VISTA:an inclusive insider threat taxonomy, with mitigation strategies

Insiders have the potential to do a great deal of damage, given their legitimate access to organisational assets and the trust they enjoy. Organisations can only mitigate insider threats if they understand what the different kinds of insider threats are, and what tailored measures can be used to mitigate the threat posed by each of them. Here, we derive VISTA (inclusiVe InSider Threat tAxonomy) based on an extensive literature review and a survey with C-suite executives to ensure that the VISTA taxonomy is not only scientifically grounded, but also meets the needs of organisations and their executives. To this end, we map each VISTA category of insider threat to tailored mitigations that can be deployed to reduce the threat

Deployment of Next Generation Intrusion Detection Systems against Internal Threats in a Medium-sized Enterprise

In this increasingly digital age, companies struggle to understand the origin of cyberattacks. Malicious actions can come from both the outside and the inside the business, so it is necessary to adopt tools that can reduce cyber risks by identifying the anomalies when the first symptoms appear. This thesis deals with the topic of internal attacks and explains how to use innovative Intrusion Detection Systems to protect the IT infrastructure of Medium-sized Enterprises. These types of technologies try to solve issues like poor visibility of network traffic, long response times to security breaches, and the use of inefficient access control mechanisms. In this research, multiple types of internal threats, the different categories of Intrusion Detection Systems and an in-depth analysis of the state-of-the-art IDSs developed during the last few years have been detailed. After that, there will be a brief explanation of the effectiveness of IDSs in both testing and production environments. All the reported phases took place within a company network, starting from the positioning of the IDS, moving on to its configuration and ending with the production environment. There is an analysis of the company expectations, together with an explanation of the different IDSs characteristics. This research shows data about potential attacks, mitigated and resolved threats, as well as network changes made thanks to the information gathered while using a cutting edge IDS. Moreover, the characteristics that a medium-sized company must have in order to be adequately protected by a new generation IDS have been generalized. In the same way, the functionalities that an IDS must possess in order to achieve the set objectives were reported. IDSs are incredibly adaptable to different environments, such as companies of different sectors and sizes, and can be tuned to achieve better results. At the end of this document are reported the potential future developments that should be addressed to improve IDS technologies further

Novel Alert Visualization: The Development of a Visual Analytics Prototype for Mitigation of Malicious Insider Cyber Threats

Cyber insider threat is one of the most difficult risks to mitigate in organizations. However, innovative validated visualizations for cyber analysts to better decipher and react to detected anomalies has not been reported in literature or in industry. Attacks caused by malicious insiders can cause millions of dollars in losses to an organization. Though there have been advances in Intrusion Detection Systems (IDSs) over the last three decades, traditional IDSs do not specialize in anomaly identification caused by insiders. There is also a profuse amount of data being presented to cyber analysts when deciphering big data and reacting to data breach incidents using complex information systems. Information visualization is pertinent to the identification and mitigation of malicious cyber insider threats. The main goal of this study was to develop and validate, using Subject Matter Experts (SME), an executive insider threat dashboard visualization prototype. Using the developed prototype, an experimental study was conducted, which aimed to assess the perceived effectiveness in enhancing the analysts’ interface when complex data correlations are presented to mitigate malicious insiders cyber threats. Dashboard-based visualization techniques could be used to give full visibility of network progress and problems in real-time, especially within complex and stressful environments. For instance, in an Emergency Room (ER), there are four main vital signs used for urgent patient triage. Cybersecurity vital signs can give cyber analysts clear focal points during high severity issues. Pilots must expeditiously reference the Heads Up Display (HUD), which presents only key indicators to make critical decisions during unwarranted deviations or an immediate threat. Current dashboard-based visualization techniques have yet to be fully validated within the field of cybersecurity. This study developed a visualization prototype based on SME input utilizing the Delphi method. SMEs validated the perceived effectiveness of several different types of the developed visualization dashboard. Quantitative analysis of SME’s perceived effectiveness via self-reported value and satisfaction data as well as qualitative analysis of feedback provided during the experiments using the prototype developed were performed. This study identified critical cyber visualization variables and identified visualization techniques. The identifications were then used to develop QUICK.v™ a prototype to be used when mitigating potentially malicious cyber insider threats. The perceived effectiveness of QUICK.v™ was then validated. Insights from this study can aid organizations in enhancing cybersecurity dashboard visualizations by depicting only critical cybersecurity vital signs

