8 research outputs found

    Cyber Security of Critical Infrastructures

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    Critical infrastructures are vital assets for public safety, economic welfare, and the national security of countries. The vulnerabilities of critical infrastructures have increased with the widespread use of information technologies. As Critical National Infrastructures are becoming more vulnerable to cyber-attacks, their protection becomes a significant issue for organizations as well as nations. The risks to continued operations, from failing to upgrade aging infrastructure or not meeting mandated regulatory regimes, are considered highly significant, given the demonstrable impact of such circumstances. Due to the rapid increase of sophisticated cyber threats targeting critical infrastructures with significant destructive effects, the cybersecurity of critical infrastructures has become an agenda item for academics, practitioners, and policy makers. A holistic view which covers technical, policy, human, and behavioural aspects is essential to handle cyber security of critical infrastructures effectively. Moreover, the ability to attribute crimes to criminals is a vital element of avoiding impunity in cyberspace. In this book, both research and practical aspects of cyber security considerations in critical infrastructures are presented. Aligned with the interdisciplinary nature of cyber security, authors from academia, government, and industry have contributed 13 chapters. The issues that are discussed and analysed include cybersecurity training, maturity assessment frameworks, malware analysis techniques, ransomware attacks, security solutions for industrial control systems, and privacy preservation methods

    Hiding in the Particles: When Return-Oriented Programming Meets Program Obfuscation

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    Largely known for attack scenarios, code reuse techniques at a closer look reveal properties that are appealing also for program obfuscation. We explore the popular return-oriented programming paradigm under this light, transforming program functions into ROP chains that coexist seamlessly with the surrounding software stack. We show how to build chains that can withstand popular static and dynamic deobfuscation approaches, evaluating the robustness and overheads of the design over common programs. The results suggest a significant amount of computational resources would be required to carry a deobfuscation attack for secret finding and code coverage goals.Comment: Published in the proceedings of DSN'21 (51st IEEE/IFIP Int. Conf. on Dependable Systems and Networks). Code and BibTeX entry available at https://github.com/pietroborrello/raindro

    Automating Cyber Analytics

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    Model based security metrics are a growing area of cyber security research concerned with measuring the risk exposure of an information system. These metrics are typically studied in isolation, with the formulation of the test itself being the primary finding in publications. As a result, there is a flood of metric specifications available in the literature but a corresponding dearth of analyses verifying results for a given metric calculation under different conditions or comparing the efficacy of one measurement technique over another. The motivation of this thesis is to create a systematic methodology for model based security metric development, analysis, integration, and validation. In doing so we hope to fill a critical gap in the way we view and improve a system’s security. In order to understand the security posture of a system before it is rolled out and as it evolves, we present in this dissertation an end to end solution for the automated measurement of security metrics needed to identify risk early and accurately. To our knowledge this is a novel capability in design time security analysis which provides the foundation for ongoing research into predictive cyber security analytics. Modern development environments contain a wealth of information in infrastructure-as-code repositories, continuous build systems, and container descriptions that could inform security models, but risk evaluation based on these sources is ad-hoc at best, and often simply left until deployment. Our goal in this work is to lay the groundwork for security measurement to be a practical part of the system design, development, and integration lifecycle. In this thesis we provide a framework for the systematic validation of the existing security metrics body of knowledge. In doing so we endeavour not only to survey the current state of the art, but to create a common platform for future research in the area to be conducted. We then demonstrate the utility of our framework through the evaluation of leading security metrics against a reference set of system models we have created. We investigate how to calibrate security metrics for different use cases and establish a new methodology for security metric benchmarking. We further explore the research avenues unlocked by automation through our concept of an API driven S-MaaS (Security Metrics-as-a-Service) offering. We review our design considerations in packaging security metrics for programmatic access, and discuss how various client access-patterns are anticipated in our implementation strategy. Using existing metric processing pipelines as reference, we show how the simple, modular interfaces in S-MaaS support dynamic composition and orchestration. Next we review aspects of our framework which can benefit from optimization and further automation through machine learning. First we create a dataset of network models labeled with the corresponding security metrics. By training classifiers to predict security values based only on network inputs, we can avoid the computationally expensive attack graph generation steps. We use our findings from this simple experiment to motivate our current lines of research into supervised and unsupervised techniques such as network embeddings, interaction rule synthesis, and reinforcement learning environments. Finally, we examine the results of our case studies. We summarize our security analysis of a large scale network migration, and list the friction points along the way which are remediated by this work. We relate how our research for a large-scale performance benchmarking project has influenced our vision for the future of security metrics collection and analysis through dev-ops automation. We then describe how we applied our framework to measure the incremental security impact of running a distributed stream processing system inside a hardware trusted execution environment

