The master’s thesis deals with the management of cyber security in a manufacturing company. The theoretical part contains concepts and knowledge of cyber security and discusses the current requirements of legislation and standards of the ISO/IEC 27000 series. In practical part are proposed measures to increase cyber security and information security based on the theoretical background and analysis of current state in the selected company.

Master thesis is concerned with assessing the state of information security and its use as an indicator of corporate performance in energy company. Chapter analysis of the problem and current situation presents findings on the state of information security and implementation stage of ISMS. The practical part is focused on risk analysis and assessment the maturity level of processes, which are submitted as the basis for the proposed security measures and recommendations. There are also designed metrics to measure level of information security.

This diploma thesis focuses on human resources mainly in Critical information infrastructure and Important information systems. Thesis focuses on the most frequent threats for users and design possible model of threat reduction. Integral part of results is designing of effective security awareness education program according to the Law on Cyber Security.

The master’s thesis focuses on GAP analysis of information security management system. The thesis consists of theoretical, analytical and practical part. The first part discusses the theoretical background of the issue of information and cyber security. The analytical part describes the current condition of the researched company. The thesis’s output is the draft of risk register and draft of security countermeasures implementation. The draft targets on countermeasures leading to increase information security in company.

The master‘s thesis is focused on security audit. The aim of this thesis is to create methodology, which might help with creating security audits and research current condition of cybernetic and information security in a business establishment. Theoretical part explains basic terms and concepts about cyber and information security. Own interpretation consist description of methodological areas of security audit.

This diploma thesis deals with the management of security information, according to ISO/IEC 27005 and it is implementation in the Verinice software environment. The risk information management process is applied to a critical infrastructure, that is connected to a optical fiber network. The work focuses on incidents aimed at threatening data from optical threats and active network elements in transmission systems. The result of the work is defined as a risk file in the .VNA format containing identified risks, for which appropriate measures are implemented in connection with the requirements of ISO/IEC 27001, for the protection of critical infrastructures and transmitted data in the transmission system.

This diploma thesis deals with a suggestions to improve the current state of education information and cyber security in the Czech Republic. These suggestions are from a comparison of education at the Brno University of Technology - Faculty of Business and Hallym University in South Korea. Another part is the analysis of trends in the field of cyber attacks and comparison of this area between the Czech Republic and South Korea.

MCom (Business Information Systems) / Department of Business Information Systems / Although technology is being progressively used in supporting student learning and enhancing business processes within tertiary institutions, certain aspects are hindering the decisions of cloud usage. Among many challenges of utilizing cloud computing, cybersecurity has become a primary concern for the adoption. The main aim of the study was to investigate the effect of cloud cyber-security usage at rural based tertiary institutions in order to compare the usage with an urban-based institution and propose a cybersecurity framework for adoption of cloud computing cybersecurity. The research questions focused on determining the drivers for cloud cybersecurity usage; the current adoption issues; how cybersecurity challenges, benefits, and quality affects cloud usage; the adoption perceptions and awareness of key stakeholders and identifying a cloud cybersecurity adoption framework. A quantitative approach was applied with data collected from a simple random sample of students, lecturers, admin and IT staff within the tertiary institutions through structured questionnaires. The results suggested compliance with legal law as a critical driver for cloud cybersecurity adoption. The study also found a lack of physical control of data and harmful activities executed on the internet as challenges hampering the adoption. Prevention of identity fraud and cheaper security costs were identified as benefits of adoption. Respondents found cloud cybersecurity to be accurate and effective, although most of the students and employees have not used it. However, respondents were aware of the value of cybersecurity adoption and perceive for it to be useful and convenient, hence have shown the intention of adopting it. There were no significant elements identified to differentiate the perceptions of usage at rural and urban-based tertiary institutions. The results of the study are to be used for clarifying the cybersecurity aspects of cloud computing and forecasting the suitability cloud cybersecurity within the tertiary institutions. Recommendations were made on how tertiary institutions and management can promote cloud cybersecurity adoption and how students, lecturers, and staff can effectively use cloud cybersecurity. / NRF

