Reports of the Workshops of the 32nd AAAI Conference on Artificial Intelligence

The AAAI-18 workshop program included 15 workshops covering a wide range of topics in AI. Workshops were held Sunday and Monday, February 2–7, 2018, at the Hilton New Orleans Riverside in New Orleans, Louisiana, USA. This report contains summaries of the Affective Content Analysis workshop; the Artificial Intelligence Applied to Assistive Technologies and Smart Environments; the AI and Marketing Science workshop; the Artificial Intelligence for Cyber Security workshop; the AI for Imperfect-Information Games; the Declarative Learning Based Programming workshop; the Engineering Dependable and Secure Machine Learning Systems workshop; the Health Intelligence workshop; the Knowledge Extraction from Games workshop; the Plan, Activity, and Intent Recognition workshop; the Planning and Inference workshop; the Preference Handling workshop; the Reasoning and Learning for Human-Machine Dialogues workshop; and the the AI Enhanced Internet of Things Data Processing for Intelligent Applications workshop.

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Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

AI Magazine ◽

10.1609/aimag.v40i3.4981 ◽

2019 ◽

Vol 40 (3) ◽

pp. 67-78

Author(s):

Guy Barash ◽

Mauricio Castillo-Effen ◽

Niyati Chhaya ◽

Peter Clark ◽

Huáscar Espinoza ◽

...

Keyword(s):

Artificial Intelligence ◽

Language Processing ◽

Cyber Security ◽

Question Answering ◽

Intent Recognition ◽

Affective Content ◽

Learning Plan ◽

Dialog System ◽

Affective Content Analysis ◽

Games And Simulations

The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.

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Reports of the 2016 AAAI Workshop Program

AI Magazine ◽

10.1609/aimag.v37i3.2680 ◽

2016 ◽

Vol 37 (3) ◽

pp. 99-108

Author(s):

Stefano Albrecht ◽

Bruno Bouchard ◽

John S. Brownstein ◽

David L. Buckeridge ◽

Cornelia Caragea ◽

...

Keyword(s):

Artificial Intelligence ◽

Cyber Security ◽

Health Informatics ◽

Smart Grids ◽

Imperfect Information ◽

Assistive Technologies ◽

Exploratory Research ◽

Ai Ethics ◽

Informal Setting ◽

Declarative Learning

The Workshop Program of the Association for the Advancement of Artificial Intelligence’s Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) was held at the beginning of the conference, February 12-13, 2016. Workshop participants met and discussed issues with a selected focus — providing an informal setting for active exchange among researchers, developers and users on topics of current interest. To foster interaction and exchange of ideas, the workshops were kept small, with 25-65 participants. Attendance was sometimes limited to active participants only, but most workshops also allowed general registration by other interested individuals. The AAAI-16 Workshops were an excellent forum for exploring emerging approaches and task areas, for bridging the gaps between AI and other fields or between subfields of AI, for elucidating the results of exploratory research, or for critiquing existing approaches. The fifteen workshops held at AAAI-16 were Artificial Intelligence Applied to Assistive Technologies and Smart Environments (WS-16-01), AI, Ethics, and Society (WS-16-02), Artificial Intelligence for Cyber Security (WS-16-03), Artificial Intelligence for Smart Grids and Smart Buildings (WS-16-04), Beyond NP (WS-16-05), Computer Poker and Imperfect Information Games (WS-16-06), Declarative Learning Based Programming (WS-16-07), Expanding the Boundaries of Health Informatics Using AI (WS-16-08), Incentives and Trust in Electronic Communities (WS-16-09), Knowledge Extraction from Text (WS-16-10), Multiagent Interaction without Prior Coordination (WS-16-11), Planning for Hybrid Systems (WS-16-12), Scholarly Big Data: AI Perspectives, Challenges, and Ideas (WS-16-13), Symbiotic Cognitive Systems (WS-16-14), and World Wide Web and Population Health Intelligence (WS-16-15).

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The AAAI-13 Conference Workshops

AI Magazine ◽

10.1609/aimag.v34i4.2511 ◽

2013 ◽

Vol 34 (4) ◽

pp. 108-115

Author(s):

Vikas Agrawal ◽

Christopher Archibald ◽

Mehul Bhatt ◽

Hung Bui ◽

Diane J. Cook ◽

...