Cyber Infrastructure Protection: Vol. II

View the Executive SummaryIncreased reliance on the Internet and other networked systems raise the risks of cyber attacks that could harm our nation’s cyber infrastructure. The cyber infrastructure encompasses a number of sectors including: the nation’s mass transit and other transportation systems; banking and financial systems; factories; energy systems and the electric power grid; and telecommunications, which increasingly rely on a complex array of computer networks, including the public Internet. However, many of these systems and networks were not built and designed with security in mind. Therefore, our cyber infrastructure contains many holes, risks, and vulnerabilities that may enable an attacker to cause damage or disrupt cyber infrastructure operations. Threats to cyber infrastructure safety and security come from hackers, terrorists, criminal groups, and sophisticated organized crime groups; even nation-states and foreign intelligence services conduct cyber warfare. Cyber attackers can introduce new viruses, worms, and bots capable of defeating many of our efforts. Costs to the economy from these threats are huge and increasing. Government, business, and academia must therefore work together to understand the threat and develop various modes of fighting cyber attacks, and to establish and enhance a framework to assess the vulnerability of our cyber infrastructure and provide strategic policy directions for the protection of such an infrastructure. This book addresses such questions as: How serious is the cyber threat? What technical and policy-based approaches are best suited to securing telecommunications networks and information systems infrastructure security? What role will government and the private sector play in homeland defense against cyber attacks on critical civilian infrastructure, financial, and logistical systems? What legal impediments exist concerning efforts to defend the nation against cyber attacks, especially in preventive, preemptive, and retaliatory actions?https://press.armywarcollege.edu/monographs/1527/thumbnail.jp

Exploring the motivation behind cybersecurity insider threat and proposed research agenda

Cyber exploitation and malicious activities have become more sophisticated. Insider threat is one of the most significant cyber security threat vector, while posing a great concern to corporations and governments. An overview of the fundamental motivating forces and motivation theory are discussed. Such overview is provided to identify motivations that lead trusted employees to become insider threats in the context of cyber security. A research agenda with two sequential experimental research studies are outlined to address the challenge of insider threat mitigation by a prototype development. The first proposed study will classify data intake feeds, as recognized and weighted by cyber security experts, in an effort to establish predictive analytics of novel correlations of activities that may lead to cyber security incidents. It will also develop approach to identify how user activities can be compared against an established baseline, the user’s network cyber security pulse, with visualization of simulated users’ activities. Additionally, the second study will explain the process of assessing the usability of a developed visualization prototype that intends to present correlated suspicious activities requiring immediate action. Successfully developing the proposed prototype via feeds aggregation and an advanced visualization from the proposed research could assist in the mitigation of malicious insider threat

A Privacy-Preserving, Context-Aware, Insider Threat prevention and prediction model (PPCAITPP)

