Information Security Risk Management: In Which Security Solutions Is It Worth Investing?

As companies are increasingly exposed to information security threats, decision makers are permanently forced to pay attention to security issues. Information security risk management provides an approach for measuring the security through risk assessment, risk mitigation, and risk evaluation. Although a variety of approaches have been proposed, decision makers lack well-founded techniques that (1) show them what they are getting for their investment, (2) show them if their investment is efficient, and (3) do not demand in-depth knowledge of the IT security domain. This article defines a methodology for management decision makers that effectively addresses these problems. This work involves the conception, design, and implementation of the methodology into a software solution. The results from two qualitative case studies show the advantages of this methodology in comparison to established methodologies

A Security Advisory System for Healthcare Environments

This thesis considers the current requirements for security in European healthcare establishments. Information Technology is being used increasingly by all areas of healthcare, from administration to clinical treatment and this has resulted in increased dependence upon computer systems by healthcare staff. The thesis looks at healthcare security requirements from the European perspective. An aim of the research was to develop security guidelines that could be used by healthcare establishments to implement a common baseline standard for security. These guidelines represent work submitted to the Commission of European Communities SEISMED (Secure Environment for Information Systems in Medicine) project, with which the research programme was closely linked. The guidelines were validated by implementing them with the Plymouth and Torbay Health Trust. The thesis also describes the development of a new management methodology and this was developed to allow the smooth implementation of security within healthcare establishments. The methodology was validated by actually using it within the Plymouth and Torbay Health Authority to implement security countermeasures. A major area of the research was looking at the use of risk analysis and reviewing all the known risk analysis methodologies. The use of risk analysis within healthcare was also considered and the main risk analysis methods used by UK healthcare establishments were reviewed. The thesis explains why there is a need for a risk analysis method specially developed for healthcare. As part of the research a new risk analysis method was developed, this allows healthcare establishments to determine their own security requirements. The method was also combined with the new management methodology that would determine any implementional problems. The risk analysis methodology was developed into a computerised prototype, which demonstrated the different stages of the methodology.Plymouth and Torbay Health Authorit

Ontology in Information Security

The past several years we have witnessed that information has become the most precious asset, while protection and security of information is becoming an ever greater challenge due to the large amount of knowledge necessary for organizations to successfully withstand external threats and attacks. This knowledge collected from the domain of information security can be formally described by security ontologies. A large number of researchers during the last decade have dealt with this issue, and in this paper we have tried to identify, analyze and systematize the relevant papers published in scientific journals indexed in selected scientific databases, in period from 2004 to 2014. This paper gives a review of literature in the field of information security ontology and identifies a total of 52 papers systematized in three groups: general security ontologies (12 papers), specific security ontologies (32 papers) and theoretical works (8 papers). The papers were of different quality and level of detail and varied from presentations of simple conceptual ideas to sophisticated frameworks based on ontology

Cyber-security Risk Assessment

Cyber-security domain is inherently dynamic. Not only does system configuration changes frequently (with new releases and patches), but also new attacks and vulnerabilities are regularly discovered. The threat in cyber-security is human, and hence intelligent in nature. The attacker adapts to the situation, target environment, and countermeasures. Attack actions are also driven by attacker's exploratory nature, thought process, motivation, strategy, and preferences. Current security risk assessment is driven by cyber-security expert's theories about this attacker behavior. The goal of this dissertation is to automatically generate the cyber-security risk scenarios by: * Capturing diverse and dispersed cyber-security knowledge * Assuming that there are unknowns in the cyber-security domain, and new knowledge is available frequently * Emulating the attacker's exploratory nature, thought process, motivation, strategy, preferences and his/her interaction with the target environment * Using the cyber-security expert's theories about attacker behavior The proposed framework is designed by using the unique cyber-security domain requirements identified in this dissertation and by overcoming the limitations of current risk scenario generation frameworks. The proposed framework automates the risk scenario generation by using the knowledge as it becomes available (or changes). It supports observing, encoding, validating, and calibrating cyber-security expert's theories. It can also be used for assisting the red-teaming process. The proposed framework generates ranked attack trees and encodes the attacker behavior theories. These can be used for prioritizing vulnerability remediation. The proposed framework is currently being extended for developing an automated threat response framework that can be used to analyze and recommend countermeasures. This framework contains behavior driven countermeasures that uses the attacker behavior theories to lead the attacker away from the system to be protected