Keyword(s):

Artificial Intelligence ◽

Health Informatics ◽

Imperfect Information ◽

Intent Recognition ◽

System Architectures ◽

Wide Range ◽

Trading Agent ◽

Context Aware System ◽

Plan Activity ◽

And Robotics

The AAAI-13 Workshop Program, a part of the 27th AAAI Conference on Artificial Intelligence, was held Sunday and Monday, July 14‚Äì15, 2013 at the Hyatt Regency Bellevue Hotel in Bellevue, Washington, USA. The program included 12 workshops covering a wide range of topics in artificial intelligence, including Activity Context-Aware System Architectures (WS-13-05); Artificial Intelligence and Robotics Methods in Computational Biology (WS-13-06); Combining Constraint Solving with Mining and Learning (WS-13-07); Computer Poker and Imperfect Information (WS-13-08); Expanding the Boundaries of Health Informatics Using Artificial Intelligence (WS-13-09); Intelligent Robotic Systems (WS-13-10); Intelligent Techniques for Web Personalization and Recommendation (WS-13-11); Learning Rich Representations from Low-Level Sensors (WS-13-12); Plan, Activity, and Intent Recognition (WS-13-13); Space, Time, and Ambient Intelligence (WS-13-14); Trading Agent Design and Analysis (WS-13-15); and Statistical Relational Artificial Intelligence (WS-13-16).

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Reports on the 2015 AAAI Workshop Program

AI Magazine ◽

10.1609/aimag.v36i2.2590 ◽

2015 ◽

Vol 36 (2) ◽

pp. 90-101

Author(s):

Stefano V. Albrecht ◽

J. Christopher Beck ◽

David L. Buckeridge ◽

Adi Botea ◽

Cornelia Caragea ◽

...

Keyword(s):

Artificial Intelligence ◽

Imperfect Information ◽

Autonomous Robots ◽

Turing Test ◽

Assistive Technologies ◽

General Competency ◽

Computational Sustainability ◽

Wide Range ◽

Algorithm Configuration ◽

And Behavior

AAAI's 2015 Workshop Program was held Sunday and Monday, January 25–26, 2015 at the Hyatt Regency Austin Hotel in Austion, Texas, USA. The AAAI-15 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. Most workshops were held on a single day. The titles of the workshops included AI and Ethics, AI for Cities, AI for Transportation: Advice, Interactivity and Actor Modeling, Algorithm Configuration, Artificial Intelligence Applied to Assistive Technologies and Smart Environments, Beyond the Turing Test, Computational Sustainability, Computer Poker and Imperfect Information, Incentive and Trust in E-Communities, Multiagent Interaction without Prior Coordination, Planning, Search, and Optimization, Scholarly Big Data: AI Perspectives, Challenges, and Ideas, Trajectory-Based Behaviour Analytics, World Wide Web and Public Health Intelligence, Knowledge, Skill, and Behavior Transfer in Autonomous Robots, and Learning for General Competency in Video Games.

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Reports of the AAAI 2014 Conference Workshops

AI Magazine ◽

10.1609/aimag.v36i1.2575 ◽

2015 ◽

Vol 36 (1) ◽

pp. 87-98

Author(s):

Stefano V. Albrecht ◽

André M. S. Barreto ◽

Darius Braziunas ◽

David L. Buckeridge ◽

Heriberto Cuayáhuitl ◽

...

