A socio-technical perspective to counter cyber-enabled industrial espionage

The ubiquitous digitization of information and the pervasive connectivity of work systems have inevitably facilitated cyber-enabled industrial espionage. Security failures explain most of cyber industrial espionage incidents, and insider threats represent a significant pattern in many case examples. Insiders can inadvertently or purposefully pose serious threats to organisations by facilitating access to or misuse of proprietary sensitive data. This paper argues that technical security solutions have rather limited scope to tackle this problem, and that a socio-technical approach has potential to provide a better means to address the challenge of preventing and responding to insider threats. Such an approach could bridge the gap between the design and implementation of security solutions and creation of an organisational culture that is security-aware

Impact and key challenges of insider threats on organizations and critical businesses

The insider threat has consistently been identified as a key threat to organizations and governments. Understanding the nature of insider threats and the related threat landscape can help in forming mitigation strategies, including non-technical means. In this paper, we survey and highlight challenges associated with the identification and detection of insider threats in both public and private sector organizations, especially those part of a nation’s critical infrastructure. We explore the utility of the cyber kill chain to understand insider threats, as well as understanding the underpinning human behavior and psychological factors. The existing defense techniques are discussed and critically analyzed, and improvements are suggested, in line with the current state-of-the-art cyber security requirements. Finally, open problems related to the insider threat are identified and future research directions are discussed

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

Mitigating Insider Threat Risks in Cyber-physical Manufacturing Systems

Cyber-Physical Manufacturing System (CPMS)—a next generation manufacturing system—seamlessly integrates digital and physical domains via the internet or computer networks. It will enable drastic improvements in production flexibility, capacity, and cost-efficiency. However, enlarged connectivity and accessibility from the integration can yield unintended security concerns. The major concern arises from cyber-physical attacks, which can cause damages to the physical domain while attacks originate in the digital domain. Especially, such attacks can be performed by insiders easily but in a more critical manner: Insider Threats. Insiders can be defined as anyone who is or has been affiliated with a system. Insiders have knowledge and access authentications of the system\u27s properties, therefore, can perform more serious attacks than outsiders. Furthermore, it is hard to detect or prevent insider threats in CPMS in a timely manner, since they can easily bypass or incapacitate general defensive mechanisms of the system by exploiting their physical access, security clearance, and knowledge of the system vulnerabilities. This thesis seeks to address the above issues by developing an insider threat tolerant CPMS, enhanced by a service-oriented blockchain augmentation and conducting experiments & analysis. The aim of the research is to identify insider threat vulnerabilities and improve the security of CPMS. Blockchain\u27s unique distributed system approach is adopted to mitigate the insider threat risks in CPMS. However, the blockchain limits the system performance due to the arbitrary block generation time and block occurrence frequency. The service-oriented blockchain augmentation is providing physical and digital entities with the blockchain communication protocol through a service layer. In this way, multiple entities are integrated by the service layer, which enables the services with less arbitrary delays while retaining their strong security from the blockchain. Also, multiple independent service applications in the service layer can ensure the flexibility and productivity of the CPMS. To study the effectiveness of the blockchain augmentation against insider threats, two example models of the proposed system have been developed: Layer Image Auditing System (LIAS) and Secure Programmable Logic Controller (SPLC). Also, four case studies are designed and presented based on the two models and evaluated by an Insider Attack Scenario Assessment Framework. The framework investigates the system\u27s security vulnerabilities and practically evaluates the insider attack scenarios. The research contributes to the understanding of insider threats and blockchain implementations in CPMS by addressing key issues that have been identified in the literature. The issues are addressed by EBIS (Establish, Build, Identify, Simulation) validation process with numerical experiments and the results, which are in turn used towards mitigating insider threat risks in CPMS

Distance Measurement Methods for Improved Insider Threat Detection

Insider threats are a considerable problem within cyber security and it is often difficult to detect these threats using signature detection. Increasing machine learning can provide a solution, but these methods often fail to take into account changes of behaviour of users. This work builds on a published method of detecting insider threats and applies Hidden Markov method on a CERT data set (CERT r4.2) and analyses a number of distance vector methods (Damerau–Levenshtein Distance, Cosine Distance, and Jaccard Distance) in order to detect changes of behaviour, which are shown to have success in determining different insider threats

