Katrin Franke
Bakgrunn og aktiviteter
Katrin Franke er professor i computer science ved informasjonssikkerhetsmiljøet på NTNU i Gjøvik. I 2007 ble hun en del av Norwegian Information Security Lab (NISlab) med oppdrag å etablere forskning og utdanning i "digital og computational forensics". I denne sammenheng deltok hun i å sette opp samarbeidet med det norske politiet som en del av Center for Cyber and information Security (CCIS). Dr. Franke koordinerer nå NTNU Digital Forensics-gruppen. Dr. Franke har 20+ års erfaring i industriell forskning og utvikling for finansielle tjenester og politietater (Law Enforcement Agencies - LEAs) og hun samarbeider tett med banker og LEAs i Europa, Nord -Amerika og Asia.
Emner
- IMT4210 - Computational Forensics
- IMT6101 - Computational Intelligence
- IMT4205 - Research Project Planning
- IMT4905 - Experience-based Master's Thesis
- IMT6091 - Computational Forensics
Vitenskapelig, faglig og kunstnerisk arbeid
Et utvalg av nyere tidsskriftspublikasjoner, kunstneriske produksjoner, bok, inklusiv bokdeler og rapport-del. Se alle publikasjoner i databasen
Tidsskriftspublikasjoner
- (2021) Reliability validation for file system interpretation. Forensic Science International: Digital Investigation. vol. 37.
- (2021) Coffee forensics — Reconstructing data in IoT devices running Contiki OS. Forensic Science International: Digital Investigation. vol. 37.
- (2020) Generic Metadata Time Carving. Forensic Science International: Digital Investigation. vol. 33.
- (2019) The impact of preprocessing in natural language for open source intelligence and criminal investigation. TEMP 2017 IEEE International Conference on Big Data (Big Data).
- (2018) Comparing Open Source Search Engine Functionality, Efficiency and Effectiveness with Respect to Digital Forensic Search. Norsk Informasjonssikkerhetskonferanse (NISK). vol. 11.
- (2018) Identifying Central Individuals in Organised Criminal Groups and Underground Marketplaces. Lecture Notes in Computer Science (LNCS). vol. 10862 LNCS.
- (2017) Feasibility Study of Social Network Analysis on Loosely Structured Communication Networks. Procedia Computer Science. vol. 108.
- (2017) Big data analytics by automated generation of fuzzy rules for Network Forensics Readiness. Applied Soft Computing. vol. 52.
- (2016) Data-driven Approach to Information Sharing using Data Fusion and Machine Learning for Intrusion Detection. Norsk Informasjonssikkerhetskonferanse (NISK). vol. 2016.
- (2016) Memory access patterns for malware detection. Norsk Informasjonssikkerhetskonferanse (NISK). vol. 2016.
- (2016) Intelligent generation of fuzzy rules for network firewalls based on the analysis of large-scale network traffic dumps. International Journal of Hybrid Intelligent Systems. vol. 13 (3-4).
- (2016) Multinomial classification of web attacks using improved fuzzy rules learning by Neuro-Fuzzy. International Journal of Hybrid Intelligent Systems. vol. 13 (1).
- (2016) Malware Beaconing Detection by Mining Large-scale DNS Logs for Targeted Attack Identification. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering. vol. 10 (4).
- (2014) Practical use of Approximate Hash Based Matching in digital investigations. Digital Investigation. The International Journal of Digital Forensics and Incident Response. vol. 11 (May).
- (2013) Enhancing the effectiveness of Web Application Firewalls by generic feature selection. Logic Journal of the IGPL. vol. 21 (4).
- (2012) Clustering Document Fragments using Background Color and Texture Information. Proceedings of SPIE, the International Society for Optical Engineering. vol. 8297.
- (2012) Combining expert knowledge with automatic feature extraction for reliable web attack detection. Security and Communication Networks.
- (2011) Improving Effectiveness of Intrusion Detection by Correlation Feature Selection. International Journal on Mobile Computing and Multimedia Communications. vol. 3 (1).
- (2011) On General Definition of L1-norm Support Vector Machines for Feature Selection. International Journal of Machine Learning and Computing. vol. 1 (3).
- (2009) A New Two-Stage Search Procedure for Misuse Detection. International Journal of Security and Its Applications. vol. 3 (3).