DAG-Based Attack and Defense Modeling: Don't Miss the Forest for the Attack Trees

This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions. Methods based on threat trees and Bayesian networks are two well-known approaches to security modeling. However there exist more than 30 DAG-based methodologies, each having different features and goals. The objective of this survey is to present a complete overview of graphical attack and defense modeling techniques based on DAGs. This consists of summarizing the existing methodologies, comparing their features and proposing a taxonomy of the described formalisms. This article also supports the selection of an adequate modeling technique depending on user requirements

Modeling Security Risks at the System Design Stage Alignment of Mal Activity Diagrams and SecureUML to the ISSRM Domain Model

Turvatehnika disain on üks olulisi süsteemiarenduse komponente. Ta peaks läbima tervet süsteemiarendusprotsessi. Kahjuks pööratakse talle paljudel juhtudel tähelepanu ainult süsteemi arendamise ja haldamise ajal. Paljud turvalise modelleerimise keeled (näiteks Misuse Case, Secure Tropos) aitavad turvariskejuba nõuete analüüsi etapil hallata. Käesolevas magistritöös vaatleme modelleerimisvahendeid (pahateoskeemid ja SecureUML), mida kasutatakse süsteemi disainil. Täpsemalt, me uurime, kuivõrd need vahendid toetavad infosüsteemide turvariskide haldust (Information Systems Security Risks Management, ISSRM). Töö tulemuseks on tabel, mis seab pahateoskeemid ning SecureUML-keele konstruktsioonid ISSRM domeeni mõistetega omavahel vastavusse. Me põhjendame oma analüüsi ning valideerime saadud tulemusi mitmel illustratiivsel näitel. Me loodame, et saadud tulemused aitavad arendajatel paremini aru saada, kuidas turvariske süsteemi disainietapil arvesse võtta. Peale selle, nende keelte analüüs ühisel kontseptuaalsel taustal annab tulevikus võimaluse neid keeli korraga kasutada ning loodud mudeleid ühest keelest teise teisendada.Security engineering is one of the important concerns during system development. It should be addressed throughout the whole system development process; however in many cases it is often dealt only during system development and maintenance. There are several security modeling languages (e.g, Misuse case, Secure Tropos) that help dealing with security risk management at the requirements stage. In this thesis, we are focusing on the modeling languages (e.g. Mal activity diagrams and SecureUML) that are used to design the system. More specifically we investigate how these languages support information systems security risks management (ISSRM). The outcome of this work is an alignment table between the Mal activity diagrams and SecureUML language constructs to the ISSRM domain model concepts. We ground our analysis and validate the received results on the number of illustrative examples. We hope that our results will help developers to understand how they can consider security risks at the system design stage. In addition we open the way for the interoperability between different modeling languages that are analysed using the same conceptual background, thus, potentially leading to the transformation between these modeling approaches

