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name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option value="msc_class">MSC classification</option><option value="report_num">Report number</option><option value="paper_id">arXiv identifier</option><option value="doi">DOI</option><option value="orcid">ORCID</option><option value="license">License (URI)</option><option value="author_id">arXiv author ID</option><option value="help">Help pages</option><option value="full_text">Full text</option></select> <input id="query" name="query" type="text" value="Islam, C"> <ul id="abstracts"><li><input checked id="abstracts-0" name="abstracts" type="radio" value="show"> <label for="abstracts-0">Show abstracts</label></li><li><input id="abstracts-1" name="abstracts" type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2503.00324">arXiv:2503.00324</a> <span> [<a href="https://arxiv.org/pdf/2503.00324">pdf</a>, <a href="https://arxiv.org/format/2503.00324">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> </div> </div> <p class="title is-5 mathjax"> DySec: A Machine Learning-based Dynamic Analysis for Detecting Malicious Packages in PyPI Ecosystem </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Mehedi%2C+S+T">Sk Tanzir Mehedi</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+C">Chadni Islam</a>, <a href="/search/cs?searchtype=author&query=Ramachandran%2C+G">Gowri Ramachandran</a>, <a href="/search/cs?searchtype=author&query=Jurdak%2C+R">Raja Jurdak</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2503.00324v1-abstract-short" style="display: inline;"> Malicious Python packages make software supply chains vulnerable by exploiting trust in open-source repositories like Python Package Index (PyPI). Lack of real-time behavioral monitoring makes metadata inspection and static code analysis inadequate against advanced attack strategies such as typosquatting, covert remote access activation, and dynamic payload generation. To address these challenges,… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2503.00324v1-abstract-full').style.display = 'inline'; document.getElementById('2503.00324v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2503.00324v1-abstract-full" style="display: none;"> Malicious Python packages make software supply chains vulnerable by exploiting trust in open-source repositories like Python Package Index (PyPI). Lack of real-time behavioral monitoring makes metadata inspection and static code analysis inadequate against advanced attack strategies such as typosquatting, covert remote access activation, and dynamic payload generation. To address these challenges, we introduce DySec, a machine learning (ML)-based dynamic analysis framework for PyPI that uses eBPF kernel and user-level probes to monitor behaviors during package installation. By capturing 36 real-time features-including system calls, network traffic, resource usage, directory access, and installation patterns-DySec detects threats like typosquatting, covert remote access activation, dynamic payload generation, and multiphase attack malware. We developed a comprehensive dataset of 14,271 Python packages, including 7,127 malicious sample traces, by executing them in a controlled isolated environment. Experimental results demonstrate that DySec achieves a 95.99\% detection accuracy with a latency of <0.5s, reducing false negatives by 78.65\% compared to static analysis and 82.24\% compared to metadata analysis. During the evaluation, DySec flagged 11 packages that PyPI classified as benign. A manual analysis, including installation behavior inspection, confirmed six of them as malicious. These findings were reported to PyPI maintainers, resulting in the removal of four packages. DySec bridges the gap between reactive traditional methods and proactive, scalable threat mitigation in open-source ecosystems by uniquely detecting malicious install-time behaviors. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2503.00324v1-abstract-full').style.display = 'none'; document.getElementById('2503.00324v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 28 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2025. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2502.07905">arXiv:2502.07905</a> <span> [<a href="https://arxiv.org/pdf/2502.07905">pdf</a>, <a href="https://arxiv.org/format/2502.07905">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> DeepSeek on a Trip: Inducing Targeted Visual Hallucinations via Representation Vulnerabilities </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Islam%2C+C+M">Chashi Mahiul Islam</a>, <a href="/search/cs?searchtype=author&query=Chacko%2C+S+J">Samuel Jacob Chacko</a>, <a href="/search/cs?searchtype=author&query=Horne%2C+P">Preston Horne</a>, <a href="/search/cs?searchtype=author&query=Liu%2C+X">Xiuwen Liu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2502.07905v1-abstract-short" style="display: inline;"> Multimodal Large Language Models (MLLMs) represent the cutting edge of AI technology, with DeepSeek models emerging as a leading open-source alternative offering competitive performance to closed-source systems. While these models demonstrate remarkable capabilities, their vision-language integration mechanisms introduce specific vulnerabilities. We implement