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<NewsItem contentIssues="true" id="129555" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129555">
<Title>Talk: Comparing Spatial Heterogeneity, 11:15-12:50 Wed 12/7</Title>
<Tagline>A way to estimate the importance of spatial factors in data</Tagline>
<Body>
<![CDATA[
    <div class="html-content">
    <div><strong>UMBC ACM Chapter</strong></div>
    <div><strong><br></strong></div>
    <div><strong>Modeling and Assessing Association by Comparing Spatial Heterogeneity</strong></div>
    <div><strong><br></strong></div>
    <div><strong>Dr. Xuezhi Cang</strong></div>
    <div><strong>Geography and Environmental Systems, UMBC</strong></div>
    <div><strong><br></strong></div>
    <div><strong>11:15-12:50 ET, Wednesday 7 December 2022</strong></div>
    <div><br></div>
    <div><strong>ITE 325b and online via <a href="https://umbc.webex.com/meet/dayuan1" rel="nofollow external" class="bo">WebEx</a></strong></div>
    <div><br></div>
    <div>Measuring spatial association between different spatial layers is important in spatial data modeling. Traditionally, the relationship between variables can be measured by linear regression. The assumptions of those traditional methods are hard to meet in the spatial data. Also, the traditional statistical methods do not consider Tobler's First Law of Geography which is an important spatial data property. To address these drawbacks, I propose a spatial data association estimator (termed as SPatial Association DEtector, SPADE). By comparing the spatial heterogeneity, this estimator, which evolved from a variance-based relation estimator, explicitly considers the spatial variance by assigning the weight of the influence based on spatial distribution. It also overcomes the drawback of its old version which can only measure the association between continuous and discrete variables.</div>
    <div><br></div>
    <div>This method has been applied to estimate the influence of the environmental factors and their outcome (e.g. junction angle and environmental factors). The associations between environmental factors and junction angles have been used to infer the paleoenvironment of Mars; they showed that Mars was probably "warm" and "wet" several billion years ago. The method could also be used in human geography and social science to estimate the importance of spatial factors and their outcome.</div>
    <div><br></div>
    <div>Dr. Xuezhi Cang graduated from Northern Illinois University with Ph.D. degree in Geography. His research and teaching focus on Mars Geomorphology, Spatial Analysis, and Geographic Information Systems. He is currently a Postdoctoral Scholar at UMBC.</div>
    <div><br></div>
    <div><img src="https://i.imgur.com/EVlqkUS.png" style="max-width: 100%; height: auto;"></div>
    </div>
]]>
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<Summary>UMBC ACM Chapter     Modeling and Assessing Association by Comparing Spatial Heterogeneity     Dr. Xuezhi Cang  Geography and Environmental Systems, UMBC     11:15-12:50 ET, Wednesday 7 December...</Summary>
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<PostedAt>Sat, 03 Dec 2022 21:13:41 -0500</PostedAt>
<EditAt>Sat, 03 Dec 2022 21:16:12 -0500</EditAt>
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<NewsItem contentIssues="true" id="129511" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129511">
<Title>Talk: Think Like an Attacker, 12-1 Fri. 12/2 online</Title>
<Tagline>Towards a definition and assessment of Adversarial Thinking</Tagline>
<Body>
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    <div><img src="https://i.imgur.com/xMNI4ho.jpg" style="max-width: 100%; height: auto;"></div>
    <div><strong><br></strong></div>
    <div><strong>The UMBC Cyber Defense Lab presents</strong></div>
    <div><br></div>
    <div><strong>Think Like an Attacker: Towards a Definition and Non-Technical Assessment of Adversarial Thinking</strong></div>
    <div><br></div>
    <div><a href="https://www.d.umn.edu/~pahp/" rel="nofollow external" class="bo"><strong>Peter A. H. Peterson</strong></a></div>
    <div><strong>University of Minnesota Duluth</strong></div>
    <div><strong><br></strong></div>
    <div><strong>12-1:00 pm ET, Friday, 2 Dec, 2022, via <a href="https://umbc.webex.com/meet/sherman" rel="nofollow external" class="bo">WebEx</a><span> </span></strong></div>
    <div><br></div>
    <div>
    <div>"Adversarial thinking" (AT), sometimes called the "security mindset" or described as the ability to "think like an attacker," is widely accepted in the computer security community as an essential ability for successful cybersecurity practice. Supported by intuition and anecdotes, many in the community stress the importance of AT, and multiple projects have produced interventions explicitly intended to strengthen individual AT skills to improve security in general.  However, there is no agreed-upon definition of "adversarial thinking" or its components, and accordingly, no test for it.  