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A multiple-perspective approach for insider-threat risk prediction in cyber-securityElmrabit, Nebrase January 2018 (has links)
Currently governments and research communities are concentrating on insider threat matters more than ever, the main reason for this is that the effect of a malicious insider threat is greater than before. Moreover, leaks and the selling of the mass data have become easier, with the use of the dark web. Malicious insiders can leak confidential data while remaining anonymous. Our approach describes the information gained by looking into insider security threats from the multiple perspective concepts that is based on an integrated three-dimensional approach. The three dimensions are human issue, technology factor, and organisation aspect that forms one risk prediction solution. In the first part of this thesis, we give an overview of the various basic characteristics of insider cyber-security threats. We also consider current approaches and controls of mitigating the level of such threats by broadly classifying them in two categories: a) technical mitigation approaches, and b) non-technical mitigation approaches. We review case studies of insider crimes to understand how authorised users could harm their organisations by dividing these cases into seven groups based on insider threat categories as follows: a) insider IT sabotage, b) insider IT fraud, c) insider theft of intellectual property, d) insider social engineering, e) unintentional insider threat incident, f) insider in cloud computing, and g) insider national security. In the second part of this thesis, we present a novel approach to predict malicious insider threats before the breach takes place. A prediction model was first developed based on the outcomes of the research literature which highlighted main prediction factors with the insider indicator variables. Then Bayesian network statistical methods were used to implement and test the proposed model by using dummy data. A survey was conducted to collect real data from a single organisation. Then a risk level and prediction for each authorised user within the organisation were analysed and measured. Dynamic Bayesian network model was also proposed in this thesis to predict insider threats for a period of time, based on data collected and analysed on different time scales by adding time series factors to the previous model. Results of the verification test comparing the output of 61 cases from the education sector prediction model show a good consistence. The correlation was generally around R-squared =0.87 which indicates an acceptable fit in this area of research. From the result we expected that the approach will be a useful tool for security experts. It provides organisations with an insider threat risk assessment to each authorised user and also organisations can discover their weakness area that needs attention in dealing with insider threat. Moreover, we expect the model to be useful to the researcher's community as the basis for understanding and future research.
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Computer literacy : Does a background in computer programming give you better cyber security habits?Ivanov, Bozhidar, Vaino, Joonas January 2019 (has links)
Background: Computers are everywhere around us today and skills must be acquired in order for a person to use them. However, the topic of computer literacy is not researched enough to specify basic computer skills to consider an individual computer literate. This thesis will contribute to the research gap by investigating the computer skills of the workforce in the IT sector. Purpose: The purpose of this thesis is to examine the connection between computer programming and cyber security skills of the IT professional, e.g. is there a beneficial factor of this connection. Method: For this study the quantitative research method was used to gather data. The authors decided that the best way to reach their target group and answer the research questions was to conduct a survey and pose questions on the topics of computer literacy and cyber security. Conclusion: The results show that there is a statistical significance between the user’s security habits and his or her programming skills (or the absence of them). People who write code, defined as programmers, scored better on security skills survey, whereas their counterparts, the non-programmers, have some knowledge on the topic but they can never be absolutely sure of their cyber safety in the fast changing world of IT.
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Cyber security in power systemsSridharan, Venkatraman 06 April 2012 (has links)
Many automation and power control systems are integrated into the 'Smart Grid' concept for efficiently managing and delivering electric power. This integrated approach created several challenges that need to be taken into consideration such as cyber security issues, information sharing, and regulatory compliance. There are several issues that need to be addressed in the area of cyber security. Currently, there are no metrics for evaluating cyber security and methodologies to detect cyber attacks are in their infancy. There is a perceived lack of security built into the smart grid systems, but there is no mechanism for information sharing on cyber security incidents. In this thesis, we discuss the vulnerabilities in power system devices, and present ideas and a proposal towards multiple-threat system intrusion detection. We propose to test the multiple-threat methods for cyber security monitoring on a multi-laboratory test bed, and aid the development of a SCADA test bed, to be constructed on the Georgia Tech Campus.