Keyword(s):

Artificial Intelligence ◽

Imperfect Information ◽

Open Data ◽

Assistive Technologies ◽

Interactive Systems ◽

Quebec City ◽

Cognitive Computing ◽

Information Discovery ◽

Sequential Decision ◽

Wide Range

The AAAI-14 Workshop program was held Sunday and Monday, July 27–28, 2012, at the Québec City Convention Centre in Québec, Canada. Canada. The AAAI-14 workshop program included fifteen workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were AI and Robotics; Artificial Intelligence Applied to Assistive Technologies and Smart Environments; Cognitive Computing for Augmented Human Intelligence; Computer Poker and Imperfect Information; Discovery Informatics; Incentives and Trust in Electronic Communities; Intelligent Cinematography and Editing; Machine Learning for Interactive Systems: Bridging the Gap between Perception, Action and Communication; Modern Artificial Intelligence for Health Analytics; Multiagent Interaction without Prior Coordination; Multidisciplinary Workshop on Advances in Preference Handling; Semantic Cities — Beyond Open Data to Models, Standards and Reasoning; Sequential Decision Making with Big Data; Statistical Relational AI; and The World Wide Web and Public Health Intelligence. This article presents short summaries of those events.

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PenQuest: a gamified attacker/defender meta model for cyber security assessment and education

Journal of Computer Virology and Hacking Techniques ◽

10.1007/s11416-019-00342-x ◽

2019 ◽

Vol 16 (1) ◽

pp. 19-61

Author(s):

Robert Luh ◽

Marlies Temper ◽

Simon Tjoa ◽

Sebastian Schrittwieser ◽

Helge Janicke

Keyword(s):

Information Security ◽

Cyber Security ◽

Imperfect Information ◽

Security Assessment ◽

Meta Model ◽

Organizational Controls ◽

Semantic Data ◽

Education Environment ◽

It Systems ◽

Wide Range

AbstractAttacks on IT systems are a rising threat against the confidentiality, integrity, and availability of critical information and infrastructures. At the same time, the complex interplay of attack techniques and possible countermeasures makes it difficult to appropriately plan, implement, and evaluate an organization’s defense. More often than not, the worlds of technical threats and organizational controls remain disjunct. In this article, we introduce PenQuest, a meta model designed to present a complete view on information system attacks and their mitigation while providing a tool for both semantic data enrichment and security education. PenQuest simulates time-enabled attacker/defender behavior as part of a dynamic, imperfect information multi-player game that derives significant parts of its ruleset from established information security sources such as STIX, CAPEC, CVE/CWE and NIST SP 800-53. Attack patterns, vulnerabilities, and mitigating controls are mapped to counterpart strategies and concrete actions through practical, data-centric mechanisms. The gamified model considers and defines a wide range of actors, assets, and actions, thereby enabling the assessment of cyber risks while giving technical experts the opportunity to explore specific attack scenarios in the context of an abstracted IT infrastructure. We implemented PenQuest as a physical serious game prototype and successfully tested it in a higher education environment. Additional expert interviews helped evaluate the model’s applicability to information security scenarios.

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AI-based anomaly detection for cyberattacks on Windows systems - Creation of a prototype for automated monitoring of the process environment

Electronic Imaging ◽

10.2352/issn.2470-1173.2020.3.mobmu-304 ◽

2020 ◽

Vol 2020 (3) ◽

pp. 331-1-331-13

Author(s):

Benjamin Yüksel ◽

Klaus Schwarz ◽

Reiner Creutzburg

Keyword(s):

Artificial Intelligence ◽

Anomaly Detection ◽

Cyber Security ◽

Secret Data ◽

Security Vulnerabilities ◽

Modern Computer ◽

Wide Range ◽

Software And Hardware ◽

Attack Surface ◽

And Control

Cyber security has become an increasingly important topic in recent years. The increasing popularity of systems and devices such as computers, servers, smartphones, tablets and smart home devices is causing a rapidly increasing attack surface. In addition, there are a variety of security vulnerabilities in software and hardware that make the security situation more complex and unclear. Many of these systems and devices also process personal or secret data and control critical processes in the industry. The need for security is tremendously high. The owners and administrators of modern computer systems are often overwhelmed with the task of securing their systems as the systems become more complex and the attack methods increasingly intelligent. In these days a there are a lot of encryption and hiding techniques available. They are used to make the detection of malicious software with signature based scanning methods very difficult. Therefore, novel methods for the detection of such threats are necessary. This paper examines whether cyber threats can be detected using modern artificial intelligence methods. We develop, describe and test a prototype for windows systems based on neural networks. In particular, an anomaly detection based on autoencoders is used. As this approach has shown, it is possible to detect a wide range of threats using artificial intelligence. Based on the approach in this work, this research topic should be continued to be investigated. Especially cloud-based solutions based on this principle seem to be very promising to protect against modern threats in the world of cyber security.

