The paper "Improving Security Requirement Adequacy" by Hanan Hibishi, Travis D. Breaux and Christian Wagner has been accepted to the 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016) will be held in Athens, Greece in December 2016. The paper has resulted from a recent collaboration between Carnegie Mellon and Nottingham Universities, with Hanan visiting Nottingham in early 2016.
Full title and abstract are included below. A full version of the paper will be available soon.
Title: Improving Security Requirement Adequacy - An Interval Type 2 Fuzzy Logic Security Assessment System
Abstract: Organizations rely on security experts to improve the security of their systems. These professionals use background knowledge and experience to align known threats and vulnerabilities before selecting mitigation options. The substantial depth of expertise in any one area (e.g., databases, networks, operating systems) precludes the possibility that an expert would have complete knowledge about all threats and vulnerabilities. To begin addressing this problem of fragmented knowledge, we investigate the challenge of developing a security requirements rule base that mimics multi-human expert reasoning to enable new decision-support systems. In this paper, we show how to collect relevant information from cyber security experts to enable the generation of: (1) interval type-2 fuzzy sets that capture intra- and inter-expert uncertainty around vulnerability levels; and (2) fuzzy logic rules driving the decision-making process within the requirements analysis. The proposed method relies on comparative ratings of security requirements in the context of concrete vignettes, providing a novel, interdisciplinary approach to knowledge generation for fuzzy logic systems. The paper presents an initial evaluation of the proposed approach through 52 scenarios with 13 experts to compare their assessments to those of the fuzzy logic decision support system. The results show that the system provides reliable assessments to the security analysts, in particular, generating more conservative assessments in 19% of the test scenarios compared to the experts’ ratings.
Tajul and Chao have released a new version of FuzzyR! https://CRAN.R-project.org/package=FuzzyR
Prof. Jon Garibaldi is giving a keynote presentation at CEEC 2016, the 8th Computer Science & Electronic Engineering Conference taking place at University of Essex, UK, on Friday 30th September. Copies of his slides will be posted here soon after the talk.
Bob John has just had an article accepted in the International Journal of Approximate Reasoning.
This paper concerns itself with decision making under uncertainty and the
consideration of risk. Type-1 fuzzy logic by its (essentially) crisp nature
is limited in modelling decision making as there is no uncertainty in the
membership function. We are interested in the role that interval type-2 fuzzy
sets might play in enhancing decision making. Previous work by Bellman and
Zadeh considered decision making to be based on goals and constraint. They
deployed type-1 fuzzy sets. This paper extends this notion to interval type-2
fuzzy sets and presents a new approach to using interval type-2 fuzzy sets
in a decision making situation taking into account the risk associated with
the decision making. The explicit consideration of risk levels increases the
solution space of the decision process and thus enables better decisions. We
explain the new approach and provide two examples to show how this new
Congratulations to everyone who published their papers at WCCI 2016. We had a great mix from our research and academic staff and from our PhD students within the group. It was a successful trip with many high quality papers, including two runner up best papers for best Fuzz-IEEE regular and student papers. Photos of our group giving their presentations and at the banquet can be seen here.
Runners-up in both Best Regular and Best Student Paper in Fuzz-IEEE 2016!
At this years WCCI 2016 conference, LUCID papers came second in both the Best Student and Best Regular Paper category! While it is not the top spot, we are very proud for the work to be recognised in the face of strong competition of 350 accepted papers. The papers are:
2nd in Best Student Paper Category:
Measuring the Similarity between zSlices General Type-2 Fuzzy Sets with Non-Normal Secondary
Josie McCulloch and Christian Wagner
University of Nottingham, United Kingdom
2nd in Best Regular Paper Category:
A Similarity-based Inference Engine for Non-Singleton Fuzzy Logic Systems
Christian Wagner, Amir Pourabdollah, Josie McCulloch, Robert John and Jonathan M. Garibaldi
University of Nottingham, United Kingdom
A number of us at are WCCI 2016 in the beautiful city of Vancouver. This conference brings together 3 conferences and we are at FUZZ-IEEE. Vancouver is a beautiful city and the conference is great.....
A bit of very important news. It was announced today that LUCID member Prof. Jon Garibaldi is to become the new editor-in-chief of IEEE Transactions on Fuzzy Systems. This is THE premier journal in fuzzy logic and a great honour for Jon reflecting his standing in the fuzzy community. There is hardly a more important role. Congratulations Jon!
The representation of type-2 fuzzy sets is a hot research topic. Christian Wagner and Hani Hagras introduced the notion of zslices. Mendel also introduced alph planes. Bob John's paper with Hussam Hamrawi and Simon Coupland on type-2 alpha cuts has just been accepted in IEEE Transactions on Fuzzy Systems. The paper is here. Type-2 fuzzy logic systems make use of type-2 fuzzy sets. To be able to deliver useful type-2 fuzzy logic applications we need to be able to perform meaningful operations on these sets. These operations should also be practically tractable. However, type-2 fuzzy sets suffer the shortcoming of being complex by definition. Indeed, the third dimension, which is the source of extra parameters, is in itself the origin of extra computational cost. The quest for a representation that allow practical systems to be implemented is the motivation for our work. In this paper we define the alpha-cut decomposition theorem for type- 2 fuzzy sets which is a new representation analogous to the alpha-cut representation of type-1 fuzzy sets and the extension principle.
It has taken a number of months, but finally the LUCID website is taking shape. Please bear with us while we include more content over the next few weeks and months.