{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T04:19:35Z","timestamp":1750997975299,"version":"3.41.0"},"reference-count":75,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,7]]},"DOI":"10.1109\/icci-cc.2017.8109765","type":"proceedings-article","created":{"date-parts":[[2017,11,16]],"date-time":"2017-11-16T21:49:41Z","timestamp":1510868981000},"page":"297-308","source":"Crossref","is-referenced-by-count":7,"title":["Fractal based cognitive neural network to detect obfuscated and indistinguishable internet threats"],"prefix":"10.1109","author":[{"given":"Sana","family":"Siddiqui","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad Salman","family":"Khan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ken","family":"Ferens","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Witold","family":"Kinsner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref73","article-title":"Estimation of high dimensional mean regression in the absence of symmetry and light tail assumptions","author":"jianqing","year":"2016","journal-title":"Royal Statistical Society Series B (Statistical Methodology)"},{"key":"ref72","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1287\/moor.23.1.145","article-title":"Heavy tails and long range dependence in on\/off processes and associated fluid models","volume":"23","author":"david","year":"1998","journal-title":"Mathematics of Operations Research"},{"key":"ref71","doi-asserted-by":"crossref","DOI":"10.1142\/S0219525911003451","article-title":"The dynamics of internet traffic: self-similarity, self-organization, and complex phenomena","volume":"14","author":"smith","year":"2011","journal-title":"Advances in Complex Systems"},{"key":"ref70","first-page":"173","article-title":"An approach for characterising Heavy-Tailed internet traffic based on EDF statistics","author":"karim","year":"2009","journal-title":"Intelligent Engineering Systems and Computational Cybernetics"},{"key":"ref74","article-title":"Robust and Effective Malware Detection Through Quantitative Data Flow Graph Metrics","author":"tobias","year":"2015","journal-title":"proc of the Intl Conference on Detection of Intrusions and Malware"},{"journal-title":"Transfer Function Graphs","year":"0","key":"ref39"},{"key":"ref75","article-title":"Can machine learning be secure?","author":"marco","year":"2006","journal-title":"ACM Symp on Information Computer and Communications Security"},{"journal-title":"Generative Design Visualize Program and Create with Processing","year":"2012","author":"hartmut","key":"ref38"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1143\/ptp\/89.5.965","article-title":"Fractal Neural Network","volume":"89","author":"eung-soo","year":"1993","journal-title":"Progress of Theoretical Physics"},{"key":"ref32","first-page":"145","article-title":"Recurrent fractal neural networks: A strategy for the exchange of local and global information processing in the brain","volume":"66","author":"erhard","year":"2002","journal-title":"Elsevier"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-25646-2_43"},{"key":"ref30","article-title":"A fractal Radial Basis Function neural net For modelling","author":"murray-smith","year":"1992","journal-title":"proc of Intl Conferece on Automation Robotics and Computer Vision"},{"journal-title":"The Nature of Code Simulating Natural Systems with Processing","year":"2012","author":"daniel","key":"ref37"},{"journal-title":"Neural Networks A Systematic Introduction","year":"1996","author":"raul","key":"ref36"},{"key":"ref35","article-title":"Graduate Level Course on Data Mining (MIT Course Number 15.062) - Lecture 6 Artificial Neural Networks","author":"nitin","year":"2013","journal-title":"MIT Open Courseware"},{"key":"ref34","article-title":"Neural Network Primer: Part","author":"maureen","year":"1989","journal-title":"AI Expert"},{"key":"ref60","doi-asserted-by":"crossref","first-page":"17","DOI":"10.4018\/IJSSCI.2015070102","article-title":"Multifractal singularity spectrum for cognitive cyber defence in internet time series","volume":"7","author":"muhammad","year":"2015","journal-title":"International Journal of Software Science and Computational Intelligence (IJSSCI)"},{"key":"ref62","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1162\/evco.2009.17.3.275","article-title":"Evolutionary undersampling for classification with imbalanced datasets: Proposals and taxonomy","volume":"17","author":"salvador","year":"2009","journal-title":"Evolutionary Computation"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2006.17"},{"key":"ref63","article-title":"ADFA-NB15-Datasets - UNSW-NB15 Network Packets and Flows Captures","author":"nour","year":"2014","journal-title":"Cyber Range Lab of the Australian Centre for Cyber Security"},{"key":"ref28","first-page":"489","article-title":"Exploring feature extraction and ELM in malware detection for Android devices","author":"wei","year":"2015","journal-title":"Advances in Neural Networks"},{"key":"ref64","article-title":"UNSW-NB15: A comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set)","author":"nour","year":"0","journal-title":"proc of the IEEE Military Communications and Information Systems Conference (MilCIS)"},{"key":"ref27","article-title":"Learning to detect malicious URLs","volume":"2","author":"justin","year":"2011","journal-title":"ACM Transactions on