The insider threat problem is extremely challenging to address, as it is committed by insiders who are trusted and authorized to access the information resources of the organization. The problem is further complicated by the multifaceted nature of insiders, as human beings have various motivations and fluctuating behaviours. Additionally, typical monitoring systems may violate the privacy of insiders. Consequently, there is a need to consider a comprehensive approach to mitigate insider threats. This research presents a novel insider threat prevention and prediction model, combining several approaches, techniques and tools from the fields of computer science and criminology. The model is a Privacy- Preserving, Context-Aware, Insider Threat Prevention and Prediction model (PPCAITPP). The model is predicated on the Fraud Diamond (a theory from Criminology) which assumes there must be four elements present in order for a criminal to commit maleficence. The basic elements are pressure (i.e. motive), opportunity, ability (i.e. capability) and rationalization. According to the Fraud Diamond, malicious employees need to have a motive, opportunity and the capability to commit fraud. Additionally, criminals tend to rationalize their malicious actions in order for them to ease their cognitive dissonance towards maleficence. In order to mitigate the insider threat comprehensively, there is a need to consider all the elements of the Fraud Diamond because insider threat crime is also related to elements of the Fraud Diamond similar to crimes committed within the physical landscape. The model intends to act within context, which implies that when the model offers predictions about threats, it also reacts to prevent the threat from becoming a future threat instantaneously. To collect information about insiders for the purposes of prediction, there is a need to collect current information, as the motives and behaviours of humans are transient. Context-aware systems are used in the model to collect current information about insiders related to motive and ability as well as to determine whether insiders exploit any opportunity to commit a crime (i.e. entrapment). Furthermore, they are used to neutralize any rationalizations the insider may have via neutralization mitigation, thus preventing the insider from committing a future crime. However, the model collects private information and involves entrapment that will be deemed unethical. A model that does not preserve the privacy of insiders may cause them to feel they are not trusted, which in turn may affect their productivity in the workplace negatively. Hence, this thesis argues that an insider prediction model must be privacy-preserving in order to prevent further cybercrime. The model is not intended to be punitive but rather a strategy to prevent current insiders from being tempted to commit a crime in future. The model involves four major components: context awareness, opportunity facilitation, neutralization mitigation and privacy preservation. The model implements a context analyser to collect information related to an insider who may be motivated to commit a crime and his or her ability to implement an attack plan. The context analyser only collects meta-data such as search behaviour, file access, logins, use of keystrokes and linguistic features, excluding the content to preserve the privacy of insiders. The model also employs keystroke and linguistic features based on typing patterns to collect information about any change in an insider’s emotional and stress levels. This is indirectly related to the motivation to commit a cybercrime. Research demonstrates that most of the insiders who have committed a crime have experienced a negative emotion/pressure resulting from dissatisfaction with employment measures such as terminations, transfers without their consent or denial of a wage increase. However, there may also be personal problems such as a divorce. The typing pattern analyser and other resource usage behaviours aid in identifying an insider who may be motivated to commit a cybercrime based on his or her stress levels and emotions as well as the change in resource usage behaviour. The model does not identify the motive itself, but rather identifies those individuals who may be motivated to commit a crime by reviewing their computer-based actions. The model also assesses the capability of insiders to commit a planned attack based on their usage of computer applications and measuring their sophistication in terms of the range of knowledge, depth of knowledge and skill as well as assessing the number of systems errors and warnings generated while using the applications. The model will facilitate an opportunity to commit a crime by using honeypots to determine whether a motivated and capable insider will exploit any opportunity in the organization involving a criminal act. Based on the insider’s reaction to the opportunity presented via a honeypot, the model will deploy an implementation strategy based on neutralization mitigation. Neutralization mitigation is the process of nullifying the rationalizations that the insider may have had for committing the crime. All information about insiders will be anonymized to remove any identifiers for the purpose of preserving the privacy of insiders. The model also intends to identify any new behaviour that may result during the course of implementation. This research contributes to existing scientific knowledge in the insider threat domain and can be used as a point of departure for future researchers in the area. Organizations could use the model as a framework to design and develop a comprehensive security solution for insider threat problems. The model concept can also be integrated into existing information security systems that address the insider threat problemInformation ScienceD. Phil. (Information Systems

Cyber-Physical Threat Intelligence for Critical Infrastructures Security

Modern critical infrastructures comprise of many interconnected cyber and physical assets, and as such are large scale cyber-physical systems. Hence, the conventional approach of securing these infrastructures by addressing cyber security and physical security separately is no longer effective. Rather more integrated approaches that address the security of cyber and physical assets at the same time are required. This book presents integrated (i.e. cyber and physical) security approaches and technologies for the critical infrastructures that underpin our societies. Specifically, it introduces advanced techniques for threat detection, risk assessment and security information sharing, based on leading edge technologies like machine learning, security knowledge modelling, IoT security and distributed ledger infrastructures. Likewise, it presets how established security technologies like Security Information and Event Management (SIEM), pen-testing, vulnerability assessment and security data analytics can be used in the context of integrated Critical Infrastructure Protection. The novel methods and techniques of the book are exemplified in case studies involving critical infrastructures in four industrial sectors, namely finance, healthcare, energy and communications. The peculiarities of critical infrastructure protection in each one of these sectors is discussed and addressed based on sector-specific solutions. The advent of the fourth industrial revolution (Industry 4.0) is expected to increase the cyber-physical nature of critical infrastructures as well as their interconnection in the scope of sectorial and cross-sector value chains. Therefore, the demand for solutions that foster the interplay between cyber and physical security, and enable Cyber-Physical Threat Intelligence is likely to explode. In this book, we have shed light on the structure of such integrated security systems, as well as on the technologies that will underpin their operation. We hope that Security and Critical Infrastructure Protection stakeholders will find the book useful when planning their future security strategies