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Reconnaissance de forme dans cybersécuritéVashaee, Ali January 2014 (has links)
Résumé : L’expansion des images sur le Web a provoqué le besoin de mettre en œuvre des méthodes de classement d’images précises pour plusieurs applications notamment la cybersécurité. L’extraction des caractéristiques est une étape primordiale dans la procédure du classement des images vu son impact direct sur la performance de la catégorisation finale des images et de leur classement. L’objectif de cette étude est d’analyser l’état de l’art des différents espaces de caractéristiques pour évaluer leur
efficacité dans le contexte de la reconnaissance de forme pour les applications de
cybersécurité. Les expériences ont montré que les descripteurs de caractéristiques
HOG et GIST ont une performance élevée. Par contre, cette dernière se dégrade
face aux transformations géométriques des objets dans les images. Afin d’obtenir
des systèmes de classement d’image plus fiables basés sur ces descripteurs, nous proposons deux méthodes. Dans la première méthode (PrMI) nous nous concentrons
sur l’amélioration de la propriété d’invariance du système de classement par tout
en maintenant la performance du classement. Dans cette méthode, un descripteur
invariant par rapport à la rotation dérivé de HOG est utilisé (RIHOG) dans une technique de recherche "top-down" pour le classement des images. La méthode (PrMI)
proposée donne non seulement une robustesse face aux transformations géométriques des objets, mais aussi une performance élevée similaire à celle de HOG. Elle est aussi efficace en terme de coût de calcul avec une complexité de l’ordre de O(n). Dans la deuxième méthode proposée (PrMII), nous nous focalisons sur la performance du classement en maintenant la propriété d’invariance du système de classement. Les objets sont localisés d’une façon invariante aux changement d’échelle dans l’espace de caractéristiques de covariance par région. Ensuite elles sont décrites avec les descripteurs HOG et GIST. Cette méthode procure une performance de classement meilleure en comparaison avec les méthodes implémentées dans l’étude et quelques méthodes CBIR expérimentées sur les données Caltech-256 dans les travaux antérieurs. // Abstract : The tremendous growth of accessible online images (Web images), provokes the need to perform accurate image ranking for applications like cyber-security. Feature extraction is an important step in image ranking procedures due to its direct impact on final categorization and ranking performance. The goal of this study is to analyse the state of the art feature spaces in order to evaluate their efficiency in the abject recognition context and image ranking framework for cyber-security applications. Experiments show that HOG and GIST feature descriptors exhibit high ranking performance. Whereas, these features are not rotation and scale invariant. In order to obtain more reliable image ranking systems based on these feature spaces, we proposed two methods. In the first method (PrMI) we focused on improving the invariance property of the ranking system while maintaining the ranking performance. In this method, a rotation invariant feature descriptor is derived from HOC (RIHOC). This descriptor is used in a top-down searching technique to caver the scale variation of the abjects in the images. The proposed method (PrMI) not only pro vides robustness against geometrical transformations of objects but also provides high ranking performance close to HOC performance. It is also computationally efficient with complexity around O(n). In the second proposed method (PrMII) we focused on the ranking performance while maintaining the invariance property of the ranking system. Objects are localized in a scale invariant fashion under a Region Covariance feature space, then they are described using HOC and CIST features. Finally to ob tain better evaluation over the performance of proposed method we compare it with existing research in the similar domain(CBIR) on Caltech-256. Proposed methods provide highest ranking performance in comparison with implemented methods in this study, and some of the CBIR methods on Caltech-256 dataset in previous works.
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Advanced Methodologies for Power System Security and Vulnerability AnalysisGuo Chen Unknown Date (has links)
Nowadays, with the rapid expansion of increasing utilization of renewable energy sources, power grid is evolving into a much complex man-made system in the technological age. Under the new circumstances, traditional methodologies for power system security analysis are facing a serious challenge. For the past decade, many countries have experienced large blackouts, which expose potential problems of current models and methodologies in power industry. On the other hand, since the 9.11 event and frequent suicide bombing attacks in some countries, terrorism has become a major threat for national security. With the extensive growth of terrorism activities, power system, the significant critical infrastructure, probably becomes the target of terrorists. If this happens, the impact is dramatically severe and may yield more frequent blackouts. This Ph.D. thesis aims at developing some advanced models and methodologies for exploring the vulnerability of power system and protecting it against potential terrorism threat. The dissertation mainly consists of the following four parts. (1)Complex network theory based power system security and vulnerability analysis methodologies are introduced. Mathematically, an interconnected complex power grid can be described as a complex network of nodes connected by edges. Generally speaking, topology parameters of network structure include important information of the structure. That is to say, some critical nodes and lines can have significant impact on large-scale blackouts. The thesis will present a new methodology to recognize those critical nodes and lines in power grids. (2)Complex system theory based power grid security and vulnerability analysis methodologies are presented. Power grid is a complex dynamic evolutionary system over years with continuous expansion so as to underpin the ongoing increase of power demand. Some properties of complex systems may have important relationship with large-scale blackouts. In other words, there may be some stages of evolutionary power systems that would be more likely to cause large blackouts. The thesis will investigate the relationship to identify those critical stages of power grids. (3)Game theory is applied to methodologies for power system security and vulnerability analysis. Terrorists are often considered as fully intelligent and strategic actors who can even hire scientists and power engineers to seek the vulnerability of power systems and then launch a vital attack. Game theory does treat actors as fully strategic players and has been successfully applied to many disciplines including economics, political science and military. The thesis will present new models and analysis methods for protecting power systems under terrorism attacks. (4)Cyber security technology is considered in power system security and vulnerability analysis. It is known that information technology plays an import role in today and next generation grid. In this situation, cyber security should be an important issue. If it is vulnerable to malicious threats such as hackers and cyber-terrorists, power grid will not reach its full capabilities. The thesis will present an initial framework to reduce the vulnerability of power grid against potential cyber attack.
