Comparative Assessment of Process Mining for Supporting IoT Predictive Security

[1]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[2]  D. Pham,et al.  Statistical approach to normalization of feature vectors and clustering of mixed datasets , 2012, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[3]  Emin Anarim,et al.  An intelligent intrusion detection system (IDS) for anomaly and misuse detection in computer networks , 2005, Expert Syst. Appl..

[4]  Lionel Roucoules,et al.  On the Use of Process Mining and Machine Learning to Support Decision Making in Systems Design , 2016, PLM.

[5]  Jacques Wainer,et al.  Anomaly Detection Using Process Mining , 2009, BMMDS/EMMSAD.

[6]  Wil M. P. van der Aalst,et al.  Process Mining - Discovery, Conformance and Enhancement of Business Processes , 2011 .

[7]  Elisa Bertino,et al.  A Data Driven Approach for the Science of Cyber Security: Challenges and Directions , 2016, 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI).

[8]  Maël Chiapino,et al.  One Class Splitting Criteria for Random Forests , 2016, ACML.

[9]  Alessandro Bassi,et al.  Enabling Things to Talk: Designing IoT solutions with the IoT Architectural Reference Model , 2013 .

[10]  B. B. Zaidan,et al.  A review of smart home applications based on Internet of Things , 2017, J. Netw. Comput. Appl..

[11]  Yi Zhou,et al.  Understanding the Mirai Botnet , 2017, USENIX Security Symposium.

[12]  Marc-Oliver Pahl,et al.  Securing IoT microservices with certificates , 2018, NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium.

[13]  Chong Kuan Chen,et al.  IoT Security: Ongoing Challenges and Research Opportunities , 2014, 2014 IEEE 7th International Conference on Service-Oriented Computing and Applications.

[14]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[15]  Markus Hofmann,et al.  RapidMiner: Data Mining Use Cases and Business Analytics Applications , 2013 .

[16]  Elisa Bertino,et al.  Botnets and Internet of Things Security , 2017, Computer.

[17]  Milos Prvulovic,et al.  Syndrome: Spectral analysis for anomaly detection on medical IoT and embedded devices , 2018, 2018 IEEE International Symposium on Hardware Oriented Security and Trust (HOST).

[18]  Hans-Peter Kriegel,et al.  LOF: identifying density-based local outliers , 2000, SIGMOD '00.

[19]  M. Debruyne,et al.  Minimum covariance determinant , 2010 .

[20]  Charu C. Aggarwal,et al.  Outlier Analysis , 2013, Springer New York.

[21]  Seref Sagiroglu,et al.  Big data analytics for network anomaly detection from netflow data , 2017, 2017 International Conference on Computer Science and Engineering (UBMK).

[22]  Bernhard Schölkopf,et al.  Estimating the Support of a High-Dimensional Distribution , 2001, Neural Computation.

[23]  Georgios Kambourakis,et al.  DDoS in the IoT: Mirai and Other Botnets , 2017, Computer.

[24]  Lovekesh Vig,et al.  Anomaly detection in ECG time signals via deep long short-term memory networks , 2015, 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

[25]  Amit P. Sheth,et al.  Machine learning for Internet of Things data analysis: A survey , 2017, Digit. Commun. Networks.

[26]  Jiujun Cheng,et al.  Research on the Matthews Correlation Coefficients Metrics of Personalized Recommendation Algorithm Evaluation , 2015 .

[27]  Sander J. J. Leemans,et al.  Scalable Process Discovery with Guarantees , 2015, BMMDS/EMMSAD.

[28]  Isabelle Chrisment,et al.  A Process Mining Approach for Supporting IoT Predictive Security , 2020, NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium.

[29]  James B. Fraley,et al.  The promise of machine learning in cybersecurity , 2017, SoutheastCon 2017.

[30]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[31]  Soma Bandyopadhyay,et al.  IoT Healthcare Analytics: The Importance of Anomaly Detection , 2016, 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA).

[32]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[33]  José Hernández-Orallo,et al.  An experimental comparison of performance measures for classification , 2009, Pattern Recognit. Lett..

[34]  Karuna Pande Joshi,et al.  Anomaly Detection Models for Smart Home Security , 2019, 2019 IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS).

[35]  Katrien van Driessen,et al.  A Fast Algorithm for the Minimum Covariance Determinant Estimator , 1999, Technometrics.

[36]  Zhi-Hua Zhou,et al.  Isolation Forest , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[37]  Jérôme François,et al.  A Universal Controller to Take Over a Z-Wave Network , 2017 .

[38]  Juergen Jasperneite,et al.  The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0 , 2017, IEEE Industrial Electronics Magazine.

[39]  Remi Badonnel,et al.  A Taxonomy of Attacks in RPL-based Internet of Things , 2016, Int. J. Netw. Secur..

[40]  Víctor A. Villagrá,et al.  Real-Time Multistep Attack Prediction Based on Hidden Markov Models , 2020, IEEE Transactions on Dependable and Secure Computing.