Monte-Carlo randomized algorithm: Empirical analysis on real-world information systems

2016 ◽  
Author(s):  
Robert Kudelic ◽  
Dijana Oreski ◽  
Mario Konecki
Keyword(s):  
Monte Carlo ◽  
Information Systems ◽  
Empirical Analysis ◽  
Real World ◽  
Randomized Algorithm ◽  
World Information

Towards a Standard for a Reliable Execution Environment for Security Protocols

2016 ◽  
Vol 2 (1) ◽  
pp. 78
Author(s):  
Mahalingam Ramkumar
Keyword(s):  
Information Systems ◽  
Full Advantage ◽  
Real World ◽  
Security Protocols ◽  
Low Complexity ◽  
High Integrity ◽  
Execution Environment ◽  
World Information ◽  
Digital Assets ◽  
Attack Models

Approaches for securing digital assets of information systems can be classified as active approaches based on attack models, and passive approaches based on system-models. Passive approaches are inherently superior to active ones. However, taking full advantage of passive approaches calls for a rigorous standard for a low-complexity-high-integrity execution environment for security protocols. We sketch broad outlines of mirror network (MN) modules, as a candidate for such a standard. Their utility in assuring real-world information systems is illustrated with examples.

Tailorable E-Government Information Systems

2011 ◽  
pp. 1064-1069 ◽  
Author(s):  
George Lepouras ◽  
Anya Soriropoulou ◽  
Dimitrios Theotokis ◽  
Costas Vassilakis
Keyword(s):  
Information Systems ◽  
Real World ◽  
Software Reuse ◽  
Government Information ◽  
Multiple Sources ◽  
Public Authorities ◽  
Implementation Phase ◽  
Role Based ◽  
World Information ◽  
Data Elements

Real-world information, knowledge, and procedures after which information systems are modeled are generally of dynamic nature and subject to changes, due to the emergence of new requirements or revisions to initial specifications. E-government information systems (eGIS) present a higher degree of volatility in their environment, since requirement changes may stem from multiple sources, including legislation changes, organizational reforms, end-user needs, interoperability, and distribution concerns, etc. (Jansen, 2004; Prisma Project, 2002; Scholl, Klischewski, & Moon, 2005. To this end, the design and implementation of eGIS must adhere to paradigms and practices that facilitate the accommodation of changes to the eGIS as they occur in the real world. Object-oriented technologies have been extensively used to encapsulate reusable, tailorable software architectures as a collection of collaborating, extensible object classes; however the inherent conflict between software reuse and tailorability has inhibited the development of frameworks and models that would effectively support all requirements exposed by eGIS (Demeyer, Meijler, Nierstrasz, & Steyaert, 1997). The lack of such frameworks has lead to eGIS that cannot easily be adapted to the new requirements, mainly because only the predetermined specifications are taken into account and design decisions are fixed during the implementation phase (Stamoulis, Theotokis, Martakos, & Gyftodimos, 2003). A key issue to a viable solution eGIS modeling is the provision of the ability to multiple public authorities (PAs) to represent different aspects of the same real-world entity, while maintaining at the same time information consistency. Aspect representation is not only limited to data elements that describe the particular entity, but may extend to behavior alterations, when the entity is examined in different contexts. For example, an entity representing the citizen is expected to assume the behavior of beneficiary, when used in the context of the Ministry of Social Security, and the behavior of taxpayer, when accessed from the Ministry of Finance’s eGIS. Distinct behaviors may rely on different data representations and/or respond differently in requests. In this work we present a role-based modeling and implementation framework, which can be used for building eGIS and we argue that this model promotes the tailorability and maintainability of eGIS.

scholarly journals A Novel Monte-Carlo Simulation-Based Model for Malware Detection (eRBCM)

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2881
Author(s):  
Muath Alrammal ◽  
Munir Naveed ◽  
Georgios Tsaramirsis
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Information Systems ◽  
Malware Detection ◽  
New Model ◽  
Malicious Activity ◽  
Model Based ◽  
Simulation Based ◽  
Computer Based ◽  
Reinforcement Model

The use of innovative and sophisticated malware definitions poses a serious threat to computer-based information systems. Such malware is adaptive to the existing security solutions and often works without detection. Once malware completes its malicious activity, it self-destructs and leaves no obvious signature for detection and forensic purposes. The detection of such sophisticated malware is very challenging and a non-trivial task because of the malware’s new patterns of exploiting vulnerabilities. Any security solutions require an equal level of sophistication to counter such attacks. In this paper, a novel reinforcement model based on Monte-Carlo simulation called eRBCM is explored to develop a security solution that can detect new and sophisticated network malware definitions. The new model is trained on several kinds of malware and can generalize the malware detection functionality. The model is evaluated using a benchmark set of malware. The results prove that eRBCM can identify a variety of malware with immense accuracy.

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