Current Personnel Security Research at PERSEREC

1992 ◽  
Author(s):  
Roger P. Denk ◽  
Keyword(s):  
Security Research

Big Data in the Field of Civil Security Research

2016 ◽  
Vol 7 (1) ◽  
pp. 54-64 ◽  
Author(s):  
Julia Gonschorek ◽  
Anja Langer ◽  
Benjamin Bernhardt ◽  
Caroline Räbiger
Keyword(s):  
Big Data ◽  
Temporal Distribution ◽  
Tactical Planning ◽  
Fire Departments ◽  
Prevention Measures ◽  
Scientific Contribution ◽  
Security Research ◽  
Geovisual Analytics ◽  
The University ◽  
Selection Of

This article gives insight in a running dissertation at the University in Potsdam. Point of discussion is the spatial and temporal distribution of emergencies of German fire brigades that have not sufficiently been scientifically examined. The challenge is seen in Big Data: enormous amounts of data that exist now (or can be collected in the future) and whose variables are linked to one another. These analyses and visualizations can form a basis for strategic, operational and tactical planning, as well as prevention measures. The user-centered (geo-) visualization of fire brigade data accessible to the general public is a scientific contribution to the research topic 'geovisual analytics and geographical profiling'. It may supplement antiquated methods such as the so-called pinmaps as well as the areas of engagement that are freehand constructions in GIS. Considering police work, there are already numerous scientific projects, publications, and software solutions designed to meet the specific requirements of Crime Analysis and Crime Mapping. By adapting and extending these methods and techniques, civil security research can be tailored to the needs of fire departments. In this paper, a selection of appropriate visualization methods will be presented and discussed.

scholarly journals Understanding Social Security Development: Lessons From the Chinese Case

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110326
Author(s):  
Guan Huang ◽  
Zhuang Cai
Keyword(s):  
Social Security ◽  
Political Legitimacy ◽  
Political Context ◽  
Common Mechanism ◽  
Social Security Systems ◽  
Security Systems ◽  
Security Research ◽  
Chinese Case ◽  
Thematic Approach ◽  
Convergence And Divergence

Understanding the development of social security systems constitutes the ultimate goal of social security research. This review traces and compares two schools of thought regarding social security development: the convergence and divergence schools. Using a thematic approach, this article first categorizes extant studies into one of these two schools and then identifies the broadly accepted mechanism of social security development by comparing them. After reviewing the extant research and its theoretical underpinnings, this article applies Mill’s methods of agreement and difference to show how the Chinese case contributes to and challenges our understanding of social security development. By discussing the assumptions of current research on social security development in light of the Chinese case, this article illuminates how political legitimacy serves as a common mechanism of social security development regardless of political context or structure.

scholarly journals Protection Motivation Theory in Information Systems Security Research

2021 ◽  
Vol 52 (2) ◽  
pp. 25-67
Author(s):  
Steffi Haag ◽  
Mikko Siponen ◽  
Fufan Liu
Keyword(s):  
Information Systems ◽  
Protection Motivation Theory ◽  
Protection Motivation ◽  
Security Threats ◽  
Motivation Theory ◽  
Road Map ◽  
Systems Security ◽  
Security Research ◽  
Is Security ◽  
New Research

Protection motivation theory (PMT) is one of the most commonly used theories to examine information security behaviors. Our systematic review of the application of PMT in information systems (IS) security and the comparison with its application for decades in psychology identified five categories of important issues that have not yet been examined in IS security research. Discussing these issues in terms of why they are relevant and important for IS security, and to what extent IS research has not considered them, offers new research opportunities associated with the study of PMT and IS security threats. We suggest how future studies can approach each of the open issues to provide a new road map for quantitative and qualitative IS scholars.

scholarly journals A Survey on Machine-Learning Based Security Design for Cyber-Physical Systems

2021 ◽  
Vol 11 (12) ◽  
pp. 5458
Author(s):  
Sangjun Kim ◽  
Kyung-Joon Park
Keyword(s):  
Machine Learning ◽  
Physical System ◽  
Large Scale ◽  
Computing System ◽  
Future Research ◽  
Physical Security ◽  
Computing Systems ◽  
Physical Systems ◽  
Security Research ◽  
Simultaneous Control

A cyber-physical system (CPS) is the integration of a physical system into the real world and control applications in a computing system, interacting through a communications network. Network technology connecting physical systems and computing systems enables the simultaneous control of many physical systems and provides intelligent applications for them. However, enhancing connectivity leads to extended attack vectors in which attackers can trespass on the network and launch cyber-physical attacks, remotely disrupting the CPS. Therefore, extensive studies into cyber-physical security are being conducted in various domains, such as physical, network, and computing systems. Moreover, large-scale and complex CPSs make it difficult to analyze and detect cyber-physical attacks, and thus, machine learning (ML) techniques have recently been adopted for cyber-physical security. In this survey, we provide an extensive review of the threats and ML-based security designs for CPSs. First, we present a CPS structure that classifies the functions of the CPS into three layers: the physical system, the network, and software applications. Then, we discuss the taxonomy of cyber-physical attacks on each layer, and in particular, we analyze attacks based on the dynamics of the physical system. We review existing studies on detecting cyber-physical attacks with various ML techniques from the perspectives of the physical system, the network, and the computing system. Furthermore, we discuss future research directions for ML-based cyber-physical security research in the context of real-time constraints, resiliency, and dataset generation to learn about the possible attacks.

Protecting a whale in a sea of phish

2020 ◽  
Vol 35 (3) ◽  
pp. 214-231
Author(s):  
Daniel Pienta ◽  
Jason Bennett Thatcher ◽  
Allen Johnston
Keyword(s):  
Information Security ◽  
Real World ◽  
Spillover Effects ◽  
Directed Attention ◽  
Future Directions ◽  
Security Research ◽  
Email Message ◽  
Multiple Domains ◽  
Future Information

Whaling is one of the most financially damaging, well-known, effective cyberattacks employed by sophisticated cybercriminals. Although whaling largely consists of sending a simplistic email message to a whale (i.e. a high-value target in an organization), it can result in large payoffs for cybercriminals, in terms of money or data stolen from organizations. While a legitimate cybersecurity threat, little information security research has directed attention toward whaling. In this study, we begin to provide an initial understanding of what makes whaling such a pernicious problem for organizations, executives, or celebrities (e.g. whales), and those charged with protecting them. We do this by defining whaling, delineating it from general phishing and spear phishing, presenting real-world cases of whaling, and provide guidance on future information security research on whaling. We find that whaling is far more complex than general phishing and spear phishing, spans multiple domains (e.g. work and personal), and potentially results in spillover effects that ripple across the organization. We conclude with a discussion of promising future directions for whaling and information security research.

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