Data Exfiltration:A Review of External Attack Vectors and Countermeasures

AbstractContext One of the main targets of cyber-attacks is data exfiltration, which is the leakage of sensitive or private data to an unauthorized entity. Data exfiltration can be perpetrated by an outsider or an insider of an organization. Given the increasing number of data exfiltration incidents, a large number of data exfiltration countermeasures have been developed. These countermeasures aim to detect, prevent, or investigate exfiltration of sensitive or private data. With the growing interest in data exfiltration, it is important to review data exfiltration attack vectors and countermeasures to support future research in this field. Objective This paper is aimed at identifying and critically analysing data exfiltration attack vectors and countermeasures for reporting the status of the art and determining gaps for future research. Method We have followed a structured process for selecting 108 papers from seven publication databases. Thematic analysis method has been applied to analyse the extracted data from the reviewed papers. Results We have developed a classification of (1) data exfiltration attack vectors used by external attackers and (2) the countermeasures in the face of external attacks. We have mapped the countermeasures to attack vectors. Furthermore, we have explored the applicability of various countermeasures for different states of data (i.e., in use, in transit, or at rest). Conclusion This review has revealed that (a) most of the state of the art is focussed on preventive and detective countermeasures and significant research is required on developing investigative countermeasures that are equally important; (b) Several data exfiltration countermeasures are not able to respond in real-time, which specifies that research efforts need to be invested to enable them to respond in real-time (c) A number of data exfiltration countermeasures do not take privacy and ethical concerns into consideration, which may become an obstacle in their full adoption (d) Existing research is primarily focussed on protecting data in ‘in use’ state, therefore, future research needs to be directed towards securing data in ‘in rest’ and ‘in transit’ states (e) There is no standard or framework for evaluation of data exfiltration countermeasures. We assert the need for developing such an evaluation framework

Three-dimensional security framework for BYOD enabled banking institutions in Nigeria.

Doctoral Degree. University of KwaZulu-Natal, Durban.Bring your own device (BYOD) has become a trend in the present day, giving employees the freedom to bring personal mobile devices to access corporate networks. In Nigeria, most banking institutions are increasingly allowing their employees the flexibility to utilize mobile devices for work-related activities. However, as they do so, the risk of corporate data being exposed to threats increases. Hence, the study considered developing a security framework for mitigating BYOD security challenges. The study was guided by organizational, socio-technical and mobility theories in developing a conceptual framework. The study was conducted in two phases, the threat identification and the framework evaluation, using a mixed-methods approach. The main research strategies used for the threat identification were a questionnaire and interviews while closed and open-ended questions were used for the framework evaluation. A sample consisted of 380 banking employees from four banks were involved in the study. In addition, the study conducted in-depth interviews with twelve management officials from the participating banks. As for the framework evaluation, the study sampled twelve respondents to assess the developed security framework for viability as far as mitigating security threats emanating from BYOD in the banking sector is concerned. The sample consisted of eight executive managers of the bank and four academic experts in information security. Quantitative data was analysed using SPSS version 21 while qualitative data was thematically analysed. Findings from the threat identification revealed that banking institutions must develop security systems that not only identify threats associated with technical, social and mobility domains but also provide adequate mitigation of the threats. For the framework evaluation, the findings revealed that the security framework is appropriate in mitigating BYOD security threats. Based on the findings of the study, the developed security framework will help banks in Nigeria to mitigate against BYOD security threats. Furthermore, this security framework will contribute towards the generation of new knowledge in the field of information security as far as BYODs are concerned. The study recommends ongoing training for banks’ employees as it relates to mitigation of security threats posed by mobile devices