An SEC 10-K XML Schema Extension to Extract Cyber Security Risks

The text sections of the SEC mandated annual reports abound with important corporate operational information but they are hard to manipulate in bulk because of the varying formats used by the submitting companies. Researchers and private entities have demonstrated the difficulties inherent in extracting and accumulating certain textual portions of these reports. This paper proposes an XML schema that will follow a specific DTD for the 10-K (and 10-Q) reports. Using simple computer commands, the ease of manipulation of the reports text sections is demonstrated

Cyber-Storms Come from Clouds: Security of Cloud Computing in the IoT Era

The Internet of Things (IoT) is rapidly changing our society to a world where every "thing" is connected to the Internet, making computing pervasive like never before. This tsunami of connectivity and data collection relies more and more on the Cloud, where data analytics and intelligence actually reside. Cloud computing has indeed revolutionized the way computational resources and services can be used and accessed, implementing the concept of utility computing whose advantages are undeniable for every business. However, despite the benefits in terms of flexibility, economic savings, and support of new services, its widespread adoption is hindered by the security issues arising with its usage. From a security perspective, the technological revolution introduced by IoT and Cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. While the literature mostly focuses on security of IoT and Cloud computing as separate entities, in this article we provide an up-to-date and well-structured survey of the security issues of Cloud computing in the IoT era. We give a clear picture of where security issues occur and what their potential impact is. As a result, we claim that it is not enough to secure IoT devices, as cyber-storms come from Clouds

A Relevance Model for Threat-Centric Ranking of Cybersecurity Vulnerabilities

The relentless and often haphazard process of tracking and remediating vulnerabilities is a top concern for cybersecurity professionals. The key challenge they face is trying to identify a remediation scheme specific to in-house, organizational objectives. Without a strategy, the result is a patchwork of fixes applied to a tide of vulnerabilities, any one of which could be the single point of failure in an otherwise formidable defense. This means one of the biggest challenges in vulnerability management relates to prioritization. Given that so few vulnerabilities are a focus of real-world attacks, a practical remediation strategy is to identify vulnerabilities likely to be exploited and focus efforts towards remediating those vulnerabilities first. The goal of this research is to demonstrate that aggregating and synthesizing readily accessible, public data sources to provide personalized, automated recommendations that an organization can use to prioritize its vulnerability management strategy will offer significant improvements over what is currently realized using the Common Vulnerability Scoring System (CVSS). We provide a framework for vulnerability management specifically focused on mitigating threats using adversary criteria derived from MITRE ATT&CK. We identify the data mining steps needed to acquire, standardize, and integrate publicly available cyber intelligence data sets into a robust knowledge graph from which stakeholders can infer business logic related to known threats. We tested our approach by identifying vulnerabilities in academic and common software associated with six universities and four government facilities. Ranking policy performance was measured using the Normalized Discounted Cumulative Gain (nDCG). Our results show an average 71.5% to 91.3% improvement towards the identification of vulnerabilities likely to be targeted and exploited by cyber threat actors. The ROI of patching using our policies resulted in a savings in the range of 23.3% to 25.5% in annualized unit costs. Our results demonstrate the efficiency of creating knowledge graphs to link large data sets to facilitate semantic queries and create data-driven, flexible ranking policies. Additionally, our framework uses only open standards, making implementation and improvement feasible for cyber practitioners and academia

Web application penetration testing: an analysis of a corporate application according to OWASP guidelines

During the past decade, web applications have become the most prevalent way for service delivery over the Internet. As they get deeply embedded in business activities and required to support sophisticated functionalities, the design and implementation are becoming more and more complicated. The increasing popularity and complexity make web applications a primary target for hackers on the Internet. According to Internet Live Stats up to February 2019, there is an enormous amount of websites being attacked every day, causing both direct and significant impact on huge amount of people. Even with support from security specialist, they continue having troubles due to the complexity of penetration procedures and the vast amount of testing case in both penetration testing and code reviewing. As a result, the number of hacked websites per day is increasing. The goal of this thesis is to summarize the most common and critical vulnerabilities that can be found in a web application, provide a detailed description of them, how they could be exploited and how a cybersecurity tester can find them through the process of penetration testing. To better understand the concepts exposed, there will be also a description of a case of study: a penetration test performed over a company's web application

