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| Dato | Tittel | Foreleser | Emne | |
|---|---|---|---|---|
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14. september 2018 Kl. 12.12 60 min A153 |
CyberAIMs We hardly pass any day without hearing of a new cyber attack. The recent ever-increasing occurrence of such attacks has given to researchers, practitioners and others an opportunity to raise awareness and train staff from the public and private institutions, as well as other people within the society, while there seems to be a gap between what companies and institutions plan to do when developing their internal policies regarding information security and what it should be done according to a system perspective in this area. Our task as researchers is to bridge this gap by offering potential solutions. The first aim of our work is to promote the usage of a socio-technical systems (STS) approach to support the emerging role of systems thinking in cyber security education using simulation as a supporting tool for the learning. A secondary aim of this work is to include the tool within the Norwegian Cyber Range (NCR) exercise toolkit. As a first step, we are introducing the CyberAIMs tool, which stands for Cyber Agents’ Interactive Modeling and Simulation tool. We designed this agent-based simulation tool so as to use it as an educational tool for Master students in a Cyber security course. The experiment is still in progress with preliminary data indicating a shift in students' perspective, that could be related to both adversarial and systems thinking processes. In the next stage, we intend to extend our intended users by including target groups who need training in adversarial and systems thinking, especially in the critical infrastructure sectors. |
Erjon Zoto | NISseminar |
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20. oktober 2017 Kl. 12.12 55 min A146 |
Pankaj Shivdayal Wasnik | NISseminar | |
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6. oktober 2017 Kl. 12.12 55 min A146 |
Advancing Neuro-Fuzzy Algorithm for Automated Classification in Large-scale Forensic and Cybercrime Investigations Abstract: Big Data is a reality and Cyber Crime Investigators are confronted with the amount and complexity of seized digital data in criminal cases. Human experts are sitting in the Court of Law and making decisions with respect to found evidences that are being presented. Therefore, there is a strong need to bridge data processing and automated analysis for providing human-understandable representation of evidences. There is a history of successful applications of Machine Learning methods in Digital Forensics such that Artificial Neural Networks, Support Vector Machines and Bayes Network. However, the challenge is that such methods neither provide human-explainable models nor can work without prior knowledge required for inference and data representation. In this work Andrii focuses on Neuro-Fuzzy, a Hybrid Intelligence method that is capable of connecting two worlds: Computational Intelligence and Digital Forensics. CV: Andrii Shalaginov received his Master Degree from the Gjøvik University College in 2013 and also holds his degree from the National Technical University of Ukraine “Kyiv Polytechnic Institute” - Department of Computer Aided Design. Before studying at HiG he had an industry experience, including Samsung R&D center in Kiev. He joined NTNU Digital Group as a PhD student with the research topic related to application of soft computing in digital forensics. Andrii also has extensive knowledge in malware analysis and machine learning. |
Andrii Shalaginov | NISseminar |
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22. september 2017 Kl. 12.12 55 min A146 |
Speeding-up K-means clustering Modern Intrusion Detection Systems (IDS) must process enormous quantities of traffic data in real time. Reducing the amount of data that IDS has to process at a time is necessary in order for these systems to be practically useful. The reduction is performed by grouping the similar attack signatures in the IDS knowledge base and comparing the actual network traffic with the representatives of such groups instead of each member of the group. The problem of grouping similar attack signatures is solved by classifying these signatures, very often in an unsupervised way. In that case, we are talking about clustering of attack signatures, i.e. finding well separated groups of similar signatures without learning. There are many methods of clustering, of which a particular one, the K-means partitional clustering method has gained popularity due to its linear time complexity with respect to the number of data units (vectors of features) to cluster. But with the increase of network bandwidth, even linear time complexity becomes insufficient. Since the beginning of the 21st century, several methods of improvement of the 50 years old original K-means algorithm have been proposed with the idea of reducing its time complexity especially when implemented in a distributed computing environment. This talk reviews these proposals and puts some research questions related to the properties of clusters and their optimal number. |
Slobodan Petrovic | NISseminar |
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15. september 2017 Kl. 12.12 55 min A146 |