Because of this absence, it is impossible to meaningfully quantify AT in subjects, AT's importance for cybersecurity practitioners, or the effectiveness of interventions designed to improve AT. Working towards the goal of a characterization of AT in cybersecurity and a non-technical test for AT that anyone can take, I will discuss existing conceptions of AT from the security community, as well as ideas about AT in other fields with adversarial aspects including war, politics, law, critical thinking, and games. I will also describe some of the unique difficulties of creating a non-technical test for AT, compare and contrast this effort to our work on the CATS and Security Misconceptions projects, and describe some potential solutions. I will explore potential uses for such an instrument, including measuring a student's change in AT over time, measuring the effectiveness of interventions meant to improve AT, comparing AT in different populations (e.g., security professionals vs. software engineers), and identifying individuals from all walks of life with strong AT skills -- people who might help meet our world's pressing need for skilled and insightful security professionals and researchers. Along the way, I will give some sample non-technical adversarial thinking challenges and describe how they might be graded and validated.</div>
    <div><br></div>
    <div>Peter A. H. Peterson is an associate professor of computer science at the University of Minnesota Duluth, where he teaches and directs the Laboratory for Advanced Research in Systems (LARS), a group dedicated to research in operating systems and security, with a special focus on research and development to make security education more effective and accessible. He is an active member of the Cybersecurity Assessment Tools (CATS) project, which created and validated two concept inventories for cybersecurity (the CCI and CCA) and is working on an NSF-funded grant to evaluate educational interventions at US military academies using the CCI. He is also working on an NSF CAREER award to articulate the most critical components of Adversarial Thinking, and to create, validate, and use a non- technical assessment for AT that anyone can take. He is also finishing an NSF project to create a misconcept inventory -- a test about common misconceptions in cybersecurity. He earned his PhD from the University of California, Los Angeles for work on "adaptive compression" -- systems that make compression decisions dynamically to improve efficiency. He can be reached at <a href="mailto:pahp@d.umn.edu">pahp@d.umn.edu</a>.</div>
    <div><br></div>
    <div>Host: Alan T. Sherman, <a href="mailto:sherman@umbc.edu">sherman@umbc.edu</a>. Support for this event was provided in part by the National Science Foundation under SFS grant DGE-1753681.  The UMBC Cyber Defense Lab meets biweekly Fridays. All meetings are open to the public. Upcoming CDL Meetings: Dec 20, 10:30am-12:30pm, 3 in-person presentations from the UMBC fall 2022 cybersecurity research class, ITE-229.  Topics: protocol analysis of FIDO UAF Registration, malware analysis, cyber-physical security of UMBC's ILSB.  January 2-6, 2023, SFS/CySP Research Study</div>
    </div>
    </div>
]]>
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<Summary>The UMBC Cyber Defense Lab presents     Think Like an Attacker: Towards a Definition and Non-Technical Assessment of Adversarial Thinking     Peter A. H. Peterson  University of Minnesota Duluth...</Summary>
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<PostedAt>Thu, 01 Dec 2022 14:54:04 -0500</PostedAt>
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<NewsItem contentIssues="true" id="129320" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129320">
<Title>Talk: Forno on What Evils Lurk Over That Horizon? 6pm Dec. 8</Title>
<Tagline>Hear what new cybersecurity threats we should prepare for</Tagline>
<Body>
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    <div><br></div>
    
    As cyberattacks continue to grow in prevalence and sophistication, their costs continue to increase for corporations, governments, and consumers. But what are the next threats that we should be preparing for? Join the DataWorks MD Meetup in December to hear from UMBC cybersecurity expert Dr. Richard Forno on what evils are lurking over the horizon.<div><br></div>
    <div><strong>What Evils Lurk Over That Horizon?</strong></div>
    
    <div><strong>Dr. Richard Forno, UMBC</strong></div>
    <div><strong><br></strong></div>
    <div><strong>6-7:30 pm ET via Zoom &amp; YouTube</strong></div>
    <div><strong><a href="https://www.meetup.com/dataworks/events/289595430/" rel="nofollow external" class="bo">Register at DataWorks MD</a></strong></div>
    <div><br></div>
    
    <div>This discussion will explore several likely cyber-related threats facing individuals, businesses, and global society at large over the next decade. In doing so, the state of cybersecurity at America's grassroots --our cities and communities-- will be examined since not only are these the most intimate levels of government interaction with citizens, but they often are fairly vulnerable targets.</div>
    <div><br></div>
    
    <div>
