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A Comparison of Genetic Programming and Look-up Table Learning for the Game of Spoof

Mark Wittkamp, Luigi Barone, Lyndon While
2007 2007 IEEE Symposium on Computational Intelligence and Games  
We compare a genetic programming approach with a look-up table based approach, contrasting the performance of each in different scenarios of the game.  ...  In this paper, we compare two learning techniques for strategy development in the game of Spoof, a simple guessing game of imperfect information.  ...  In Section III, we introduce our adaptive approaches for building computer Spoof players through genetic programming and look-up table learning.  ... 
doi:10.1109/cig.2007.368080 dblp:conf/cig/WittkampBW07 fatcat:fznx473gi5gwdmn3tmzrlfnlv4

Deep Learning in the Wild [article]

Thilo Stadelmann, Mohammadreza Amirian and Ismail Arabaci, Marek Arnold, Gilbert François Duivesteijn, Ismail Elezi, Melanie Geiger and Stefan Lörwald and Benjamin Bruno Meier, Katharina Rombach, Lukas Tuggener
2018 arXiv   pre-print
It thus fills a gap between the publication of latest algorithmic and methodical developments, and the usually omitted nitty-gritty of how to make them work.  ...  Deep learning with neural networks is applied by an increasing number of people outside of classic research environments, due to the vast success of the methodology on a wide range of machine perception  ...  Acknowledgements We are grateful for the invitation by the ANNPR chairs and the support of our business partners in Innosuisse grants 17719.1 "PANOPTES", 17963.1 "DeepScore", 25256.1 "Libra", 25335.1 "  ... 
arXiv:1807.04950v1 fatcat:6cb63xget5fynmjxrhzcpirvii

Deep Learning in the Wild [chapter]

Thilo Stadelmann, Mohammadreza Amirian, Ismail Arabaci, Marek Arnold, Gilbert François Duivesteijn, Ismail Elezi, Melanie Geiger, Stefan Lörwald, Benjamin Bruno Meier, Katharina Rombach, Lukas Tuggener
2018 Lecture Notes in Computer Science  
It thus fills a gap between the publication of latest algorithmic and methodical developments, and the usually omitted nitty-gritty of how to make them work.  ...  Deep learning with neural networks is applied by an increasing number of people outside of classic research environments, due to the vast success of the methodology on a wide range of machine perception  ...  Acknowledgements We are grateful for the invitation by the ANNPR chairs and the support of our business partners in Innosuisse grants 17719.1 "PANOPTES", 17963.1 "DeepScore", 25256.1 "Libra", 25335.1 "  ... 
doi:10.1007/978-3-319-99978-4_2 fatcat:gmpuuzlio5ea3ck75fekk3ab7y

Distributed Denial-of-Service (DDoS) Attacks and Defence Mechanisms in Various Web-enabled Computing Platforms

2022 International Journal on Semantic Web and Information Systems (IJSWIS)  
The attackers protect their anonymity by infecting distributed devices and utilizing them to create a bot army to constitute a large-scale attack.  ...  The demand for Internet security has escalated in the last two decades because the rapid proliferation in the number of Internet users has presented attackers with new detrimental opportunities.  ...  Table 5 presents a comparison of multiple DDoS defense approaches that utilize machine learning algorithms along with their strengths and weaknesses.  ... 
doi:10.4018/ijswis.297143 fatcat:imoau72665dxbmfdoxvntbyyiq

Recent Advancements in Intrusion Detection Systems for the Internet of Things

Zeeshan Ali Khan, Peter Herrmann
2019 Security and Communication Networks  
Besides looking on approaches developed particularly for IoT, we introduce also work for the three similar network types mentioned above and discuss if they are also suitable for IoT systems.  ...  Often, the limited processing resources do not allow the use of standard security mechanisms on the nodes, making IoT applications quite vulnerable to different types of attacks.  ...  Conflicts of Interest The authors declare that there are no conflicts of interest regarding the publication of this paper.  ... 
doi:10.1155/2019/4301409 fatcat:qupk6elzcvbkrarqf25epmjdci

A Survey on Machine-Learning Techniques for UAV-Based Communications

Petros S Bithas, Emmanouel T Michailidis, Nikolaos Nomikos, Demosthenes Vouyioukas, Athanasios G Kanatas
2019 Sensors  
In this context, the machine-learning (ML) framework is expected to provide solutions for the various problems that have already been identified when UAVs are used for communication purposes.  ...  In this article, we provide a detailed survey of all relevant research works, in which ML techniques have been used on UAV-based communications for improving various design and functional aspects such  ...  So, an ESN-based DRL framework for online UAV trajectory optimization is presented and a noncooperative game is formulated consisting of the UAVs as the players and having the objective of learning their  ... 
doi:10.3390/s19235170 pmid:31779133 pmcid:PMC6929112 fatcat:pnur7lmpj5bj7poebmdfpd6bhi

Foreword of Special Issue on "Nomadic Services and Applications"

Jason C. Hung
2011 Journal of Networks  
a) The result of first method A program is designed to carry out ARP Spoofing and DNS Spoofing. With the OpenSSL library, two modules are designed to tamper certificate and forward SSL data.  ...  In addition, the design of the users a high participation rate of the game and learning.  ... 
doi:10.4304/jnw.6.5.687-688 fatcat:3qws6kqycnffxnh6n6th6ioc5a

Survey on synchrophasor data quality and cybersecurity challenges, and evaluation of their interdependencies