Big Data Analytics: Topic Modeling for Digital Forensics Investigations and Cyber Threat Intelligence “Big Data Analytics” has become a high priority topic in Cyber Research and in the field of Cyber Security, Big Data represents a very serious problem. In the domain of Digital Forensics Investigations (DFI), the sheer volume of data to be analyzed impedes police operations that require timely reporting of DFI results to support active criminal investigations in the field. In the domain of Cyber Threat Intelligence (CTI), a rapid assessment of the available threat data is required to enable dissemination of actionable intelligence in a timely manner. Topic Modeling is an unsupervised machine learning method for analyzing large bodies of text data and producing estimates of the topics under discussion in them. To gain some insight into how it works, we reviewed some of the underlying principles of Topic Modeling. Then, I presented experimental results that show how Topic Modeling would work in the specific domains of DFI (using the Enron data set) and CTI (using posts scraped from an online hacker forum). |
Carl Stuart Leichter | NISseminar |
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1. september 2017 Kl. 12.12 55 min A146 |
Challenges and opportunities in sharing information security knowledge Abstract: We believe that proper sharing and re-use of information security knowledge among the information security professionals (ISP) can improve the quality of their work. Therefore, we aim to establish an open electronic community of practice for ISP in Norway under the project UnRizkNow. The proposed community should be the target’s group preferred venue for creating, obtaining, and sharing knowledge related to information security. In the NisSeminar session, I will talk about the challenges and opportunities that are associated with establishing this community of practice. Bio: Vivek Agrawal received the master’s degree in Information and communication systems security from Royal Institute of Technology (KTH), Sweden in 2013. He has been working as a PhD researcher at NTNU in Gjøvik in the field of Information security management since 2014. He is currently working on UnRizkNow project, funded by CCIS, as a part of his PhD research work. His research interests are Information security risk assessment, Information sharing, cloud computing. For further details about my publications, research interests, please check the following weblinks: https://www.ntnu.edu/employees/vivek.agrawal https://www.linkedin.com/in/vivek8705/ |
Vivek Agrawal | NISseminar |
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2. juni 2017 Kl. 12.12 55 min K105 |
Decisions, decisions, decisions Security governance in highly constrained and dynamic networks, such as C2 (Command and Control) and C4I (Command, Control, Communications, Computers, and Intelligence) systems at the tactical edge, requires refined control and adaptability to the rapidly evolving operational context. Imagine that you are in the field, commanding a cordon and search operation, and you receive information that a building is trapped with IEDs (Improvised Explosive Device). One of the tactical teams under your command is already executing a building clearing. What do you do, and how the network can accommodate your decision efficiently and effectively, while maintaining security? |
Vasileios Gkioulos | NISseminar |
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19. mai 2017 Kl. 12.12 55 min K105 |
A novel Binarization Scheme for Real-valued Biometric Feature Biometric binarization is the feature-type transformation that converts a specific feature representation into a binary representation. It is a fundamental issue to transform the real-valued feature vectors to the binary vectors in biometric template protection schemes. The transformed binary vectors should be high for both discriminability and privacy protection when they are employed as the input data for biometric cryptosystems. We present a novel binarization scheme based on random projection and random Support Vector Machine (SVM) to further enhance the security and privacy of biometric binary vectors. The proposed scheme can generate a binary vector of any given length as an ideal input for biometric cryptosystems. In addition, the proposed scheme is independent of the biometric feature data distribution. Several comparative experiments are conducted on multiple biometric databases to show the feasibility and efficiency of the proposed scheme. |
Jialiang Peng | NISseminar |
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12. mai 2017 Kl. 12.12 55 min A153 |
Digital Forensics and the Internet of Things A notable trend is found in the proliferation of systems and devices of various sizes and in various environments that are connected to the Internet through various network protocols. This Internet of Things (IoT) is still not fully developed or explored, but it is just a question of time before information gathered by these systems will be used as evidence in court. How will evidence dynamics be affected by machine to machine communication and data processing in IoT systems? What are the challenges these new systems pose for the digital forensic scientist and what are the opportunities they promise? |
Jens-Petter Sandvik | NISseminar |
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5. mai 2017 Kl. 12.20 45 min A153 |
Shao-Fang Wen | NISseminar | |
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7. april 2017 Kl. 12.12 55 min A153 |
Prediction of privacy violating behaviours within Smart Grids CIRA (Conflicting Incentives Risk Analysis) is a novel approach to risk analysis that focuses on the consequences of human decisions when identifying risks. However, in its current state, it lacks the theoretical foundation in psychology. Therefore it is necessary to identify and integrate relevant psychological theories into the current framework. Taking into account that stakeholders might not cooperate with the analyst during risk analysis, it is crucial to consider efficient and reliable data acquisition methods that require no direct access to the stakeholders. By integrating theories of behavior prediction and appropriate data collection methods CIRA is expected to become suitable for identifying real-life risks. To test this assumption the performance of the enhanced method will be assessed within the context of the IoTSec project focusing on Smart Electrical Grids. |