A methodology to take account of diversity in collective adaptive system

Collective Adaptive Systems (CASs) are comprised of a heterogeneous set of components often developed in a distributed manner. Their users are diverse with respect to their profiles, preferences, interests and goals, and hence, have different requirements. We propose a typology for the diversity of these components, users, and their requirements. We then present a methodology which provides steps to integrate features that record diversity to support accountability. The foundation of accountability is provided by provenance data, and a CAS vocabulary, these knowledge representation languages provide the core vocabulary that can be exploited by agents and services

Security Management Framework for the Internet of Things

The increase in the design and development of wireless communication technologies offers multiple opportunities for the management and control of cyber-physical systems with connections between smart and autonomous devices, which provide the delivery of simplified data through the use of cloud computing. Given this relationship with the Internet of Things (IoT), it established the concept of pervasive computing that allows any object to communicate with services, sensors, people, and objects without human intervention. However, the rapid growth of connectivity with smart applications through autonomous systems connected to the internet has allowed the exposure of numerous vulnerabilities in IoT systems by malicious users. This dissertation developed a novel ontology-based cybersecurity framework to improve security in IoT systems using an ontological analysis to adapt appropriate security services addressed to threats. The composition of this proposal explores two approaches: (1) design time, which offers a dynamic method to build security services through the application of a methodology directed to models considering existing business processes; and (2) execution time, which involves monitoring the IoT environment, classifying vulnerabilities and threats, and acting in the environment, ensuring the correct adaptation of existing services. The validation approach was used to demonstrate the feasibility of implementing the proposed cybersecurity framework. It implies the evaluation of the ontology to offer a qualitative evaluation based on the analysis of several criteria and also a proof of concept implemented and tested using specific industrial scenarios. This dissertation has been verified by adopting a methodology that follows the acceptance in the research community through technical validation in the application of the concept in an industrial setting.O aumento no projeto e desenvolvimento de tecnologias de comunicação sem fio oferece múltiplas oportunidades para a gestão e controle de sistemas ciber-físicos com conexões entre dispositivos inteligentes e autônomos, os quais proporcionam a entrega de dados simplificados através do uso da computação em nuvem. Diante dessa relação com a Internet das Coisas (IoT) estabeleceu-se o conceito de computação pervasiva que permite que qualquer objeto possa comunicar com os serviços, sensores, pessoas e objetos sem intervenção humana. Entretanto, o rápido crescimento da conectividade com as aplicações inteligentes através de sistemas autônomos conectados com a internet permitiu a exposição de inúmeras vulnerabilidades dos sistemas IoT para usuários maliciosos. Esta dissertação desenvolveu um novo framework de cibersegurança baseada em ontologia para melhorar a segurança em sistemas IoT usando uma análise ontológica para a adaptação de serviços de segurança apropriados endereçados para as ameaças. A composição dessa proposta explora duas abordagens: (1) tempo de projeto, o qual oferece um método dinâmico para construir serviços de segurança através da aplicação de uma metodologia dirigida a modelos, considerando processos empresariais existentes; e (2) tempo de execução, o qual envolve o monitoramento do ambiente IoT, a classificação de vulnerabilidades e ameaças, e a atuação no ambiente garantindo a correta adaptação dos serviços existentes. Duas abordagens de validação foram utilizadas para demonstrar a viabilidade da implementação do framework de cibersegurança proposto. Isto implica na avaliação da ontologia para oferecer uma avaliação qualitativa baseada na análise de diversos critérios e também uma prova de conceito implementada e testada usando cenários específicos. Esta dissertação foi validada adotando uma metodologia que segue a validação na comunidade científica através da validação técnica na aplicação do nosso conceito em um cenário industrial

Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations

As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the in-time aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance

Augmenting security event information with contextual data to improve the detection capabilities of a SIEM

The increasing number of cyber security breaches have revealed a need for proper cyber security measures. The emergence of the internet and the increase in overall connectivity means that data is more easily accessible and available. Using the available data in a security context may provide a system with an external contextual insight such as environmental awareness or current affair awareness. A security information and event management (SIEM) system is a security system that correlates security event information from surrounding systems and decides whether the surrounding environment (possibly an enterprise's network) is vulnerable or even under attack by a malicious person whether they be internal (authorised) or external (unauthorised). In this thesis, the aim is to provide such a system with con- text by adding non-security related information from surrounding available sources known as context information feeds. Contextual information feeds are added to the SIEM and tested using randomised events. There are various context information types used in this thesis, namely: social media, meteorological, calendar information and terror threat level. The SIEM is tested with each contextual data feed active and the results are recorded. The testing shows that the addition of contextual data feeds actively affects the sensitivity of OSSIM and hence results in higher alarms raised during elevated context triggered states. The system showed a greater and deeper visibility of its surrounding environment and hence an improved detection capability

Self-reconfigurable, intrusion-tolerant, web-service composition framework

The Internet has provided an opportunity for businesses to offer their services as Web Services (WSs). WSs are used to implement Service Ori-ented Architecture (SOA). They enable composition of independent services with complementary functionalities to produce value-added services, which results in less development effort, time consumption and cost, enabling com-panies and organizations to implement their core business only and out-source other service components over the Internet, either pre-selected or on-the-fly. Simple Object Access Protocol (SOAP) based WSs are at risk of se-curity vulnerabilities related to their specific implementation technologies such as Extensible Markup Language (XML) as well as those of their under-lying platforms (e.g., operating systems and frameworks) and their applica-tions (e.g., vulnerability to SQL Injection attacks). Cyber-attacks on WSs may cause unavailability, loss of confidentiality and/or integrity as well as signifi-cant monetary penalties. Security issues become more challenging when Off-The-Shelf Web Services (OTSWSs) are used since they are beyond the con-trol of their clients. The central question underlying this work is: Can a self-reconfigurable Intrusion-Tolerant Web Ser-vice, implemented using N-version programming and diversity formed by composing Off-The-Shelf Web Services that are selected through penetration testing, Principal Component Analysis, and Cluster Analysis process-es mitigate XML-related security vulnerabilities? While aiming to answer the above question, this dissertation presents a novel framework to increase dependability by constructing an Intrusion-Tolerant Web Service (ITWS) in which N-version programming and diversity, formed by composing SOAP-OTSWSs, is used. It describes how penetration testing can be used as a measure of security vulnerabilities of available SOAP-OTSWSs (that offer the required functionality) and the resultant ITWS, how Principal Component Analysis (PCA) and Cluster Analysis (CA) and be utilized to group the SOAP-OTSWSs based on their security vulnerabilities diversity and how a further penetration testing on each group of diverse SOAP-OTSWSs can be used to select the optimal set (most secure among the groups) for construction of ITWS. This dissertation also demonstrates how the dynamic reconfiguration of ITWS, created in Business Process Engineering Language (BPEL), can be enabled using a combination of BPEL constructs and Java as BPEL exten-sion approach and using only Java as BPEL extension approach. The novelty of the work presented in this dissertation is twofold. On the one hand, it is security informed and on the other hand, it demonstrates the use of Java (as BPEL 2.0 extension) to implement self-reconfigurable composite WS. It has the advantage of, at the same time, facilitating a de-pendable service to users and exploiting existing standard technologies. This work also assesses the effectiveness of the proposed solutions through vari-ous case studies and discusses the implications of the proposed framework