Incorporating psychology into cyber security education: A pedagogical approach

The role of the human in cyber security is well acknowledged. Many cyber security incidents rely upon targets performing specific behavioural actions, such as opening a link within a phishing email. Cyber adversaries themselves are driven by psychological processes such as motivation, group dynamics and social identity. Furthermore, both intentional and unintentional insider threats are associated with a range of psychological factors, including cognitive load, mental wellbeing, trust and interpersonal relations. By incorporating psychology into cyber security education, practitioners will be better equipped with the skills they need to address cyber security issues. However, there are challenges in doing so. Psychology is a broad discipline, and many theories, approaches and methods may have little practical significance to cyber security. There is a need to sift through the literature to identify what can be applied to cyber security. There are also pedagogical differences in how psychology and cyber security are taught and also psychological differences in the types of student that may typically study psychology and cyber security. To engage with cyber security students, it is important that these differences are identified and positively addressed. Essential to this endeavor is the need to discuss and collaborate across the two disciplines. In this paper, we explore these issues and discuss our experiences as psychology and cyber security academics who work across disciplines to deliver psychology education to cyber security students, practitioners and commercial clients

A multiple-perspective approach for insider-threat risk prediction in cyber-security

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

Development of Cybersecurity Competency and Professional Talent for Cyber Ummah

The world is facing with threats in digital transformation. Cyber threats become trending as reported by my countries. Developed countries like Britain, America, Europe and Japan already prepared countermeasures for various incidents on computer threats since Internet was introduced. They formulated and developed a successful model to produce computer security expert and highly skilled talent at various level diploma, bachelor and professional. University and College established academic program in computer and internet security at bachelor and postgraduate level. Industries at those countries introduced certification program in computer and internet security. Throughout our studies, limited initiatives related to talent development in combating computer security issues including cyber threats. Previous studies showed development of cybersecurity talent in Muslim countries is critical. Malaysia needs 20000 cybersecurity professional in 2025 and only achieved 2500 at present. This study presents our experience in developing cybersecurity competencies and professional talent for OIC-Country. We collaborated virtually with OIC-CERT (OIC Centre for Emergency and Response Team) in knowledge exchange, proposed appropriate competency model and participate in professional certification development. We presented the eight years active involvement with OIC-CERT activities.  All initiatives established by OIC-CERT has produced outstanding impact to OIC Countries. One of the impactful initiatives known GlobalAce, it getting serious attention by many muslim countries. We also get benefit of other programs such as  training for risks analysis, incident management and policy development. Our students be able to participate with Virtual Lecture on Combating Insider Threats, Cyber Threats Drill, and Security Audit. OIC-CERT also introduce the first Industry Journal in Cybersecurity known as OIC-CERT Journal of Cybersecurity.   

A Systematic Review of the Availability and Efficacy of Countermeasures to Internal Threats in Healthcare Critical Infrastructure

Insider attacks are becoming increasingly detrimental and frequent, affecting critical infrastructure at a massive scale. Recent attacks such as the UK National Health Service (NHS) WannaCry ransomware attack which partly depends on internal users for initial infection highlight the increasing role of the malicious insiders in cyber attack campaigns . The objective of this research is to ascertain the existing technological capability to mitigate insider threats within computer security systems by way of a mixed-method systematic review. Evidence was acquired from major sources of mainstream and grey literature by analysing about 300, 000 papers. Crude aggregated results were analysed across the literature, the results were TPR 0.75, FPR 0.32, σ 0.24 and 0.36 respectively, σ 2 0.06 and 0.13 respectively. In totality, the literature evidence suggests that there is high heterogeneity across crude data indicating that the effectiveness of security measures varies significantly. No solution is able to totally mitigate an insider threat. Themes when set against that data suggest that most, if not all, security measures require breaches to occur before an analysis of malicious activity can prevent it in future through recall. Such a reactive approach is not effective to protect our critical infrastructure including our healthcare systems. Consequently, there is a major theoretical shortfall in current cyber defence architecture