Adam Szekeres | NISseminar |
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24. mars 2017 Kl. 12.12 53 min A153 |
Extended Multi-spectral Imaging for Face Biometrics Biometric authentication based on face recognition acquired enormous attention due to its non-intrusive nature of image capture. Recently, with the advancement in sensor technology, face recognition based on multi-spectral imaging has gained a lot of popularity due to its potential of capturing discrete spatio-spectral images across the electromagnetic spectrum. In this presentation, I will be presenting a customized extended multispectral imaging sensor that can capture spectral images in nine narrow spectral bands across 530nm to 1000nm (Visible-NearInfrared) wavelength range. Further, in the presentation, the performance analysis study across two different age groups using our extended multi-spectral face database. |
Narayan Tulshidas Vetrekar | NISseminar |
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10. mars 2017 Kl. 12.12 55 min A153 |
Biometric Template Protection and Unlinkability Abstract: The wide deployment of biometric recognition systems in the last two decades has raised privacy concerns regarding the storage and use of biometric data. As a consequence, the ISO/IEC 24745 international standard on biometric information protection has established two main requirements for protecting biometric templates: irreversibility and unlinkability. Numerous efforts have been directed to the development and analysis of irreversible templates. However, there is still no systematic manner to analyse the unlinkability of such templates. We address this shortcoming by proposing a new general framework for the evaluation of biometric templates unlinkability. About the speaker: Marta Gomez-Barrero received her MSc degrees in Computer Science and Mathematics, and her PhD degree in Electrical Engineering from Universidad Autonoma de Madrid, in 2011 and 2016, respectively. She has carried out research internships at several worldwide leading groups in biometric recognition such as the Norwegian Biometrics Laboratory, part of the NISlab – Norwegian Information Security laboratory, at NTNU i Gjøvik, and the COMLAB, at Università degli Studi Roma Tre, Italy. Since 2016 she is a postdoctoral researcher at the Center for Research in Security and Privacy (CRISP), Hochshule Darmstdt, Germany. Her current research focuses on security and privacy evaluations and template protection schemes. She is the recipient of a number of distinctions, including: EAB European Biometric Industry Award 2015, Siew-Sngiem Best Paper Award at ICB 2015, Archimedes Award for young researches from Spanish MECD and Best Poster Award at ICB 2013. |
Marta Gomez-Barrero | NISseminar |
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3. mars 2017 Kl. 12.12 50 min A153 |
Memory access patterns for malware detection. This paper presents a novel method that could potentially detect zero-day attacks and contribute to proactive malware detection. Our method is based on analysis of sequences of memory access operations produced by binary _le during execution. In order to perform experiments, we utilized an automated virtualized environment with binary instrumentation tools to trace the memory access sequences. Unlike the other relevant papers, we focus only on analysis of basic (Read and Write) memory access operations and their n-grams rather than on the fact of a presence or an overall number of operations. Additionally, we performed a study of n-grams of memory accesses and tested it against real-world malware samples collected from open sources. Collected data and proposed feature construction methods resulted in accuracy of up to 98.92% using such Machine Learning methods as k-NN and ANN. |
Sergii Banin | NISseminar |
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10. februar 2017 Kl. 12.15 45 min A153 |
Bitcoin and the world of blockchain Abstract: The world of virtual currencies is exponentially growing to have ambitions to replace many of the present-day financial systems. Bitcoin, the first de-centralized cryptocurrency, has hitherto been the most successful one out of many existing virtual currencies. Yet, having many limitations, Bitcoin is continuously being refined. Scalability has been the biggest issue up until now which encouraged an invention of off-chain transactions. The off- chain transactions are Bitcoin transactions that do not get on the Bitcoin’s public ledger, blockchain. Such a concept changes the whole idea in a principle way. The presentation will discuss what problems de-centralized cryptocurrencies try to solve, what are the current limitations and approaches to solving them. Dmytro Piatkivskyi received a Bachelor degree in Information security from National Technical University of Ukraine “Kyiv Polytechnic Institute” in 2012. Graduated Gjøvik University College in 2014 with a Master degree in Information security. Before joining Testimon Forensics Research Group at NISlab as a PhD student was employed at UBS AG as a software developer, Investment Banking department. |
Dmytro Piatkivskyi | NISseminar |
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3. februar 2017 Kl. 12.13 47 min A153 |
Data mining techniques and applications used in official data | Ogerta Elezaj | NISseminar |
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21. mars 2014 Kl. 12.15 45 min K105 |
22/7 How to handle a major crisis | Svein Erik Egge | NISseminar |
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14. mars 2014 Kl. 12.05 67 min K105 |
Cyber War, Cyber Peace, Stones, and Glass Houses | Gary McGraw | NISseminar |