to the North. They were tuned and validated by 15 tower controllers. Emphasis was on the traffic and situation awareness of tower controllers using remote cameras and projection system for safe operational tower control, replacing direct view on the airport and its traffic. The validation results give valuable information for further development and operational application even outside the Remote Tower application area.

关键词： Air traffic control

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Experimental study on robust force control of a flexible arm with a symmetric rigid tip body

Experimental study on robust force control of a flexible arm...

引用

ieee International Conference on Robotics and automation (ICRA)

作者： F. Matsuno S. Umeyama S. Kasai Department of Computational Intelligence and Systems Science Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology Yokohama Japan Department of Computer and Systems Engineering Faculty of Engineering Kobe University Kobe Japan Department of Electronic Engineering Kobe College of Technology Kobe Japan

In this paper, an experimental study on robust control of bending and torsional vibrations and contact force of a one-link flexible arm is discussed. The flexible arm carries a symmetric rigid tip body, of which the mass center lies on the center axis of the arm. We derive dynamic equations of the joint angle, the vibrations of the flexible link, and the contact force. On the basis of a finite-dimensional modal model of a distributed-parameter system, robust controllers are constructed. Some experimental results are shown.

关键词： Robust control Force control Manipulators Vibration control Equations Orbital robotics Rotors computational intelligence Systems engineering and theory Educational institutions

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