Aditya SUNDARARAJAN, Tanwir KHAN, Amir MOGHADASI, Arif I. SARWAT
2018 Journal of Modern Power Systems and Clean Energy  
This paper conducts a comprehensive review of quality and cybersecurity challenges for synchrophasors, and identifies the interdependencies between them.  ...  In doing so, this paper serves as a starting point for researchers entering the fields of synchrophasor data analytics and security.  ...  More recent solutions include game theory, machine learning, proactive data visualization, and defense-indepth [12, 123] .  ... 
doi:10.1007/s40565-018-0473-6 fatcat:sw5vt7jdvjc3jml7ylpx3kp2ja

INTRUSION DETECTION SYSTEMS: A REVIEW

D. Ashok Kumar
2017 International Journal of Advanced Research in Computer Science  
the Intrusion Detection System (IDS) and to develop a morphological framework for IDS for easy understanding.  ...  Given the exponential growth of Internet and increased availability of bandwidth, Intrusion Detection has become the critical component of Information Security and the importance of secure networks has  ...  Learning Rule for Anomaly Detection (LERAD): This uses a rule based learning algorithm to pick up good rules rather than fixed set of rules and it is first method to characterize the normal behaviour in  ... 
doi:10.26483/ijarcs.v8i8.4703 fatcat:gbd4sfehwjd6vktthnlp7jfhoa

Opponent modeling and exploitation in poker using evolved recurrent neural networks

Xun Li, Risto Miikkulainen
2018 Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '18  
Empirical game-theoretic analysis showed that spoofing can be profitable in a market with heuristic belief learning traders.  ...  As the game proceeds, five cards are dealt face up on the table. Each of them is a community card, and the set of community cards is called the board.  ... 
doi:10.1145/3205455.3205589 dblp:conf/gecco/LiM18 fatcat:z66onqk6xjfdtk7url4fjssa54

Some Research Problems in Biometrics: The Future Beckons [article]

Arun Ross, Sudipta Banerjee, Cunjian Chen, Anurag Chowdhury, Vahid Mirjalili, Renu Sharma, Thomas Swearingen, Shivangi Yadav
2019 arXiv   pre-print
The need for reliably determining the identity of a person is critical in a number of different domains ranging from personal smartphones to border security; from autonomous vehicles to e-voting; from  ...  Biometrics, which entails the use of biological attributes such as face, fingerprints and voice for recognizing a person, is being increasingly used in several such applications.  ...  , such as India's Unique ID program that uses face, fingerprint and iris; (c) development of robust matching techniques for various biometric modalities based on Deep Learning; (d) investigation of previously  ... 
arXiv:1905.04717v1 fatcat:n6q2a7oa6jckzd4cinpph5xebm

SoK: Applying Machine Learning in Security - A Survey [article]

Heju Jiang, Jasvir Nagra, Parvez Ahammad
2016 arXiv   pre-print
Based on our survey, we also suggest a point of view that treats security as a game theory problem instead of a batch-trained ML problem.  ...  The idea of applying machine learning(ML) to solve problems in security domains is almost 3 decades old.  ...  We emphasize a position which treats security as a game theory problem.  ... 
arXiv:1611.03186v1 fatcat:hfvc5hhu7ze77lrnjufslcg6gm

Are Self-Driving Vehicles Ready to Launch? An Insight into Steering Control in Autonomous Self-Driving Vehicles

Marya Rasib, Muhammad Atif Butt, Shehzad Khalid, Samia Abid, Faisal Raiz, Sohail Jabbar, Kijun Han, Mehmet Cunkas
2021 Mathematical Problems in Engineering  
In this regard, we present a comprehensive study considering the evolution of steering control methods for self-driving vehicles.  ...  To the best of our knowledge, currently, there is no taxonomy available, which elaborates steering control methods for self-driving vehicles.  ...  (c) Dynamic programming Nonmodel-based adaptive dynamic programming (ADP) enabled steering control methods are also motivated by control, biological learning, and enhanced learning.  ... 
doi:10.1155/2021/6639169 fatcat:btneip645ra4denpv2trdddnui

MAINTAINING CLOUD PERFORMANCE UNDER DDOS ATTACKS

Moataz H. Khalil, Mohamed Azab, Ashraf Elsayed, Walaa Sheta, Mahmoud Gabr, Adel S. Elmaghraby
2019 Zenodo  
The results show the great effect of the MLD to reduce the energy consumption and the overall SLA violation for all datasets.  ...  This paper proposes a Multiple Layer Defense (MLD) scheme to detect and mitigate DDoS attacks which due to resource depletion. The MLD consists of two layers.  ...  The main reason is that the VM of the DDoS attacks is looking for free provisions for hosting. If there are no free allowances, an inactive host wakes up.  ... 
doi:10.5281/zenodo.3564217 fatcat:kucix7m4hjbn7danh3tlo4arca

A Comprehensive Survey for Intelligent Spam Email Detection

Asif Karim, Sami Azam, Bharanidharan Shanmugam, Krishnan Kannoorpatti, Mamoun Alazab
2019 IEEE Access  
This survey paper describes a focused literature survey of Artificial Intelligence (AI) and Machine Learning (ML) methods for intelligent spam email detection, which we believe can help in developing appropriate  ...  like email and IP address of each sender and recipient of where the email originated and what stopovers, and final destination.  ...  Although the sample in Table 7 shows disproportionate number of research works for these two types of methods in comparison to supervised learning, but the following Scatterplots and Standard Deviation  ... 
doi:10.1109/access.2019.2954791 fatcat:ikt6cayggbb2dkrm52fxzz2dqm
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