This paper presents a methodology for quantitative evaluation of how lightweight a certain security service (cryptographic protocol) is. So far the term "lightweight" protocol was not precisely defined, and there was no metric to formally verify such protocols in terms of computational resources. This research is serving for significant further achievements for quantitative risk management in information systems.
COBISS.SI-ID: 2557399
The paper presents an approach for evaluation of software development methodologies (SDM) that considers the aspects of a SDM's social adoption and technical efficiency. It builds on existing evaluation models used in the field of SDM. Case study approach was used to validate the model in four software development organisations.
COBISS.SI-ID: 6803284
The organized flight of birds is one of the most easily observed, yet challenging to study, phenomena in biology. Scientific questions about these groups are usually concerned with mechanism such as how synchrony is achieved. Computer modelling has recently generated striking visual representations of organized flight and a number of hypotheses, but the ability to test these hypotheses lags behind the capacity to generate them.
COBISS.SI-ID: 7271764
This paper presents an approximate algorithm for detecting and filtering data dependencies with a sufficiently large distance between memory references. A sequence of the same operations can be replaced with a single SIMD operation if the distanceis greater than or equal to the number of data processed in the SIMD register. Some loops that could not be vectorized on traditional vector processors, can still be parallelized for short SIMD execution.
COBISS.SI-ID: 7412820
This article provides a methodology for quantitative evaluation of risks in information systems, covering in particular reactive and active approaches. Using this methodology, which is completely new (and using related solutions), it is possible to tangibly evaluate threats in information systems instead of providing descriptive estimates.
COBISS.SI-ID: 1024172628