an adapted embedding manipulation atta… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.07905v1-abstract-full').style.display = 'inline'; document.getElementById('2502.07905v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2502.07905v1-abstract-full" style="display: none;"> Multimodal Large Language Models (MLLMs) represent the cutting edge of AI technology, with DeepSeek models emerging as a leading open-source alternative offering competitive performance to closed-source systems. While these models demonstrate remarkable capabilities, their vision-language integration mechanisms introduce specific vulnerabilities. We implement an adapted embedding manipulation attack on DeepSeek Janus that induces targeted visual hallucinations through systematic optimization of image embeddings. Through extensive experimentation across COCO, DALL-E 3, and SVIT datasets, we achieve hallucination rates of up to 98.0% while maintaining high visual fidelity (SSIM > 0.88) of the manipulated images on open-ended questions. Our analysis demonstrates that both 1B and 7B variants of DeepSeek Janus are susceptible to these attacks, with closed-form evaluation showing consistently higher hallucination rates compared to open-ended questioning. We introduce a novel multi-prompt hallucination detection framework using LLaMA-3.1 8B Instruct for robust evaluation. The implications of these findings are particularly concerning given DeepSeek's open-source nature and widespread deployment potential. This research emphasizes the critical need for embedding-level security measures in MLLM deployment pipelines and contributes to the broader discussion of responsible AI implementation. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.07905v1-abstract-full').style.display = 'none'; document.getElementById('2502.07905v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2025. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">19 pages, 4 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2502.04679">arXiv:2502.04679</a> <span> [<a href="https://arxiv.org/pdf/2502.04679">pdf</a>, <a href="https://arxiv.org/format/2502.04679">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Mechanistic Understandings of Representation Vulnerabilities and Engineering Robust Vision Transformers </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Islam%2C+C+M">Chashi Mahiul Islam</a>, <a href="/search/cs?searchtype=author&query=Chacko%2C+S+J">Samuel Jacob Chacko</a>, <a href="/search/cs?searchtype=author&query=Nishino%2C+M">Mao Nishino</a>, <a href="/search/cs?searchtype=author&query=Liu%2C+X">Xiuwen Liu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2502.04679v1-abstract-short" style="display: inline;"> While transformer-based models dominate NLP and vision applications, their underlying mechanisms to map the input space to the label space semantically are not well understood. In this paper, we study the sources of known representation vulnerabilities of vision transformers (ViT), where perceptually identical images can have very different representations and semantically unrelated images can hav… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.04679v1-abstract-full').style.display = 'inline'; document.getElementById('2502.04679v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2502.04679v1-abstract-full" style="display: none;"> While transformer-based models dominate NLP and vision applications, their underlying mechanisms to map the input space to the label space semantically are not well understood. In this paper, we study the sources of known representation vulnerabilities of vision transformers (ViT), where perceptually identical images can have very different representations and semantically unrelated images can have the same representation. Our analysis indicates that imperceptible changes to the input can result in significant representation changes, particularly in later layers, suggesting potential instabilities in the performance of ViTs. Our comprehensive study reveals that adversarial effects, while subtle in early layers, propagate and amplify through the network, becoming most pronounced in middle to late layers. This insight motivates the development of NeuroShield-ViT, a novel defense mechanism that strategically neutralizes vulnerable neurons in earlier layers to prevent the cascade of adversarial effects. We demonstrate NeuroShield-ViT's effectiveness across various attacks, particularly excelling against strong iterative attacks, and showcase its remarkable zero-shot generalization capabilities. Without fine-tuning, our method achieves a competitive accuracy of 77.8% on adversarial examples, surpassing conventional robustness methods. Our results shed new light on how adversarial effects propagate through ViT layers, while providing a promising approach to enhance the robustness of vision transformers against adversarial attacks. Additionally, they provide a promising approach to enhance the robustness of vision transformers against adversarial attacks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.04679v1-abstract-full').style.display = 'none'; document.getElementById('2502.04679v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2025. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">10 pages, 5 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2410.19160">arXiv:2410.19160</a> <span> [<a href="https://arxiv.org/pdf/2410.19160">pdf</a>, <a href="https://arxiv.org/format/2410.19160">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> </div> </div> <p class="title is-5 mathjax"> Adversarial Attacks on Large Language Models Using Regularized Relaxation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Chacko%2C+S+J">Samuel Jacob Chacko</a>, <a href="/search/cs?searchtype=author&query=Biswas%2C+S">Sajib Biswas</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+C+M">Chashi Mahiul Islam</a>, <a href="/search/cs?searchtype=author&query=Liza%2C+F+T">Fatema Tabassum Liza</a>, <a href="/search/cs?searchtype=author&query=Liu%2C+X">Xiuwen Liu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2410.19160v1-abstract-short" style="display: inline;"> As powerful Large Language Models (LLMs) are now widely used for numerous practical applications, their safety is of critical importance. While alignment techniques have significantly improved overall safety, LLMs remain vulnerable to carefully crafted adversarial inputs. Consequently, adversarial attack methods are extensively used to study and understand these vulnerabilities. However, current a… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.19160v1-abstract-full').style.display = 'inline'; document.getElementById('2410.19160v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2410.19160v1-abstract-full" style="display: none;"> As powerful Large Language Models (LLMs) are now widely used for numerous practical applications, their safety is of critical importance. While alignment techniques have significantly improved overall safety, LLMs remain vulnerable to carefully crafted adversarial inputs. Consequently, adversarial attack methods are extensively used to study and understand these vulnerabilities. However, current attack methods face significant limitations. Those relying on optimizing discrete tokens suffer from limited efficiency, while continuous optimization techniques fail to generate valid tokens from the model's vocabulary, rendering them impractical for real-world applications. In this paper, we propose a novel technique for adversarial attacks that overcomes these limitations by leveraging regularized gradients with continuous optimization methods. Our approach is two orders of magnitude faster than the state-of-the-art greedy coordinate gradient-based method, significantly improving the attack success rate on aligned language models. Moreover, it generates valid tokens, addressing a fundamental limitation of existing continuous optimization methods. We demonstrate the effectiveness of our attack on five state-of-the-art LLMs using four datasets. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.19160v1-abstract-full').style.display = 'none'; document.getElementById('2410.19160v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">8 pages, 6 figures</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> I.2.7 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2407.07392">arXiv:2407.07392</a> <span> [<a href="https://arxiv.org/pdf/2407.07392">pdf</a>, <a href="https://arxiv.org/format/2407.07392">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Malicious Path Manipulations via Exploitation of Representation Vulnerabilities of Vision-Language Navigation Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Islam%2C+C+M">Chashi Mahiul Islam</a>, <a href="/search/cs?searchtype=author&query=Salman%2C+S">Shaeke Salman</a>, <a href="/search/cs?searchtype=author&query=Shams%2C+M">Montasir Shams</a>, <a href="/search/cs?searchtype=author&query=Liu%2C+X">Xiuwen Liu</a>, <a href="/search/cs?searchtype=author&query=Kumar%2C+P">Piyush Kumar</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2407.07392v1-abstract-short" style="display: inline;"> Building on the unprecedented capabilities of large language models for command understanding and zero-shot recognition of multi-modal vision-language transformers, visual language navigation (VLN) has emerged as an effective way to address multiple fundamental challenges toward a natural language interface to robot navigation. However, such vision-language models are inherently vulnerable due to… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.07392v1-abstract-full').style.display = 'inline'; document.getElementById('2407.07392v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2407.07392v1-abstract-full" style="display: none;"> Building on the unprecedented capabilities of large language models for command understanding and zero-shot recognition of multi-modal vision-language transformers, visual language navigation (VLN) has emerged as an effective way to address multiple fundamental challenges toward a natural language interface to robot navigation. However, such vision-language models are inherently vulnerable due to the lack of semantic meaning of the underlying embedding space. Using a recently developed gradient based optimization procedure, we demonstrate that images can be modified imperceptibly to match the representation of totally different images and unrelated texts for a vision-language model. Building on this, we develop algorithms that can adversarially modify a minimal number of images so that the robot will follow a route of choice for commands that require a number of landmarks. We demonstrate that experimentally using a recently proposed VLN system; for a given navigation command, a robot can be made to follow drastically different routes. We also develop an efficient algorithm to detect such malicious modifications reliably based on the fact that the adversarially modified images have much higher sensitivity to added Gaussian noise than the original images. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.07392v1-abstract-full').style.display = 'none'; document.getElementById('2407.07392v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">8 pages, 5 figures. This paper has been accepted for publication at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2404.03823">arXiv:2404.03823</a> <span> [<a href="https://arxiv.org/pdf/2404.03823">pdf</a>, <a href="https://arxiv.org/format/2404.03823">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> </div> </div> <p class="title is-5 mathjax"> An Investigation into Misuse of Java Security APIs by Large Language Models </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Mousavi%2C+Z">Zahra Mousavi</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+C">Chadni Islam</a>, <a href="/search/cs?searchtype=author&query=Moore%2C+K">Kristen Moore</a>, <a href="/search/cs?searchtype=author&query=Abuadbba%2C+A">Alsharif Abuadbba</a>, <a href="/search/cs?searchtype=author&query=Babar%2C+M+A">Muhammad Ali Babar</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2404.03823v1-abstract-short" style="display: inline;"> The increasing trend of using Large Language Models (LLMs) for code generation raises the question of their capability to generate trustworthy code. While many researchers are exploring the utility of code generation for uncovering software vulnerabilities, one crucial but often overlooked aspect is the security Application Programming Interfaces (APIs). APIs play an integral role in upholding sof… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.03823v1-abstract-full').style.display = 'inline'; document.getElementById('2404.03823v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2404.03823v1-abstract-full" style="display: none;"> The increasing trend of using Large Language Models (LLMs) for code generation raises the question of their capability to generate trustworthy code. While many researchers are exploring the utility of code generation for uncovering software vulnerabilities, one crucial but often overlooked aspect is the security Application Programming Interfaces (APIs). APIs play an integral role in upholding software security, yet effectively integrating security APIs presents substantial challenges. This leads to inadvertent misuse by developers, thereby exposing software to vulnerabilities. To overcome these challenges, developers may seek assistance from LLMs. In this paper, we systematically assess ChatGPT's trustworthiness in code generation for security API use cases in Java. To conduct a thorough evaluation, we compile an extensive collection of 48 programming tasks for 5 widely used security APIs. We employ both automated and manual approaches to effectively detect security API misuse in the code generated by ChatGPT for these tasks. Our findings are concerning: around 70% of the code instances across 30 attempts per task contain security API misuse, with 20 distinct misuse types identified. Moreover, for roughly half of the tasks, this rate reaches 100%, indicating that there is a long way to go before developers can rely on ChatGPT to securely implement security API code. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.03823v1-abstract-full').style.display = 'none'; document.getElementById('2404.03823v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This paper has been accepted by ACM ASIACCS 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2307.06520">arXiv:2307.06520</a> <span> [<a href="https://arxiv.org/pdf/2307.06520">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/ACCESS.2024.3360412">10.1109/ACCESS.2024.3360412 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> A Framework for Migrating to Post-Quantum Cryptography: Security Dependency Analysis and Case Studies </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Hasan%2C+K+F">Khondokar Fida Hasan</a>, <a href="/search/cs?searchtype=author&query=Simpson%2C+L">Leonie Simpson</a>, <a href="/search/cs?searchtype=author&query=Baee%2C+M+A+R">Mir Ali Rezazadeh Baee</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+C">Chadni Islam</a>, <a href="/search/cs?searchtype=author&query=Rahman%2C+Z">Ziaur Rahman</a>, <a href="/search/cs?searchtype=author&query=Armstrong%2C+W">Warren Armstrong</a>, <a href="/search/cs?searchtype=author&query=Gauravaram%2C+P">Praveen Gauravaram</a>, <a href="/search/cs?searchtype=author&query=McKague%2C+M">Matthew McKague</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2307.06520v2-abstract-short" style="display: inline;"> Quantum computing is emerging as a significant threat to information protected by widely used cryptographic systems. Cryptographic methods, once deemed secure for decades, are now at risk of being compromised, posing a massive threat to the security of sensitive data and