    <a href="https://cybersecurity.umbc.edu/richard-forno/" rel="nofollow external" class="bo"><strong>Dr. Richard Forno</strong></a> is a Principal Lecturer in the UMBC Department of Computer Science and Electrical Engineering, where he directs the UMBC Graduate Cybersecurity Program, serves as the Assistant Director of the <a href="https://cybersecurity.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for Cybersecurity</strong></a>, and is an Affiliate of the Stanford Law School's Center for Internet and Society (CIS). Prior to academia, his twenty-year career in operational cybersecurity includes helping build a formal cybersecurity program for the US House of Representatives, serving as the first Chief Security Officer for Network Solutions (then the global center of the internet DNS system), consulting to Fortune 100 companies, the government, military, and more. As a technologist and student of national security studies, Dr. Forno is an unconventional, albeit realistic, critical thinker about the relationships between technology, security, and society. His latest book is <a href="https://www.wiley.com/en-us/Cybersecurity+and+Local+Government-p-9781119788287" rel="nofollow external" class="bo"><strong>Cybersecurity for Local Government</strong> </a>(Wiley, 2022.)</div>
    </div>
]]>
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<Summary>As cyberattacks continue to grow in prevalence and sophistication, their costs continue to increase for corporations, governments, and consumers. But what are the next threats that we should be...</Summary>
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<PostedAt>Sun, 20 Nov 2022 17:52:08 -0500</PostedAt>
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<NewsItem contentIssues="false" id="129312" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129312">
<Title>Talk: How Does Fact-checking Affect News Engagement, 11/22</Title>
<Tagline>A Multi-method Study on Social Media Platforms</Tagline>
<Body>
<![CDATA[
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    <div><strong>UMBC ACM Chapter Talk</strong></div>
    <div><br></div>
    <h5>How Does Fact-checking Affect News Engagement</h5>
    <h5>on Social Media  Platforms: A Multi-method Study</h5>
    <div><br></div>
    <h5><strong>Guohou (Jack) Shan</strong></h5>
    <div>
    <strong>PhD Candidate at Temple University and </strong><strong>UMBC Alum ’2019. </strong>
    </div>
    <div><strong><br></strong></div>
    <div><strong>11-12:50 pm ET, Tue. 22 Nov. 2022</strong></div>
    <div><strong>ITE 346, UMBC and <a href="https://umbc.webex.com/meet/dayuan1" rel="nofollow external" class="bo">Webex</a></strong></div>
    <div><br></div>
    <div>Social media platforms have begun to counter false news by integrating fact-checking services. These fact checkers verify posts’ content and inform users about the posts’ veracity before engaging with them. While the efficacy of fact-checking on users has been studied in prior literature, little attention has been paid to the factors that determine the effectiveness of fact-checking (e.g., fact-checking timeliness or reputation of the poster) to sway user reactions. Our multi-method study leverages the high external validity of observational data from Twitter (Study 1) complemented by the high internal validity of experimental data (Study 2) to build insights into how fact-checking methods and poster attributes affect news engagement (i.e., willingness to read, talk, comment, and share). </div>
    <div><br></div>
    <div>We find when fact-checking flags news as false significantly decreases news engagement and that fact-checking timeliness and poster reputation moderate the effect of fact-checking. Moreover, we find that fact-checking affects news engagement by influencing users’ evaluation of the news believability and shareability. Our findings enrich the understanding of the impact of fact-checking on users’ engagement with news and suggest managerial implications for reducing false news engagement.   </div>
    <div><br></div>
    </div>
]]>
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<Summary>UMBC ACM Chapter Talk     How Does Fact-checking Affect News Engagement  on Social Media  Platforms: A Multi-method Study     Guohou (Jack) Shan  PhD Candidate at Temple University and UMBC Alum...</Summary>
<Website>https://acm.umbc.edu/2022/11/17/acm-talk-hi-tea-nov-22-2022-tuesday-11am-to-1250pm-ite346/</Website>
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<NewsItem contentIssues="false" id="129310" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129310">
<Title>BW Tech Tour Notes</Title>
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<![CDATA[
    <div class="html-content">Hey everyone! Here are the notes that were taken during our BW Tech tour. Have a good weekend!</div>
]]>
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<Summary>Hey everyone! Here are the notes that were taken during our BW Tech tour. Have a good weekend!</Summary>
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<Sponsor>Information Systems Security Association, UMBC Chapter</Sponsor>
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<PostedAt>Fri, 18 Nov 2022 18:18:34 -0500</PostedAt>
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<NewsItem contentIssues="false" id="129222" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129222">
<Title></Title>
<Body>
<![CDATA[