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Advanced Methodologies for Power System Security and Vulnerability AnalysisGuo Chen Unknown Date (has links)
Nowadays, with the rapid expansion of increasing utilization of renewable energy sources, power grid is evolving into a much complex man-made system in the technological age. Under the new circumstances, traditional methodologies for power system security analysis are facing a serious challenge. For the past decade, many countries have experienced large blackouts, which expose potential problems of current models and methodologies in power industry. On the other hand, since the 9.11 event and frequent suicide bombing attacks in some countries, terrorism has become a major threat for national security. With the extensive growth of terrorism activities, power system, the significant critical infrastructure, probably becomes the target of terrorists. If this happens, the impact is dramatically severe and may yield more frequent blackouts. This Ph.D. thesis aims at developing some advanced models and methodologies for exploring the vulnerability of power system and protecting it against potential terrorism threat. The dissertation mainly consists of the following four parts. (1)Complex network theory based power system security and vulnerability analysis methodologies are introduced. Mathematically, an interconnected complex power grid can be described as a complex network of nodes connected by edges. Generally speaking, topology parameters of network structure include important information of the structure. That is to say, some critical nodes and lines can have significant impact on large-scale blackouts. The thesis will present a new methodology to recognize those critical nodes and lines in power grids. (2)Complex system theory based power grid security and vulnerability analysis methodologies are presented. Power grid is a complex dynamic evolutionary system over years with continuous expansion so as to underpin the ongoing increase of power demand. Some properties of complex systems may have important relationship with large-scale blackouts. In other words, there may be some stages of evolutionary power systems that would be more likely to cause large blackouts. The thesis will investigate the relationship to identify those critical stages of power grids. (3)Game theory is applied to methodologies for power system security and vulnerability analysis. Terrorists are often considered as fully intelligent and strategic actors who can even hire scientists and power engineers to seek the vulnerability of power systems and then launch a vital attack. Game theory does treat actors as fully strategic players and has been successfully applied to many disciplines including economics, political science and military. The thesis will present new models and analysis methods for protecting power systems under terrorism attacks. (4)Cyber security technology is considered in power system security and vulnerability analysis. It is known that information technology plays an import role in today and next generation grid. In this situation, cyber security should be an important issue. If it is vulnerable to malicious threats such as hackers and cyber-terrorists, power grid will not reach its full capabilities. The thesis will present an initial framework to reduce the vulnerability of power grid against potential cyber attack.
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Advanced Methodologies for Power System Security and Vulnerability AnalysisGuo Chen Unknown Date (has links)
Nowadays, with the rapid expansion of increasing utilization of renewable energy sources, power grid is evolving into a much complex man-made system in the technological age. Under the new circumstances, traditional methodologies for power system security analysis are facing a serious challenge. For the past decade, many countries have experienced large blackouts, which expose potential problems of current models and methodologies in power industry. On the other hand, since the 9.11 event and frequent suicide bombing attacks in some countries, terrorism has become a major threat for national security. With the extensive growth of terrorism activities, power system, the significant critical infrastructure, probably becomes the target of terrorists. If this happens, the impact is dramatically severe and may yield more frequent blackouts. This Ph.D. thesis aims at developing some advanced models and methodologies for exploring the vulnerability of power system and protecting it against potential terrorism threat. The dissertation mainly consists of the following four parts. (1)Complex network theory based power system security and vulnerability analysis methodologies are introduced. Mathematically, an interconnected complex power grid can be described as a complex network of nodes connected by edges. Generally speaking, topology parameters of network structure include important information of the structure. That is to say, some critical nodes and lines can have significant impact on large-scale blackouts. The thesis will present a new methodology to recognize those critical nodes and lines in power grids. (2)Complex system theory based power grid security and vulnerability analysis methodologies are presented. Power grid is a complex dynamic evolutionary system over years with continuous expansion so as to underpin the ongoing increase of power demand. Some properties of complex systems may have important relationship with large-scale blackouts. In other words, there may be some stages of evolutionary power systems that would be more likely to cause large blackouts. The thesis will investigate the relationship to identify those critical stages of power grids. (3)Game theory is applied to methodologies for power system security and vulnerability analysis. Terrorists are often considered as fully intelligent and strategic actors who can even hire scientists and power engineers to seek the vulnerability of power systems and then launch a vital attack. Game theory does treat actors as fully strategic players and has been successfully applied to many disciplines including economics, political science and military. The thesis will present new models and analysis methods for protecting power systems under terrorism attacks. (4)Cyber security technology is considered in power system security and vulnerability analysis. It is known that information technology plays an import role in today and next generation grid. In this situation, cyber security should be an important issue. If it is vulnerable to malicious threats such as hackers and cyber-terrorists, power grid will not reach its full capabilities. The thesis will present an initial framework to reduce the vulnerability of power grid against potential cyber attack.