Viiteraamistik turvariskide haldamiseks plokiahela abil

Turvalise tarkvara loomiseks on olemas erinevad programmid (nt OWASP), ohumudelid (nt STRIDE), turvariskide juhtimise mudelid (nt ISSRM) ja eeskirjad (nt GDPR). Turvaohud aga arenevad pidevalt, sest traditsiooniline tehnoloogiline infrastruktuur ei rakenda turvameetmeid kavandatult. Blockchain näib leevendavat traditsiooniliste rakenduste turvaohte. Kuigi plokiahelapõhiseid rakendusi peetakse vähem haavatavateks, ei saanud need erinevate turvaohtude eest kaitsmise hõbekuuliks. Lisaks areneb plokiahela domeen pidevalt, pakkudes uusi tehnikaid ja sageli vahetatavaid disainikontseptsioone, mille tulemuseks on kontseptuaalne ebaselgus ja segadus turvaohtude tõhusal käsitlemisel. Üldiselt käsitleme traditsiooniliste rakenduste TJ-e probleemi, kasutades vastumeetmena plokiahelat ja plokiahelapõhiste rakenduste TJ-t. Alustuseks uurime, kuidas plokiahel leevendab traditsiooniliste rakenduste turvaohte, ja tulemuseks on plokiahelapõhine võrdlusmudel (PV), mis järgib TJ-e domeenimudelit. Järgmisena esitleme PV-it kontseptualiseerimisega alusontoloogiana kõrgema taseme võrdlusontoloogiat (ULRO). Pakume ULRO kahte eksemplari. Esimene eksemplar sisaldab Cordat, kui lubatud plokiahelat ja finantsjuhtumit. Teine eksemplar sisaldab lubadeta plokiahelate komponente ja tervishoiu juhtumit. Mõlemad ontoloogiaesitlused aitavad traditsiooniliste ja plokiahelapõhiste rakenduste TJ-es. Lisaks koostasime veebipõhise ontoloogia parsimise tööriista OwlParser. Kaastööde tulemusel loodi ontoloogiapõhine turberaamistik turvariskide haldamiseks plokiahela abil. Raamistik on dünaamiline, toetab TJ-e iteratiivset protsessi ja potentsiaalselt vähendab traditsiooniliste ja plokiahelapõhiste rakenduste turbeohte.Various programs (e.g., OWASP), threat models (e.g., STRIDE), security risk management models (e.g., ISSRM), and regulations (e.g., GDPR) exist to communicate and reduce the security threats to build secure software. However, security threats continuously evolve because the traditional technology infrastructure does not implement security measures by design. Blockchain is appearing to mitigate traditional applications’ security threats. Although blockchain-based applications are considered less vulnerable, they did not become the silver bullet for securing against different security threats. Moreover, the blockchain domain is constantly evolving, providing new techniques and often interchangeable design concepts, resulting in conceptual ambiguity and confusion in treating security threats effectively. Overall, we address the problem of traditional applications’ SRM using blockchain as a countermeasure and the SRM of blockchain-based applications. We start by surveying how blockchain mitigates the security threats of traditional applications, and the outcome is a blockchain-based reference model (BbRM) that adheres to the SRM domain model. Next, we present an upper-level reference ontology (ULRO) as a foundation ontology and provide two instantiations of the ULRO. The first instantiation includes Corda as a permissioned blockchain and the financial case. The second instantiation includes the permissionless blockchain components and the healthcare case. Both ontology representations help in the SRM of traditional and blockchain-based applications. Furthermore, we built a web-based ontology parsing tool, OwlParser. Contributions resulted in an ontology-based security reference framework for managing security risks using blockchain. The framework is dynamic, supports the iterative process of SRM, and potentially lessens the security threats of traditional and blockchain-based applications.https://www.ester.ee/record=b551352

Matching Possible Mitigations to Cyber Threats: A Document-Driven Decision Support Systems Approach

Cyber systems are ubiquitous in all aspects of society. At the same time, breaches to cyber systems continue to be front-page news (Calfas, 2018; Equifax, 2017) and, despite more than a decade of heightened focus on cybersecurity, the threat continues to evolve and grow, costing globally up to $575 billion annually (Center for Strategic and International Studies, 2014; Gosler & Von Thaer, 2013; Microsoft, 2016; Verizon, 2017). To address possible impacts due to cyber threats, information system (IS) stakeholders must assess the risks they face. Following a risk assessment, the next step is to determine mitigations to counter the threats that pose unacceptably high risks. The literature contains a robust collection of studies on optimizing mitigation selections, but they universally assume that the starting list of appropriate mitigations for specific threats exists from which to down-select. In current practice, producing this starting list is largely a manual process and it is challenging because it requires detailed cybersecurity knowledge from highly decentralized sources, is often deeply technical in nature, and is primarily described in textual form, leading to dependence on human experts to interpret the knowledge for each specific context. At the same time cybersecurity experts remain in short supply relative to the demand, while the delta between supply and demand continues to grow (Center for Cyber Safety and Education, 2017; Kauflin, 2017; Libicki, Senty, & Pollak, 2014). Thus, an approach is needed to help cybersecurity experts (CSE) cut through the volume of available mitigations to select those which are potentially viable to offset specific threats. This dissertation explores the application of machine learning and text retrieval techniques to automate matching of relevant mitigations to cyber threats, where both are expressed as unstructured or semi-structured English language text. Using the Design Science Research Methodology (Hevner & March, 2004; Peffers, Tuunanen, Rothenberger, & Chatterjee, 2007), we consider a number of possible designs for the matcher, ultimately selecting a supervised machine learning approach that combines two techniques: support vector machine classification and latent semantic analysis. The selected approach demonstrates high recall for mitigation documents in the relevant class, bolstering confidence that potentially viable mitigations will not be overlooked. It also has a strong ability to discern documents in the non-relevant class, allowing approximately 97% of non-relevant mitigations to be excluded automatically, greatly reducing the CSE’s workload over purely manual matching. A false v positive rate of up to 3% prevents totally automated mitigation selection and requires the CSE to reject a few false positives. This research contributes to theory a method for automatically mapping mitigations to threats when both are expressed as English language text documents. This artifact represents a novel machine learning approach to threat-mitigation mapping. The research also contributes an instantiation of the artifact for demonstration and evaluation. From a practical perspective the artifact benefits all threat-informed cyber risk assessment approaches, whether formal or ad hoc, by aiding decision-making for cybersecurity experts whose job it is to mitigate the identified cyber threats. In addition, an automated approach makes mitigation selection more repeatable, facilitates knowledge reuse, extends the reach of cybersecurity experts, and is extensible to accommodate the continued evolution of both cyber threats and mitigations. Moreover, the selection of mitigations applicable to each threat can serve as inputs into multifactor analyses of alternatives, both automated and manual, thereby bridging the gap between cyber risk assessment and final mitigation selection