    <div class="html-content"><div>We will host our SQL workshop in ITE 237 from 12-1PM. We strongly recommend that you bring a device to practice scripting with us! We hope to see you there!! </div></div>
]]>
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<Summary>We will host our SQL workshop in ITE 237 from 12-1PM. We strongly recommend that you bring a device to practice scripting with us! We hope to see you there!! </Summary>
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<NewsItem contentIssues="true" id="129178" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129178">
<Title>Talk: Can we ever trust our chatbots?</Title>
<Tagline>Research towards trustable collaborative assistants</Tagline>
<Body>
<![CDATA[
    <div class="html-content">
    <div><img src="https://i.imgur.com/NSAjtLp.jpg" style="max-width: 100%; height: auto;"></div>
    <div><br></div>
    <div><strong>UMBC Ebiquity Research Lab presents</strong></div>
    <div><br></div>
    <h4>
    <strong>Can we ever trust our chatbots?<br></strong><strong>Towards trustable collaborative assistants</strong>
    </h4>
    <div><br></div>
    <div><a href="https://sites.google.com/site/biplavsrivastava/" rel="nofollow external" class="bo"><strong>Dr. Biplav Srivastava</strong></a></div>
    <div><strong>Professor and AAAS Leshner Fellow</strong></div>
    <div>
    <strong>Artificial Intelligence Institute, </strong><strong>University of South Carolina</strong>
    </div>
    <div><strong><br></strong></div>
    <div>
    <strong>3-4pm ET Wed, 16 Nov. 2022, </strong><strong>ITE 325B and <a href="https://umbc.webex.com/meet/manas" rel="nofollow external" class="bo">Webex</a></strong>
    </div>
    <div><br></div>
    <div>AI services are known to have unstable behavior when subjected to changes in data, models or users, especially in sustainable and societal applications. Such behaviors, whether triggered by omission or commission, lead to trust issues when AI works with humans. The current approach of assessing AI services in a black box setting, where the consumer does not have access to the AI's source code or training data, limits the transparency, explainability, safety, and adoption of AI. The consumer has to rely on the AI developer's documentation and trust that the system has been built as stated. Further, if the AI consumer reuses the service to build other services which they sell to their customers, the consumer is at the risk of the service providers (both data and model providers). In this talk, I will cover chatbots (collaborative assistants), the problem of trust in this context and how one may make them more trustable. I will cover software testing, AI robustness, randomized control trial and the idea of rating AI based on their behavior. I will highlight some of our work, present key results and discuss ongoing research</div>
    <div><br></div>
    <div>
    <a href="https://sites.google.com/site/biplavsrivastava/" rel="nofollow external" class="bo">Biplav Srivastava</a> is a Professor of Computer Science at the AI Institute at the University of South Carolina. Previously, he was at IBM for nearly two decades in the roles of a Research Scientist, Distinguished Data Scientist and Master Inventor. Biplav is an ACM Distinguished Scientist, AAAI Senior Member, IEEE Senior Member and AAAS Leshner Fellow for Public Engagement on AI (2020-2021).  His focus is on promoting goal-oriented, ethical, human-machine collaboration via natural interfaces using domain and user models, learning and planning.  Biplav has been working in AI trust for the last 3 years pursuing ideas in AI testing, rating, randomized control and adversarial learning.  He applies these techniques in areas of social as well as commercial relevance with particular attention to issues of developing countries (e.g., transportation, water, health and governance). Biplav's work has led to many science firsts and high-impact commercial innovations ($B+), 190+ papers and 60+ US patents issued, and awards for papers, demos and hacks. He has interacted with commercial customers, universities and governments, been on multilateral bodies, and assisted business leaders on technical issues.</div>
    <div><br></div>
    <div>Host: <a href="https://manasgaur.github.io/" rel="nofollow external" class="bo">Manas Gaur</a>, <a href="mailto:manas@umbc.edu">manas@umbc.edu</a>
    </div>
    </div>
]]>
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<Summary>UMBC Ebiquity Research Lab presents     Can we ever trust our chatbots? Towards trustable collaborative assistants     Dr. Biplav Srivastava  Professor and AAAS Leshner Fellow  Artificial...</Summary>
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<Tag>ai</Tag>
<Tag>chatbot</Tag>
<Tag>nlp</Tag>
<Tag>research</Tag>
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<PostedAt>Mon, 14 Nov 2022 14:31:28 -0500</PostedAt>
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<NewsItem contentIssues="false" id="129142" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129142">
<Title>PhD Defense: Backdoor Attacks in Computer Vision</Title>
<Tagline>Towards Adversarially Robust Machine Learning Models</Tagline>
<Body>
<![CDATA[
    <div class="html-content">