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CyberCog A Synthetic Task Environment for Measuring Cyber Situation AwarenessJanuary 2011 (has links)
abstract: This thesis describes a synthetic task environment, CyberCog, created for the purposes of 1) understanding and measuring individual and team situation awareness in the context of a cyber security defense task and 2) providing a context for evaluating algorithms, visualizations, and other interventions that are intended to improve cyber situation awareness. CyberCog provides an interactive environment for conducting human-in-loop experiments in which the participants of the experiment perform the tasks of a cyber security defense analyst in response to a cyber-attack scenario. CyberCog generates the necessary performance measures and interaction logs needed for measuring individual and team cyber situation awareness. Moreover, the CyberCog environment provides good experimental control for conducting effective situation awareness studies while retaining realism in the scenario and in the tasks performed. / Dissertation/Thesis / M.C.St. Computing Studies 2011
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Cybersecurity: Stochastic Analysis and Modelling of Vulnerabilities to Determine the Network Security and Attackers BehaviorKaluarachchi, Pubudu Kalpani 26 June 2017 (has links)
Development of Cybersecurity processes and strategies should take two main approaches. One is to develop an efficient and effective set of methodologies to identify software vulnerabilities and patch them before being exploited. Second is to develop a set of methodologies to predict the behavior of attackers and execute defending techniques based on attacking behavior. Managing of Vulnerabilities and analyzing them is directly related to the first approach. Developing of methodologies and models to predict the behavior of attackers is related to the second approach. Both these approaches are inseparably interconnected. Our effort in this study mainly focuses on developing useful statistical models that can give us signals about the behavior of cyber attackers.
Analytically understanding of vulnerabilities in statistical point of view helps to develop a set of statistical models that works as a bridge between Cybersecurity and Abstract Statistical and Mathematical knowledge. Any such effort should begin with properly understanding the nature of Vulnerabilities in a computer network system. We start this study with analyzing "Vulnerability" based on inferences that can be taken from National Vulnerability Database (NVD). In Cybersecurity context, we apply Markov approach to develop suitable predictive models to successfully estimate the minimum number of steps to compromise a security goal that an attacker would take using the concept of Expected Path Length (EPL).
We have further developed Non-Homogeneous Stochastic model by improving EPL estimates in to a time dependent variable. This approach analytically applied in a simple model of computer network with discovered vulnerabilities resulted in several useful observations exemplifying the applicability in real world computer systems. The methodology indicated a measure of the "Risk" associated with the model network as a function of time indicating defending professionals on the threats they are facing and should anticipate to face.
Furthermore, using a similar approach taken in well-known Google page rank algorithm, a new ranking algorithm of vulnerability ranks with respect to time for computer network system is also presented in this study.
With better IT resources analytical models and methodologies presented in this study can be developed into more generalized versions and apply in real world computer network environments.
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Cybersecurity: Probabilistic Behavior of Vulnerability and Life CycleRajasooriya, Sasith Maduranga 28 June 2017 (has links)
Analysis on Vulnerabilities and Vulnerability Life Cycle is at the core of Cybersecurity related studies. Vulnerability Life Cycle discussed by S. Frei and studies by several other scholars have noted the importance of this approach. Application of Statistical Methodologies in Cybersecurity related studies call for a greater deal of new information. Using currently available data from National Vulnerability Database this study develops and presents a set of useful Statistical tools to be applied in Cybersecurity related decision making processes.
In the present study, the concept of Vulnerability Space is defined as a probability space. Relevant theoretical analyses are conducted and observations in the vulnerability space in aspects of events and states are discussed.
Transforming IT related cybersecurity issues into analytical formation so that abstract and conceptual knowledge from Mathematics and Statistics can be applied is a challenge. However, to overcome rising threats from Cyber-attacks such an integration of analytical foundation to understand the issues and develop strategies is essential. In the present study we apply well known Markov approach in a new approach of Vulnerability Life Cycle to develop useful analytical methods to assess the Risk associated with a vulnerability. We also presents, a new Risk Index integrating the results obtained and details from the Common Vulnerability Scoring System (CVSS).
In addition, a comprehensive study on the Vulnerability Space is presented discussing the likelihood of probable events in the probability sub-spaces of vulnerabilities.
Finally, an Extended Vulnerability Life Cycle model is presented and discussed in relation to States and Events in the Vulnerability Space that lays down a strong foundation for any future vulnerability related analytical research efforts.
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