Intelligent Systems and Technology (TIST)"},{"key":"ref65","first-page":"1","article-title":"The evaluation of network anomaly detection systems: Statistical analysis of the UNSW-NB15 data set and the comparison with the KDD99 data set","author":"nour","year":"2016","journal-title":"information Security Journal A Global Perspective"},{"journal-title":"Imperva","article-title":"Web Attacks: The Biggest Threat to Your Network","year":"2014","key":"ref66"},{"key":"ref29","article-title":"Classifying Android malware through subgraph mining","author":"fabio","year":"2013","journal-title":"proc of the SETOP Workshop SETOP'13"},{"key":"ref67","article-title":"Intelligence-driven computer network defense informed by analysis of adversary campaigns and intrusion kill chains","volume":"1","author":"hutchins","year":"2011","journal-title":"Leading Issues in Information Warfare & Security Research"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(02)00081-8"},{"key":"ref69","article-title":"Evaluation neural networks on selected feature by meta heuristic algorithms","volume":"8","author":"maysam","year":"2016","journal-title":"Artif Intell Syst Mach Learn"},{"key":"ref2","article-title":"Panacea: Automating attack classification for anomaly-based network intrusion detection systems","author":"damiano","year":"2009","journal-title":"Proceedings of International Symposium on Recent Advances in Intrusion Detection (RAID'07)"},{"key":"ref1","article-title":"Countering phishing from brands' vantage point","author":"vlad","year":"2016","journal-title":"proc of the 2016 ACM on International Workshop on Security And Privacy Analytics"},{"key":"ref20","first-page":"943","article-title":"Intrusion Detection with Neural Networks","author":"jake","year":"1998","journal-title":"Advances in Neural Information Processing Systems 10"},{"key":"ref22","article-title":"Improving intrusion detection performance using keyword","author":"lippmann","year":"1999","journal-title":"Proc of the International Symposium on Recent Advances in Intrusion Detection"},{"key":"ref21","article-title":"Network intrusion detection system using neural networks","author":"jimmy","year":"2008","journal-title":"proc of the 4th Intl Conference on Natural Computation"},{"key":"ref24","first-page":"201","article-title":"A performance comparison of different back propagation neural networks methods in computer network intrusion detection","volume":"10","author":"dao","year":"2002","journal-title":"Differential Equations and Dynamical Systems"},{"key":"ref23","article-title":"Artificial neural networks for misdetection","author":"james","year":"1998","journal-title":"In Proceedings of the 1998 National Information System Security Conference"},{"key":"ref26","article-title":"Detecting and classifying attacks in computer networks using feed-forward and Elman neural networks","author":"vicente","year":"2006","journal-title":"proc of the First European Conference on Computer Network Defence"},{"key":"ref25","article-title":"Web spam classification using supervised artifiical neural network algorithms","volume":"2","author":"ashish","year":"2015","journal-title":"Advanced Computational Intelligence An International Journal (ACII)"},{"journal-title":"What size neural network gives optimal generalization? Convergence properties of backpropagation","year":"1996","author":"steve","key":"ref50"},{"journal-title":"Chaos Fractals and Dynamics Computer Experiments in Mathematics","year":"1990","author":"devaney","key":"ref51"},{"key":"ref59","article-title":"Estimating multifractal measures of strange attractors","author":"witold","year":"1996","journal-title":"Proc IEEE Can Conf Electrical Computer Engineering"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2001.941276"},{"key":"ref57","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1007\/978-3-642-16083-7_14","article-title":"System Complexity and Its Measures: How Complex Is Complex","volume":"323","author":"witold","year":"2010","journal-title":"Advances in Cognitive Informatics and Cognitive Computing Studies in Computational Intelligence"},{"journal-title":"proc of the IEEE 8th International Congress on Image and Signal Processing (CISP)","year":"2015","author":"zhenghua","key":"ref56"},{"key":"ref55","article-title":"Using the fractal dimension to cluster datasets","author":"daniel","year":"2000","journal-title":"Proceedings of the International Conference on Knowledge Discovery and Data Mining"},{"key":"ref54","article-title":"A polyscale based autonomous sliding window algorithm for cognitive machine classification of malicious Internet traffic","author":"salman khan","year":"2015","journal-title":"proc of International Conference on Security and Management (SAM‘15) WordComp '15"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/COGINF.2011.6016116"},{"key":"ref52","doi-asserted-by":"crossref","first-page":"26","DOI":"10.4018\/jcini.2007100103","article-title":"A unified approach to fractal dimensions","volume":"1","author":"witold","year":"2007","journal-title":"Journal of Cognitive Informatics and Natural Intelligence"},{"key":"ref10","first-page":"2669","article-title":"Machine learning for computer security","volume":"7","author":"chan","year":"2006","journal-title":"Journal of Machine Learning Research"},{"key":"ref11","article-title":"Machine learning that