communications across enterprises worldwide. As a result, there is an urgent need to migrate to quantum-resistant cryptographic… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.06520v2-abstract-full').style.display = 'inline'; document.getElementById('2307.06520v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.06520v2-abstract-full" style="display: none;"> Quantum computing is emerging as a significant threat to information protected by widely used cryptographic systems. Cryptographic methods, once deemed secure for decades, are now at risk of being compromised, posing a massive threat to the security of sensitive data and communications across enterprises worldwide. As a result, there is an urgent need to migrate to quantum-resistant cryptographic systems. This is no simple task. Migrating to a quantum-safe state is a complex process, and many organisations lack the in-house expertise to navigate this transition without guidance. In this paper, we present a comprehensive framework designed to assist enterprises with this migration. Our framework outlines essential steps involved in the cryptographic migration process, and leverages existing organisational inventories. The framework facilitates the efficient identification of cryptographic assets and can be integrated with other enterprise frameworks smoothly. To underscore its practicality and effectiveness, we have incorporated case studies that utilise graph-theoretic techniques to pinpoint and assess cryptographic dependencies. This is useful in prioritising crypto-systems for replacement. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.06520v2-abstract-full').style.display = 'none'; document.getElementById('2307.06520v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 February, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 12 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">24 Pages</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2307.04458">arXiv:2307.04458</a> <span> [<a href="https://arxiv.org/pdf/2307.04458">pdf</a>, <a href="https://arxiv.org/format/2307.04458">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> </div> </div> <p class="title is-5 mathjax"> Analyzing the Evolution of Inter-package Dependencies in Operating Systems: A Case Study of Ubuntu </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Prokhorenko%2C+V">Victor Prokhorenko</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+C">Chadni Islam</a>, <a href="/search/cs?searchtype=author&query=Babar%2C+M+A">Muhammad Ali Babar</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2307.04458v1-abstract-short" style="display: inline;"> An Operating System (OS) combines multiple interdependent software packages, which usually have their own independently developed architectures. When a multitude of independent packages are placed together in an OS, an implicit inter-package architecture is formed. For an evolutionary effort, designers/developers of OS can greatly benefit from fully understanding the system-wide dependency focused… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.04458v1-abstract-full').style.display = 'inline'; document.getElementById('2307.04458v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.04458v1-abstract-full" style="display: none;"> An Operating System (OS) combines multiple interdependent software packages, which usually have their own independently developed architectures. When a multitude of independent packages are placed together in an OS, an implicit inter-package architecture is formed. For an evolutionary effort, designers/developers of OS can greatly benefit from fully understanding the system-wide dependency focused on individual files, specifically executable files, and dynamically loadable libraries. We propose a framework, DepEx, aimed at discovering the detailed package relations at the level of individual binary files and their associated evolutionary changes. We demonstrate the utility of DepEx by systematically investigating the evolution of a large-scale Open Source OS, Ubuntu. DepEx enabled us to systematically acquire and analyze the dependencies in different versions of Ubuntu released between 2005 (5.04) to 2023 (23.04). Our analysis revealed various evolutionary trends in package management and their implications based on the analysis of the 84 consecutive versions available for download (these include beta versions). This study has enabled us to assert that DepEx can provide researchers and practitioners with a better understanding of the implicit software dependencies in order to improve the stability, performance, and functionality of their software as well as to reduce the risk of issues arising during maintenance, updating, or migration. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.04458v1-abstract-full').style.display = 'none'; document.getElementById('2307.04458v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This paper is accepted for publication in the 17th international conference on Software Architecture</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.08869">arXiv:2306.08869</a> <span> [<a href="https://arxiv.org/pdf/2306.08869">pdf</a>, <a href="https://arxiv.org/format/2306.08869">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> </div> </div> <p class="title is-5 mathjax"> Detecting Misuse of Security APIs: A Systematic Review </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Mousavi%2C+Z">Zahra Mousavi</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+C">Chadni Islam</a>, <a href="/search/cs?searchtype=author&query=Babar%2C+M+A">M. Ali Babar</a>, <a href="/search/cs?searchtype=author&query=Abuadbba%2C+A">Alsharif Abuadbba</a>, <a href="/search/cs?searchtype=author&query=Moore%2C+K">Kristen Moore</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.08869v2-abstract-short" style="display: inline;"> Security Application Programming Interfaces (APIs) are crucial for ensuring software security. However, their misuse introduces vulnerabilities, potentially leading to severe data breaches and substantial financial loss. Complex API design, inadequate documentation, and insufficient security training often lead to unintentional misuse by developers. The software security community has devised and… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.08869v2-abstract-full').style.display = 'inline'; document.getElementById('2306.08869v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.08869v2-abstract-full" style="display: none;"> Security Application Programming Interfaces (APIs) are crucial for ensuring software security. However, their misuse introduces vulnerabilities, potentially leading to severe data breaches and substantial financial loss. Complex API design, inadequate documentation, and insufficient security training often lead to unintentional misuse by developers. The software security community has devised and evaluated several approaches to detecting security API misuse to help developers and organizations. This study rigorously reviews the literature on detecting misuse of security APIs to gain a comprehensive understanding of this critical domain. Our goal is to identify and analyze security API misuses, the detection approaches developed, and the evaluation methodologies employed along with the open research avenues to advance the state-of-the-art in this area. Employing the systematic literature review (SLR) methodology, we analyzed 69 research papers. Our review has yielded (a) identification of 6 security API types; (b) classification of 30 distinct misuses; (c) categorization of detection techniques into heuristic-based and ML-based approaches; and (d) identification of 10 performance measures and 9 evaluation benchmarks. The review reveals a lack of coverage of detection approaches in several areas. We recommend that future efforts focus on aligning security API development with developers' needs and advancing standardized evaluation methods for detection technologies. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.08869v2-abstract-full').style.display = 'none'; document.getElementById('2306.08869v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 25 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 15 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.12132">arXiv:2203.12132</a> <span> [<a href="https://arxiv.org/pdf/2203.12132">pdf</a>, <a href="https://arxiv.org/format/2203.12132">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> </div> </div> <p class="title is-5 mathjax"> Runtime Software Patching: Taxonomy, Survey and Future Directions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Islam%2C+C">Chadni Islam</a>, <a href="/search/cs?searchtype=author&query=Prokhorenko%2C+V">Victor Prokhorenko</a>, <a href="/search/cs?searchtype=author&query=Babar%2C+M+A">M. Ali Babar</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.12132v2-abstract-short" style="display: inline;"> Runtime software patching aims to minimize or eliminate service downtime, user interruptions and potential data losses while deploying a patch. Due to modern software systems' high variance and heterogeneity, no universal solutions are available or proposed to deploy and execute patches at runtime. Existing runtime software patching solutions focus on specific cases, scenarios, programming languag… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.12132v2-abstract-full').style.display = 'inline'; document.getElementById('2203.12132v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.12132v2-abstract-full" style="display: none;"> Runtime software patching aims to minimize or eliminate service downtime, user interruptions and potential data losses while deploying a patch. Due to modern software systems' high variance and heterogeneity, no universal solutions are available or proposed to deploy and execute patches at runtime. Existing runtime software patching solutions focus on specific cases, scenarios, programming languages and operating systems. This paper aims to identify, investigate and synthesize state-of-the-art runtime software patching approaches and gives an overview of currently unsolved challenges. It further provides insights on multiple aspects of runtime patching approaches such as patch scales, general strategies and responsibilities. This study identifies seven levels of granularity, two key strategies providing a conceptual model of three responsible entities and four capabilities of runtime patching solutions. Through the analysis of the existing literature, this research also reveals open issues hindering more comprehensive adoption of runtime patching in practice. Finally, it proposes several crucial future directions that require further attention from both researchers and practitioners. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.12132v2-abstract-full').style.display = 'none'; document.getElementById('2203.12132v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 February, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 22 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.07603">arXiv:2203.07603</a> <span> [<a href="https://arxiv.org/pdf/2203.07603">pdf</a>, <a href="https://arxiv.org/format/2203.07603">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> </div> </div> <p class="title is-5 mathjax"> SmartValidator: A Framework for Automatic Identification and Classification of Cyber Threat Data </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Islam%2C+C">Chadni Islam</a>, <a href="/search/cs?searchtype=author&query=Babar%2C+M+A">M. Ali Babar</a>, <a href="/search/cs?searchtype=author&query=Croft%2C+R">Roland Croft</a>, <a href="/search/cs?searchtype=author&query=Janicke%2C+H">Helge Janicke</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.07603v1-abstract-short" style="display: inline;"> A wide variety of Cyber Threat Information (CTI) is used by Security Operation Centres (SOCs) to perform validation of security incidents and alerts. Security experts manually define different types of rules and scripts based on CTI to perform validation tasks. These rules and scripts need to be updated continuously due to evolving threats, changing SOCs' requirements and dynamic nature of CTI. Th… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.07603v1-abstract-full').style.display = 'inline'; document.getElementById('2203.07603v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.07603v1-abstract-full" style="display: none;"> A wide variety of Cyber Threat Information (CTI) is used by Security Operation Centres (SOCs) to perform validation of security incidents and alerts. Security experts manually define different types of rules and scripts based on CTI to perform validation tasks. These rules and scripts need to be updated continuously due to evolving threats, changing SOCs' requirements and dynamic nature of CTI. The manual process of updating rules and scripts delays the response to attacks. To reduce the burden of human experts and accelerate response, we propose a novel Artificial Intelligence (AI) based framework, SmartValidator. SmartValidator leverages Machine Learning (ML) techniques to enable automated validation of alerts. It consists of three layers to perform the tasks of data collection, model building and alert validation. It projects the validation task as a classification problem. Instead of building and saving models for all possible requirements, we propose to automatically construct the validation models based on SOC's requirements and CTI. We built a Proof of Concept (PoC) system with eight ML algorithms, two feature engineering techniques and 18 requirements to investigate the effectiveness and efficiency of SmartValidator. The evaluation results showed that when prediction models were built automatically for classifying cyber threat data, the F1-score of 75\% of the models were above 0.8, which indicates adequate performance of the PoC for use in a real-world organization. The results further showed that dynamic construction of prediction models required 99\% less models to be built than pre-building models for all possible requirements. The framework can be followed by various industries to accelerate and automate the validation of alerts and incidents based on their CTI and SOC's preferences. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.07603v1-abstract-full').style.display = 'none'; document.getElementById('2203.07603v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2201.07959">arXiv:2201.07959</a> <span> [<a href="https://arxiv.org/pdf/2201.07959">pdf</a>, <a href="https://arxiv.org/format/2201.07959">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> </div> </div> <p class="title is-5 mathjax"> APIRO: A Framework for Automated Security Tools API Recommendation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Sworna%2C+Z+T">Zarrin Tasnim Sworna</a>, <a href="/search/cs?searchtype=author&query=Islam%2C+C">Chadni Islam</a>, <a href="/search/cs?searchtype=author&query=Babar%2C+M+A">Muhammad Ali Babar</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2201.07959v1-abstract-short" style="display: inline;"> Security Orchestration, Automation, and Response (SOAR) platforms integrate and orchestrate a wide variety of security tools to accelerate the operational activities of Security Operation Center (SOC). Integration of security tools in a SOAR platform is mostly done manually using APIs, plugins, and scripts. SOC teams need to navigate through API calls of different security tools to find a suitable… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2201.07959v1-abstract-full').style.display = 'inline'; document.getElementById('2201.07959v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2201.07959v1-abstract-full" style="display: none;"> Security Orchestration, Automation, and Response (SOAR) platforms integrate and orchestrate a wide variety of security