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Quantum Go Machine

10.21203/rs.3.rs-94303/v1 ◽

2020 ◽

Author(s):

Lu-Feng Qiao ◽

Jun Gao ◽

Zhi-Qiang Jiao ◽

Zhe-Yong Zhang ◽

Zhu Cao ◽

...

Keyword(s):

Artificial Intelligence ◽

Time Series ◽

Imperfect Information ◽

Quantum Physics ◽

Time Series Data ◽

Single Point ◽

Series Data ◽

Polarization Degree ◽

Classical Counterpart ◽

Wide Range

Abstract Go has long been considered as a testbed for artificial intelligence. By introducing certain quantum features, such as superposition and collapse of wavefunction, we experimentally demonstrate a quantum version of Go by using correlated photon pairs entangled in polarization degree of freedom. The total dimension of Hilbert space of the generated states grows exponentially as two players take turns to place the stones in time series. As nondeterministic and imperfect information games are more difficult to solve using nowadays technology, we excitedly find that the inherent randomness in quantum physics can bring the game nondeterministic trait, which does not exist in the classical counterpart. Some quantum resources, like coherence or entanglement, can also be encoded to represent the state of quantum stones. Adjusting the quantum resource may vary the average imperfect information (as comparison classical Go is a perfect information game) of a single game. We further verify its non-deterministic feature by showing the unpredictability of the time series data obtained from different classes of quantum state. Finally, by comparing quantum Go with a few typical games that are widely studied in artificial intelligence, we find that quantum Go can cover a wide range of game difficulties rather than a single point. Our results establish a paradigm of inventing new games with quantum-enabled difficulties by harnessing inherent quantum features and resources, and provide a versatile platform for the test of new algorithms to both classical and quantum machine learning.

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Reports of the AAAI 2010 Conference Workshops

AI Magazine ◽

10.1609/aimag.v31i4.2318 ◽

2010 ◽

Vol 31 (4) ◽

pp. 95

Author(s):

David W. Aha ◽

Mark Boddy ◽

Vadim Bulitko ◽

Artur S. D'Avila Garcez ◽

Prashant Doshi ◽

...

Keyword(s):

Artificial Intelligence ◽

Game Theory ◽

Social Systems ◽

Visual Representations ◽

Intent Recognition ◽

Systems Model ◽

Symbolic Learning ◽

Wide Range ◽

Intelligent Security ◽

Plan Activity

The AAAI-10 Workshop program was held Sunday and Monday, July 11–12, 2010 at the Westin Peachtree Plaza in Atlanta, Georgia. The AAAI-10 workshop program included 13 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were AI and Fun, Bridging the Gap between Task and Motion Planning, Collaboratively-Built Knowledge Sources and Artificial Intelligence, Goal-Directed Autonomy, Intelligent Security, Interactive Decision Theory and Game Theory, Metacognition for Robust Social Systems, Model Checking and Artificial Intelligence, Neural-Symbolic Learning and Reasoning, Plan, Activity, and Intent Recognition, Statistical Relational AI, Visual Representations and Reasoning, and Abstraction, Reformulation, and Approximation. This article presents short summaries of those events.

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A Survey on Artificial Intelligence Techniques to Prevent Cyber Crime

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v8i5.669 ◽

2018 ◽

Vol 8 (5) ◽

pp. 80

Author(s):

Juveriya Afreen

Keyword(s):

Artificial Intelligence ◽

Cyber Security ◽

Data Security ◽

Human Reasoning ◽

Cyber Crime ◽

Artificial Intelligence Techniques

Abstract-- With increase in complexity of data, security, it is difficult for the individuals to prevent the offence. Thus, by using any automation or software it’s not possible by only using huge fixed algorithms to overcome this. Thus, we need to look for something which is robust and feasible enough. Hence AI plays an epitome role to defense such violations. In this paper we basically look how human reasoning along with AI can be applied to uplift cyber security.

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