Security Risk Management for the IoT systems

Alates 2012. aastast on ülemaailmne infastruktuuri üksuste arv (The Internet of Things) jõudsalt kasvanud üle kahe korra. Koos selle numbriga on ka kasvanud ka võimalikud riskid ning ohud, mis mõjutavad süsteemi turvalisust. Tulemuseks on suur hulk isiklikke andmeid kas varastatud või kahjustatud. Vastavalt allikatele "Third Quarter, 2016 State of the Internet / Security Report" ja "Akamai Intelligent Platform", on DdoS Q3 rünnakute arv suurenenud 2016 aastal 71% võrreldes aastaga 2015. Kõige suurem DdoS fikseeritud rünnakutest oli 623 Gbps rünnak. Kõik need faktid tõestavad, et Iot süsteemis on veel siiamaani probleeme isikuandmete turvalisusega. Isklikud andmed on ohtude suhtes haavatavad. Käesolev töö ühendab Iot raamastikus turvalisuse riskijuhtimine teadmised olemasoleva praktikaga. Raamastiku eesmärgiks on tugevdada Iot süsteemi nõrku osi ning kaitsta isiklikke andmeid. Pakume välja esialgse igakülgse võrdlusmudeli juhtkontrolli turvariskideks IoT süsteemides hallatavate ja kontrollitavate info- ja andmevarade jaoks. Infosüsteemide turvalisuse riskijuhtimise valdkonna domeeni mudeli põhjal uurime, kuidas avatud veebirakenduse turvalisuse projektis määratletud turvaauke ja nende vastumeetmeid võiks vaadelda IoT kontekstis. Selleks, et illustreerida etalonmudeli rakendamist, katsetatakse raamistikku IoT-süsteemil. Sellesse süsteemi kuuluvad Raspberry Pi 3, sensorid ning kaugandmete ladustamine.Since 2012 the number of units in global infrastructure for the information society (The Internet of Things) has grown twice. With this number also has grown the number of possible threats and risks, which influence security on all levels of the system. As a result, a huge amount of users' data was stolen or damaged. According to Third Quarter, 2016 State of the Internet / Security Report based on data gathered from the Akamai Intelligent Platform the total number of DDoS attacks in Q3 2016 increased in 71\\% compared to Q3 2015. With 623 Gbps data transfer attack it was largest DDoS ever and this fact will only increase the number of future attack events. All these facts reveal a problem that a lot of IoT systems are still unsecured and users' data or personal information stay vulnerable to threats. The thesis combines knowledge of Security Risk Management with existing practice in securing in IoT into a framework, which aim is to cover vulnerabilities in IoT systems in order to protect users' data. We propose an initial comprehensive reference model to management security risks to the information and data assets managed and controlled in the IoT systems. Based on the domain model for the information systems security risk management, we explore how the vulnerabilities and their countermeasures defined in the open Web application security project could be considered in the IoT context. To illustrate the applicability of the reference model we test the framework on self-developed IoT system represented by Raspberry Pi 3 interconnected with sensors and remote data storage