tools to accelerate the operational activities of Security Operation Center (SOC). Integration of security tools in a SOAR platform is mostly done manually using APIs, plugins, and scripts. SOC teams need to navigate through API calls of different security tools to find a suitable API to define or update an incident response action. Analyzing various types of API documentation with diverse API format and presentation structure involves significant challenges such as data availability, data heterogeneity, and semantic variation for automatic identification of security tool APIs specific to a particular task. Given these challenges can have negative impact on SOC team's ability to handle security incident effectively and efficiently, we consider it important to devise suitable automated support solutions to address these challenges. We propose a novel learning-based framework for automated security tool API Recommendation for security Orchestration, automation, and response, APIRO. To mitigate data availability constraint, APIRO enriches security tool API description by applying a wide variety of data augmentation techniques. To learn data heterogeneity of the security tools and semantic variation in API descriptions, APIRO consists of an API-specific word embedding model and a Convolutional Neural Network (CNN) model that are used for prediction of top 3 relevant APIs for a task. We experimentally demonstrate the effectiveness of APIRO in recommending APIs for different tasks using 3 security tools and 36 augmentation techniques. Our experimental results demonstrate the feasibility of APIRO for achieving 91.9% Top-1 Accuracy. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2201.07959v1-abstract-full').style.display = 'none'; document.getElementById('2201.07959v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 January, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2002.09190">arXiv:2002.09190</a> <span> [<a href="https://arxiv.org/pdf/2002.09190">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1145/3305268">10.1145/3305268 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> A Multi-Vocal Review of Security Orchestration </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Islam%2C+C">Chadni Islam</a>, <a href="/search/cs?searchtype=author&query=Babar%2C+M+A">M. Ali Babar</a>, <a href="/search/cs?searchtype=author&query=Nepal%2C+S">Surya Nepal</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2002.09190v1-abstract-short" style="display: inline;"> Organizations use diverse types of security solutions to prevent cyberattacks. Multiple vendors provide security solutions developed using heterogeneous technologies and paradigms. Hence, it is a challenging rather impossible to easily make security solutions to work an integrated fashion. Security orchestration aims at smoothly integrating multivendor security tools that can effectively and effic… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.09190v1-abstract-full').style.display = 'inline'; document.getElementById('2002.09190v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2002.09190v1-abstract-full" style="display: none;"> Organizations use diverse types of security solutions to prevent cyberattacks. Multiple vendors provide security solutions developed using heterogeneous technologies and paradigms. Hence, it is a challenging rather impossible to easily make security solutions to work an integrated fashion. Security orchestration aims at smoothly integrating multivendor security tools that can effectively and efficiently interoperate to support security staff of a Security Operation Centre (SOC). Given the increasing role and importance of security orchestration, there has been an increasing amount of literature on different aspects of security orchestration solutions. However, there has been no effort to systematically review and analyze the reported solutions. We report a Multivocal Literature Review that has systematically selected and reviewed both academic and grey (blogs, web pages, white papers) literature on different aspects of security orchestration published from January 2007 until July 2017. The review has enabled us to provide a working definition of security orchestration and classify the main functionalities of security orchestration into three main areas: unification, orchestration, and automation. We have also identified the core components of a security orchestration platform and categorized the drivers of security orchestration based on technical and socio-technical aspects. We also provide a taxonomy of security orchestration based on the execution environment, automation strategy, deployment type, mode of task and resource type. This review has helped us to reveal several areas of further research and development in security orchestration. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.09190v1-abstract-full').style.display = 'none'; document.getElementById('2002.09190v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 February, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This paper is published in ACM Computing Survey</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> D.2 </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> ACM Comput. 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