8,243 research outputs found
An Overview of Economic Approaches to Information Security Management
The increasing concerns of clients, particularly in online commerce, plus the impact of legislations on information security have compelled companies to put more resources in information security. As a result, senior managers in many organizations are now expressing a much greater interest in information security. However, the largest body of research related to preventing breaches is technical, focusing on such issues as encryption and access control. In contrast, research related to the economic aspects of information security is small but rapidly growing. The goal of this technical note is twofold: i) to provide the reader with an structured overview of the economic approaches to information security and ii) to identify potential research directions
The Challenges in SDN/ML Based Network Security : A Survey
Machine Learning is gaining popularity in the network security domain as many
more network-enabled devices get connected, as malicious activities become
stealthier, and as new technologies like Software Defined Networking (SDN)
emerge. Sitting at the application layer and communicating with the control
layer, machine learning based SDN security models exercise a huge influence on
the routing/switching of the entire SDN. Compromising the models is
consequently a very desirable goal. Previous surveys have been done on either
adversarial machine learning or the general vulnerabilities of SDNs but not
both. Through examination of the latest ML-based SDN security applications and
a good look at ML/SDN specific vulnerabilities accompanied by common attack
methods on ML, this paper serves as a unique survey, making a case for more
secure development processes of ML-based SDN security applications.Comment: 8 pages. arXiv admin note: substantial text overlap with
arXiv:1705.0056
Big Data Privacy Context: Literature Effects On Secure Informational Assets
This article's objective is the identification of research opportunities in
the current big data privacy domain, evaluating literature effects on secure
informational assets. Until now, no study has analyzed such relation. Its
results can foster science, technologies and businesses. To achieve these
objectives, a big data privacy Systematic Literature Review (SLR) is performed
on the main scientific peer reviewed journals in Scopus database. Bibliometrics
and text mining analysis complement the SLR. This study provides support to big
data privacy researchers on: most and least researched themes, research
novelty, most cited works and authors, themes evolution through time and many
others. In addition, TOPSIS and VIKOR ranks were developed to evaluate
literature effects versus informational assets indicators. Secure Internet
Servers (SIS) was chosen as decision criteria. Results show that big data
privacy literature is strongly focused on computational aspects. However,
individuals, societies, organizations and governments face a technological
change that has just started to be investigated, with growing concerns on law
and regulation aspects. TOPSIS and VIKOR Ranks differed in several positions
and the only consistent country between literature and SIS adoption is the
United States. Countries in the lowest ranking positions represent future
research opportunities.Comment: 21 pages, 9 figure
A taxonomy of approaches for integrating attack awareness in applications
Software applications are subject to an increasing number of attacks, resulting in data breaches and ļ¬nancial damage. Many solutions have been considered to help mitigate these attacks, such as the integration of attack-awareness techniques. In this paper, we propose a taxonomy illustrating how existing attack awareness techniques can be integrated into applications. This work provides a guide for security researchers and developers, aiding them when choosing the approach which best ļ¬ts the needs of their application
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