<div><p>Internet of Things (IoT) systems running on Microcontrollers (MCUS) have become a prominent target of remote attacks. Although deployed in security and safety critical domains, such systems lack basic mitigations against control-flow hijacking attacks. Attacks against IoT systems already enabled malicious takeover of smartphones, vehicles, unmanned aerial vehicles, and industrial control systems.</p></div><div><p> </p><div><p>The thesis introduces a systemic analysis of previous defense mitigations to secure IoT systems. Building off this systematization, we identify two main issues in IoT systems security. First, efforts to protect IoT systems are hindered by the lack of realistic benchmarks and evaluation frameworks. Second, existing solutions to protect from control-flow hijacking on the return edge are either impractical or have limited security guarantees. This thesis addresses these issues using two approaches. </p></div><div><p> </p></div><div><p>First, we present BenchIoT, a benchmark suite of five realistic IoT applications and an evaluation framework that enables automated and extensible evaluation of 14 metrics covering security, performance, memory usage, and energy. BenchIoT enables evaluating and comparing security mechanisms. Using BenchIoT, we show that even if two security mechanisms have similarly modest runtime overhead, one can have undesired consequences on security such as a large portion of privileged user execution.</p></div><div><p> </p></div><div><p>Second, we introduce Return Address Integrity (RAI), a novel security mechanism to prevent all control-flow hijacking attacks targeting return edges, without requiring special hardware. We design and implement μRAI to enforce the RAI property. Our results show μRAI has a low runtime overhead of 0.1% on average, and therefore is a</p></div><div><p>practical solution for IoT systems. </p></div><div><p> </p></div><div><p>This thesis enables measuring the security IoT systems through standardized benchmarks and metrics. Using static analysis and runtime monitors, it prevents control-flow hijacking attacks on return edges with low runtime overhead. Combined, this thesis advances the state-of-the-art of protecting IoT systems and benchmarking its security.</p></div></div>

Today, virtually every company world-wide is connected to the Internet. This wide-spread connectivity has given rise to sophisticated, targeted, Internet-based attacks. For example, between 2012 and 2013 security researchers counted an average of about 74 targeted attacks per day. These attacks are motivated by economical, financial, or political interests and commonly referred to as “Advanced Persistent Threat (APT)” attacks. Unfortunately, many of these attacks are successful and the adversaries manage to steal important data or disrupt vital services. Victims are preferably companies from vital industries, such as banks, defense contractors, or power plants. Given that these industries are well-protected, often employing a team of security specialists, the question is: How can these attacks be so successful? Researchers have identified several properties of APT attacks which make them so efficient. First, they are adaptable. This means that they can change the way they attack and the tools they use for this purpose at any given moment in time. Second, they conceal their actions and communication by using encryption, for example. This renders many defense systems useless as they assume complete access to the actual communication content. Third, their actions are stealthy — either by keeping communication to the bare minimum or by mimicking legitimate users. This makes them “fly below the radar” of defense systems which check for anomalous communication. And finally, with the goal to increase their impact or monetisation prospects, their attacks are targeted against several companies from the same industry. Since months can pass between the first attack, its detection, and comprehensive analysis, it is often too late to deploy appropriate counter-measures at businesses peers. Instead, it is much more likely that they have already been attacked successfully. This thesis tries to answer the question whether the last property (industry-wide attacks) can be used to detect such attacks. It presents the design, implementation and evaluation of a community-based intrusion detection system, capable of protecting businesses at industry-scale. The contributions of this thesis are as follows. First, it presents a novel algorithm for community detection which can detect an industry (e.g., energy, financial, or defense industries) in Internet communication. Second, it demonstrates the design, implementation, and evaluation of a distributed graph mining engine that is able to scale with the throughput of the input data while maintaining an end-to-end latency for updates in the range of a few milliseconds. Third, it illustrates the usage of this engine to detect APT attacks against industries by analyzing IP flow information from an Internet service provider. Finally, it introduces a detection algorithm- and input-agnostic intrusion detection engine which supports not only intrusion detection on IP flow but any other intrusion detection algorithm and data-source as well.