    Transforming malicious code to ROP gadgets for antivirus evasion

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    This study advances research in offensive technology by proposing return oriented programming (ROP) as a means to achieve code obfuscation. The key inspiration is that ROP's unique structure poses various challenges to malware analysis compared to traditional shellcode inspection and detection. The proposed ROP-based attack vector provides two unique features: (i) the ability to automatically analyse and generate equivalent ROP chains for a given code, and (ii) the ability to reuse legitimate code found in an executable in the form of ROP gadgets. To this end, a software tool named ROPInjector was developed which, given any piece of shellcode and any legitimate executable file, it transforms the shellcode to its ROP equivalent re-using the available code in the executable and finally patches the ROP chain infecting the executable. After trying various combinations of evasion techniques, the results show that ROPInjector can evade nearly and completely all antivirus software employed in the online VirusTotal service, making ROP an effective ingredient for code obfuscation. This attack vector poses a serious threat which malicious actors can take advantage to perform cyber-attack campaigns. © The Institution of Engineering and Technology 201

    Factors Influencing Customer Satisfaction towards E-shopping in Malaysia

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    Online shopping or e-shopping has changed the world of business and quite a few people have decided to work with these features. What their primary concerns precisely and the responses from the globalisation are the competency of incorporation while doing their businesses. E-shopping has also increased substantially in Malaysia in recent years. The rapid increase in the e-commerce industry in Malaysia has created the demand to emphasize on how to increase customer satisfaction while operating in the e-retailing environment. It is very important that customers are satisfied with the website, or else, they would not return. Therefore, a crucial fact to look into is that companies must ensure that their customers are satisfied with their purchases that are really essential from the ecommerce’s point of view. With is in mind, this study aimed at investigating customer satisfaction towards e-shopping in Malaysia. A total of 400 questionnaires were distributed among students randomly selected from various public and private universities located within Klang valley area. Total 369 questionnaires were returned, out of which 341 questionnaires were found usable for further analysis. Finally, SEM was employed to test the hypotheses. This study found that customer satisfaction towards e-shopping in Malaysia is to a great extent influenced by ease of use, trust, design of the website, online security and e-service quality. Finally, recommendations and future study direction is provided. Keywords: E-shopping, Customer satisfaction, Trust, Online security, E-service quality, Malaysia

    Identifying Code Injection and Reuse Payloads In Memory Error Exploits

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    Today's most widely exploited applications are the web browsers and document readers we use every day. The immediate goal of these attacks is to compromise target systems by executing a snippet of malicious code in the context of the exploited application. Technical tactics used to achieve this can be classified as either code injection - wherein malicious instructions are directly injected into the vulnerable program - or code reuse, where bits of existing program code are pieced together to form malicious logic. In this thesis, I present a new code reuse strategy that bypasses existing and up-and-coming mitigations, and two methods for detecting attacks by identifying the presence of code injection or reuse payloads. Fine-grained address space layout randomization efficiently scrambles program code, limiting one's ability to predict the location of useful instructions to construct a code reuse payload. To expose the inadequacy of this exploit mitigation, a technique for "just-in-time" exploitation is developed. This new technique maps memory on-the-fly and compiles a code reuse payload at runtime to ensure it works in a randomized application. The attack also works in face of all other widely deployed mitigations, as demonstrated with a proof-of-concept attack against Internet Explorer 10 in Windows 8. This motivates the need for detection of such exploits rather than solely relying on prevention. Two new techniques are presented for detecting attacks by identifying the presence of a payload. Code reuse payloads are identified by first taking a memory snapshot of the target application, then statically profiling the memory for chains of code pointers that reuse code to implement malicious logic. Code injection payloads are identified with runtime heuristics by leveraging hardware virtualization for efficient sandboxed execution of all buffers in memory. Employing both detection methods together to scan program memory takes about a second and produces negligible false positives and false negatives provided that the given exploit is functional and triggered in the target application version. Compared to other strategies, such as the use of signatures, this approach requires relatively little effort spent on maintenance over time and is capable of detecting never before seen attacks. Moving forward, one could use these contributions to form the basis of a unique and effective network intrusion detection system (NIDS) to augment existing systems.Doctor of Philosoph
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