matters","author":"kiri","year":"2012","journal-title":"Proc 29th Int Conf Mach Learn"},{"key":"ref40","first-page":"918","article-title":"Second-order properties of error surfaces: learning time and generalization","volume":"3","author":"yann","year":"1991","journal-title":"Advances in neural information processing systems"},{"key":"ref12","article-title":"Detecting Advanced Persistent Threats using Fractal Dimension based machine learning classification","author":"sana","year":"2016","journal-title":"proc of the 2016 ACM on International Workshop on Security And Privacy Analytics"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"163","DOI":"10.69554\/UERV9928","article-title":"How is cyber threat evolving and what do organisations need to consider?","volume":"7","author":"martin","year":"2014","journal-title":"Journal of Business Continuity & Emergency Planning"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2011.98"},{"key":"ref15","article-title":"PolyPack: An automated online packing service for optimal antivirus evasion","author":"jon","year":"2009","journal-title":"Proceedings of the 3rd USENIX Conference on Offensive Technologies"},{"key":"ref16","article-title":"Harvesting the low-hanging fruits: Defending against automated large-scale cyber-intrusions by focusing on the vulnerable population","author":"hassan","year":"2016","journal-title":"Proc Workshop New Security Paradigms (NSPW)"},{"key":"ref17","article-title":"Big data classification: problems and challenges in network intrusion prediction with machine learning","author":"shan","year":"2014","journal-title":"Proc of ACM SIGMETRICS Performance Evaluation Review"},{"key":"ref18","article-title":"Types of Machine Learning Algorithms","author":"taiwo","year":"2010","journal-title":"New Advances in Machine Learning"},{"key":"ref19","first-page":"565","article-title":"Detecting cheating aggregators and report dropping attacks in Wireless Sensor Networks","author":"mohit","year":"2012","journal-title":"Wireless Technologies Concepts Methodologies Tools and Applications"},{"key":"ref4","article-title":"AI2: Training a big data machine to defend","author":"kalyan","year":"2016","journal-title":"IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity)"},{"key":"ref3","article-title":"Intrusion detection in enterprise systems by combining and clustering diverse monitor data","author":"atul","year":"2016","journal-title":"proc of the Symposium and Bootcamp on the Science of Security"},{"key":"ref6","article-title":"Computer security and machine learning: Worst enemies or best friends?","author":"konrad","year":"0","journal-title":"proc of the IEEE First SysSec Workshop"},{"key":"ref5","article-title":"Hash Factory: New Cerber Ransomware Morphs Every 15 Seconds","author":"pat","year":"2016","journal-title":"Invincea Labs"},{"key":"ref8","article-title":"Outside the closed world: On using machine learning for network intrusion detection","author":"robin","year":"2010","journal-title":"Proc of the IEEE Symposium on Security and Privacy"},{"key":"ref7","article-title":"Novel approaches in cognitive informatics and natural intelligence","author":"yingxu","year":"2008","journal-title":"International Journal of Cognitive Informatics and Natural Intelligence"},{"journal-title":"Neural Network Design","year":"2014","author":"martin","key":"ref49"},{"journal-title":"The Fractal Geometry of Nature","year":"1982","author":"mandelbrot","key":"ref9"},{"key":"ref46","volume":"1","author":"chris","year":"2011","journal-title":"Pattern Recognition and Machine Learning"},{"key":"ref45","doi-asserted-by":"crossref","first-page":"980","DOI":"10.1016\/j.neucom.2015.06.092","article-title":"Multilayer neural network with multi-valued neurons in time series forecasting of oil production","volume":"175","author":"igor","year":"2016","journal-title":"Neurocomputing"},{"journal-title":"Introduction to Neural Networks for Java","year":"2008","author":"jeff","key":"ref48"},{"key":"ref47","article-title":"Size of multilayer networks for exact learning: analytic approach","volume":"9","author":"paugam-moisy","year":"1997","journal-title":"Advances in neural information processing systems"},{"key":"ref42","volume":"7","author":"daniel","year":"0","journal-title":"Principles of Artificial Neural Networks"},{"key":"ref41","first-page":"9","article-title":"Efficient BackProp","author":"yann","year":"1998","journal-title":"Neural Networks Tricks of the Trade"},{"journal-title":"Backpropagation Theory Architectures and Applications (Developments in Connectionist Theory Series) Psychology Press","year":"1995","author":"yves","key":"ref44"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/707\/1\/012047"}],"event":{"name":"2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","start":{"date-parts":[[2017,7,26]]},"location":"Oxford","end":{"date-parts":[[2017,7,28]]}},"container-title":["2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8100805\/8109722\/08109765.pdf?arnumber=8109765","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T02:57:53Z","timestamp":1750993073000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8109765\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7]]},"references-count":75,"URL":"https:\/\/doi.org\/10.1109\/icci-cc.2017.8109765","relation":{},"subject":[],"published":{"date-parts":[[2017,7]]}}}