an article by Namita Dahiya and Shilpa Mahajan (The NorthCap University, Gurgaon, India) published in International Journal of Networking and Virtual Organisations Volume 21 Number 2 (2019)
Abstract
With the advancement of technology, today's world is a digital world where digital technology is generating new world of possibilities and opportunities and we are abandoned with digital data over the network that needs to be exchanged with many organisations, devices and users.
This data needs to be a secure data and malware is one type of threat to this data. There are many forms of malware that can damage this sensitive data.
This paper includes various malware detection techniques to detect various known and unknown binaries and presents a detailed analysis of current methods of malware detection and a malware analyser tools.
Hazel’s comment:
I have looked, maybe not as hard or for as long as I could have, for an accessible version of this article. Sure, I can read it in the British Library but that doesn’t help you if you are as interested in this subject as I am.
Showing posts with label analysis. Show all posts
Showing posts with label analysis. Show all posts
Wednesday, 4 September 2019
Friday, 3 February 2017
A social media and crowdsourcing data mining system for crime prevention during and post-crisis situations
an article by Konstantinos Domdouzis, Babak Akhgar,Simon Andrews, Helen Gibson and Laurence Hirsch (Sheffield Hallam University, UK) published in Journal of Systems and Information Technology Volume 18 Issue 4 (2016)
Abstract
Purpose
A number of crisis situations, such as natural disasters, have affected the planet over the past decade. The outcomes of such disasters are catastrophic for the infrastructures of modern societies. Furthermore, after large disasters, societies come face-to-face with important issues, such as the loss of human lives, people who are missing and the increment of the criminality rate. In many occasions, they seem unprepared to face such issues. This paper aims to present an automated social media and crowdsourcing data mining system for the synchronization of the police and law enforcement agencies for the prevention of criminal activities during and post a large crisis situation.
Design/methodology/approach
The paper realized qualitative research in the form of a review of the literature. This review focuses on the necessity of using social media and crowdsourcing data mining techniques in combination with advanced Web technologies for the purpose of providing solutions to problems related to criminal activities caused during and after a crisis. The paper presents the ATHENA crisis management system, which uses a number of data mining techniques to collect and analyze crisis-related data from social media for the purpose of crime prevention.
Findings
Conclusions are drawn on the significance of social media and crowdsourcing data mining techniques for the resolution of problems related to large crisis situations with emphasis to the ATHENA system.
Originality/value
The paper shows how the integrated use of social media and data mining algorithms can contribute in the resolution of problems that are developed during and after a large crisis.
Abstract
Purpose
A number of crisis situations, such as natural disasters, have affected the planet over the past decade. The outcomes of such disasters are catastrophic for the infrastructures of modern societies. Furthermore, after large disasters, societies come face-to-face with important issues, such as the loss of human lives, people who are missing and the increment of the criminality rate. In many occasions, they seem unprepared to face such issues. This paper aims to present an automated social media and crowdsourcing data mining system for the synchronization of the police and law enforcement agencies for the prevention of criminal activities during and post a large crisis situation.
Design/methodology/approach
The paper realized qualitative research in the form of a review of the literature. This review focuses on the necessity of using social media and crowdsourcing data mining techniques in combination with advanced Web technologies for the purpose of providing solutions to problems related to criminal activities caused during and after a crisis. The paper presents the ATHENA crisis management system, which uses a number of data mining techniques to collect and analyze crisis-related data from social media for the purpose of crime prevention.
Findings
Conclusions are drawn on the significance of social media and crowdsourcing data mining techniques for the resolution of problems related to large crisis situations with emphasis to the ATHENA system.
Originality/value
The paper shows how the integrated use of social media and data mining algorithms can contribute in the resolution of problems that are developed during and after a large crisis.
Thursday, 14 February 2013
Educational policies in a long-run perspective
an article by Michela Braga and Daniele Checchi (University of Milan) and Elena Meschi (University Ca' Foscari, Venice) published in Economic Policy Volume 28 Issue 73 (January 2013)
Summary
In this paper we study the effects of educational reforms on school attainment.
We construct a dataset of relevant reforms that occurred at the national level over the last century, and match individual information from 24 European countries to the most likely set-up faced when individual educational choices were undertaken.
Our identification strategy relies on temporal and geographical variations in the institutional arrangements, controlling for time/country fixed effects, as well as for country specific time trend. By characterising each group of reforms for their impact on mean years of education, educational inequality and intergenerational persistence, we show an ideal policy menu which has been available to policy-makers.
We distinguish between groups of policies that are either ‘inclusive’ or ‘selective’, depending on their diminishing or augmenting impact on inequality and persistence.
Finally, we correlate these reform measures to political coalitions prevailing in parliament, finding support for the idea that left-wing parties support reforms that are inclusive, while right-wing parties prefer selective ones.
This paper is part of a larger research project on ‘Growing Inequalities’ Impacts (GINI)' financed by the European Commission under the 7th Framework Programme (contract no. 244592).
This paper was presented at the 55th Panel Meeting of Economic Policy in Copenhagen.
Summary
In this paper we study the effects of educational reforms on school attainment.
We construct a dataset of relevant reforms that occurred at the national level over the last century, and match individual information from 24 European countries to the most likely set-up faced when individual educational choices were undertaken.
Our identification strategy relies on temporal and geographical variations in the institutional arrangements, controlling for time/country fixed effects, as well as for country specific time trend. By characterising each group of reforms for their impact on mean years of education, educational inequality and intergenerational persistence, we show an ideal policy menu which has been available to policy-makers.
We distinguish between groups of policies that are either ‘inclusive’ or ‘selective’, depending on their diminishing or augmenting impact on inequality and persistence.
Finally, we correlate these reform measures to political coalitions prevailing in parliament, finding support for the idea that left-wing parties support reforms that are inclusive, while right-wing parties prefer selective ones.
This paper is part of a larger research project on ‘Growing Inequalities’ Impacts (GINI)' financed by the European Commission under the 7th Framework Programme (contract no. 244592).
This paper was presented at the 55th Panel Meeting of Economic Policy in Copenhagen.
Subscribe to:
Posts (Atom)
