Information Systems Betrayal: When Cybersecurity Systems Shift from Agents of Protection to Agents of Harm

Cybersecurity systems provide a unique opportunity of study as they can be used as agents of protection and harm. Practice uses these systems of protection against employees through the use of red team and black hat tactics for perimeter testing as well as invasive, complex monitoring for defense of internal threats. It is important to understand the effects of these actions on end users. This study seeks to understand the effects of these cybersecurity practices on individuals through the perspectives of trust, betrayal, aversion, and resistance. An integrative model is built and employed to understand the formation and consequences of IS betrayal

Reachability-based impact as a measure for insiderness

Insider threats pose a difficult problem for many organisations. While organisations in principle would like to judge the risk posed by a specific insider threat, this is in general not possible. This limitation is caused partly by the lack of models for human behaviour, partly by restrictions on how much and what may be monitored, and by our inability to identify relevant features in large amounts of logged data. To overcome this, the notion of insiderness has been proposed, which measures the degree of access an actor has to a certain resource. We extend this notion with the concept of impact of an insider, and present different realisations of impact. The suggested approach results in readily usable techniques that allow to get a quick overview of potential insider threats based on locations and assets reachable by employees. We present several variations ranging from pure reachability to potential damage to assets causable by an insider

A multi-dimension taxonomy of insider threats in cloud computing

Security is considered a significant deficiency in cloud computing, and insider threats problem exacerbate security concerns in the cloud. In addition to that, cloud computing is very complex by itself, because it encompasses numerous technologies and concepts. Apparently, overcoming these challenges requires substantial efforts from information security researchers to develop powerful mitigation solutions for this emerging problem. This entails developing a taxonomy of insider threats in cloud environments encompassing all potential abnormal activities in the cloud, and can be useful for conducting security assessment. This paper describes the first phase of an ongoing research to develop a framework for mitigating insider threats in cloud computing environments. Primarily, it presents a multidimensional taxonomy of insider threats in cloud computing, and demonstrates its viability. The taxonomy provides a fundamental understanding for this complicated problem by identifying five dimensions, it also supports security engineers in identifying hidden paths, thus determining proper countermeasures, and presents a guidance covers all bounders of insiders threats issue in clouds, hence it facilitates researchers’ endeavours in tackling this problem. For instance, according to the hierarchical taxonomy, clearly many significant issues exist in public cloud, while conventional insider mitigation solutions can be used in private clouds. Finally, the taxonomy assists in identifying future research directions in this emerging area

Identifying Common Characteristics of Malicious Insiders

Malicious insiders account for large proportion of security breaches or other kinds of loss for organizations and have drawn attention of both academics and practitioners. Although methods and mechanism have been developed to monitor potential insider via electronic data monitoring, few studies focus on predicting potential malicious insiders. Based on the theory of planned behavior, certain cues should be observed or expressed when an individual performs as a malicious insider. Using text mining to analyze various media content of existing insider cases, we strive to develop a method to identify crucial and common indicators that an individual might be a malicious insider. Keywords: malicious insider, insider threat, the theory of planned behavior, text minin

CopAS: A Big Data Forensic Analytics System

With the advancing digitization of our society, network security has become one of the critical concerns for most organizations. In this paper, we present CopAS, a system targeted at Big Data forensics analysis, allowing network operators to comfortably analyze and correlate large amounts of network data to get insights about potentially malicious and suspicious events. We demonstrate the practical usage of CopAS for insider threat detection on a publicly available PCAP dataset and show how the system can be used to detect insiders hiding their malicious activity in the large amounts of networking data streams generated during the daily activities of an organization

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Risk assessment of email accounts: Difference between perception and reality

The use of Internet is associated with a growing number of security threats. This thesis analyzes how users perceive the security of their email account based on the email account provider. With our study, we aim to contribute to the information security systems literature in three ways: First, by taking a more complete view on security online, and reviewing the concept of usable security, usability, human-computer interaction, trust and user perception. Second, by performing an analysis of providers of online services specifically emails. Third, by applying a renowned risk analysis method called Information Security Risk Analysis Method (ISRAM) for risk assessment. The ISRAM analysis revealed that Hotmail, Gmail and Yahoo email accounts have a medium risk level, while the reality analysis demonstrated no clearly more secure account provider with only low level risk counts

A Framework for an Adaptive Early Warning and Response System for Insider Privacy Breaches

Organisations such as governments and healthcare bodies are increasingly responsible for managing large amounts of personal information, and the increasing complexity of modern information systems is causing growing concerns about the protection of these assets from insider threats. Insider threats are very difficult to handle, because the insiders have direct access to information and are trusted by their organisations. The nature of insider privacy breaches varies with the organisation’s acceptable usage policy and the attributes of an insider. However, the level of risk that insiders pose depends on insider breach scenarios including their access patterns and contextual information, such as timing of access. Protection from insider threats is a newly emerging research area, and thus, only few approaches are available that systemise the continuous monitoring of dynamic insider usage characteristics and adaptation depending on the level of risk. The aim of this research is to develop a formal framework for an adaptive early warning and response system for insider privacy breaches within dynamic software systems. This framework will allow the specification of multiple policies at different risk levels, depending on event patterns, timing constraints, and the enforcement of adaptive response actions, to interrupt insider activity. Our framework is based on Usage Control (UCON), a comprehensive model that controls previous, ongoing, and subsequent resource usage. We extend UCON to include interrupt policy decisions, in which multiple policy decisions can be expressed at different risk levels. In particular, interrupt policy decisions can be dynamically adapted upon the occurrence of an event or over time. We propose a computational model that represents the concurrent behaviour of an adaptive early warning and response system in the form of statechart. In addition, we propose a Privacy Breach Specification Language (PBSL) based on this computational model, in which event patterns, timing constraints, and the triggered early warning level are expressed in the form of policy rules. The main features of PBSL are its expressiveness, simplicity, practicality, and formal semantics. The formal semantics of the PBSL, together with a model of the mechanisms enforcing the policies, is given in an operational style. Enforcement mechanisms, which are defined by the outcomes of the policy rules, influence the system state by mutually interacting between the policy rules and the system behaviour. We demonstrate the use of this PBSL with a case study from the e-government domain that includes some real-world insider breach scenarios. The formal framework utilises a tool that supports the animation of the enforcement and policy models. This tool also supports the model checking used to formally verify the safety and progress properties of the system over the policy and the enforcement specifications