Proper Incentives for Proper IT Security Management – A System Dynamics Approach

Abstract \ It has been known for many years that security failures are caused at least as often by bad incentives as by bad design. However, the regulatory correction of bad incentives is not easy in practice and it is still lacking. In the meantime, system dynamics models of security systems can improve the situation by increasing the awareness that misaligned incentives can backfire as long-term consequences of security failures hit back the principal. We illustrate our argument using system archetypes and concept simulation models revealing the impact of two different security strategies, viz. misaligned incentives (the customer having the burden of proof in case of alleged fraud) vs the bank having the burden of proof. From this we argue that online system dynamics could be used in eGovernment to educate principals and the public. Also, legal measures could become more effective when supported with forensic evidence from simulation models.

A particular type of non-associative algebras and graph theory

Evolution algebras have many connections with other mathematical fields, like group theory, stochastics processes, dynamical systems and other related ones. The main goal of this paper is to introduce a novel non-usual research on Discrete Mathematics regarding the use of graphs to solve some open problems related to the theory of graphicable algebras, which constitute a subset of those algebras. We show as many our advances in this field as other non solved problems to be tackled in future

Computational method for obtaining filiform Lie algebras of arbitrary dimension

This paper shows a new computational method to obtain filiform Lie algebras, which is based on the relation between some known invariants of these algebras and the maximal dimension of their abelian ideals. Using this relation, the law of each of these algebras can be completely determined and characterized by means of the triple consisting of its dimension and the invariants z1 and z2. As examples of application, we have included a table showing all valid triples determining filiform Lie algebras for dimension 13

Low-dimensional filiform Lie algebras over finite fields

In this paper we use some objects of Graph Theory to classify low-dimensional filiform Lie algebras over finite fields. The idea lies in the representation of each Lie algebra by a certain type of graphs. Then, some properties on Graph Theory make easier to classify the algebras. As results, which can be applied in several branches of Physics or Engineering, for instance, we find out that there exist, up to isomorphism, six 6-dimensional filiform Lie algebras over Z/pZ, for p = 2, 3, 5.Plan Andaluz de Investigación (Junta de Andalucía

QADE: a novel trust and reputation model for handling false trust values in e–commerce environments with subjectivity consideration

Trust is essential to economic efficiency. Trading partners choose each other and make decisions based on how much they trust one another. The way to assess trust in e-commerce is different from those in brick and mortar businesses, as there are limited indicators available in online environments. One way is to deploy trust and reputation management systems that are based on collecting feedbacks about partners’ transactions. One of the problems within such systems is the presence of unfair ratings. In this paper, an innovative QADE trust model is presented, which assumes the existence of unfairly reported trust assessments. Subjective nature of trust is considered, where differently reported trust values do not necessarily mean false trust values but can also imply differences in dispositions to trust. The method to identify and filter out the presumably false values is defined. In our method, a trust evaluator finds other agents in society that are similar to him, taking into account pairwise similarity of trust values and similarity of agents’ general mindsets. In order to reduce the effect of unfair ratings, the values reported by the non-similar agents are excluded from the trust computation. Simulations have been used to compare the effectiveness of algorithms to decrease the effect of unfair ratings. The simulations have been carried out in environments with varying number of attackers and targeted agents, as well as with different kinds of attackers. The results showed significant improvements of our proposed method. On average 6% to 13% more unfair trust ratings have been detected by our method. Unfair rating effects on trust assessment were reduced with average improvements from 26% to 57% compared to the other most effective filtering methods by Whitby and Teacy. First published online: 02 Jun 201