    <div><strong>PhD Dissertation Defense</strong></div>
    <div><br></div>
    <div><strong>Backdoor Attacks in Computer Vision: Towards Adversarially Robust Machine Learning Models</strong></div>
    <div><strong><br></strong></div>
    <div><strong>PhD Candidate: <a href="https://ani0075.github.io/" rel="nofollow external" class="bo">Aniruddha Saha</a> (Computer Science)</strong></div>
    <div><br></div>
    <div><strong>12-2 ET Friday, 18 November 2022, <a href="https://umbc.webex.com/meet/anisaha1" rel="nofollow external" class="bo">WebEx </a></strong></div>
    <div><br></div>
    <div>Committee: Drs. Hamed Pirsiavash (Advisor/Co-Chair), Anupam</div>
    <div>Joshi (Chair), Tim Oates, Tom Goldstein (UMCP), Dr. Pin-Yu Chen (IBM)</div>
    <div><br></div>
    <div>Deep Neural Networks (DNNs) have become the standard building block in numerous machine learning applications, including computer vision, speech recognition, machine translation, and robotic manipulation, achieving state-of-the-art performance on complex tasks. The widespread success of these networks has driven their deployment in sensitive domains like health care, finance, autonomous driving, and defense-related applications. </div>
    <div><br></div>
    <div>However, DNNs are vulnerable to adversarial attacks. An adversary is a person with malicious intent whose goal is to disrupt the normal functioning of a machine learning pipeline. Research has shown that an adversary can tamper with the training process of a model by injecting misrepresentative data (poisons) into the training set. Moreover, if provided control over the training process as a third party, they can deliver a model to a victim, which deviates from normal behavior. These are called backdoor attacks. The manipulation is done in a way that the victim's model will malfunction only when a trigger is pasted on a test input. For instance, a backdoored model in a self-driving car might work accurately for days before it suddenly fails to detect a pedestrian when the adversary decides to exploit the backdoor. Vulnerability to backdoor attacks is dangerous when deep learning models are deployed in safety-critical applications.    </div>
    <div> </div>
    <div>This dissertation studies ways in which state-of-the-art deep learning methods for computer vision are vulnerable to backdoor attacks and proposes defense methods to remedy the vulnerabilities. We push the limits of our current understanding of backdoors and address the following research questions.  </div>
    <div><br></div>
    <div>Can we design practical backdoor attacks? We propose Hidden Trigger Backdoor Attack - a novel clean-label backdoor attack where the poisoned images do not contain a visible trigger. This enables the attacker to keep the trigger hidden until its use at test-time. We believe such practical attacks reveal an important vulnerability of deep learning models. These flaws need to be studied extensively before deploying models in critical real-world applications.</div>
    <div><br></div>
    <div>Is it secure to train models on large-scale public data? Self-supervised learning (SSL) methods for vision have utilized large-scale unlabeled data to learn rich visual representations. These methods use public images downloaded from the web, e.g., Instagram-1B and Flickr image datasets. We show that if a small part of the unlabeled training data is poisoned, SSL methods are vulnerable to backdoor attacks. Backdoor attacks are more practical in self-supervised learning, since the use of large unlabeled data makes data inspection to remove poisons prohibitive. Hence, using large and diverse data to remove data biases and reduce labeling costs might unknowingly set up avenues for adversarial manipulation. Practitioners must make informed choices when choosing training data for machine learning models.</div>
    <div><br></div>
    <div>Can we design efficient and generalizable backdoor detection methods? Methods to detect backdoors in trained models have relied on analysis of model behavior on carefully chosen inputs. But often, this analysis has to be repeated for a new model. We propose a backdoor detection method that optimizes for a set of images which, when forwarded through any model, indicates successfully whether the model contains a backdoor. Our "litmus" test for backdoored models improves on state-of-the-art methods without requiring access to clean data during detection. It is computationally efficient and generalizes to new triggers as well as new architectures. We effectively detect backdoor attacks on thousands of networks with different architectures trained on four benchmark datasets, namely the German Traffic Sign Recognition Benchmark (GTSRB), MNIST, CIFAR10, and Tiny-ImageNet. This will serve as a benchmark for future research.</div>
    <div><br></div>
    <div>Do architectural design choices contribute to backdoor robustness? We find an intriguing difference between Vision Transformers and Convolutional Nets; interpretation algorithms effectively highlight the backdoor trigger on test images for transformers but not for CNNs when attacked with Hidden Trigger Backdoor Attacks. Based on this observation, we find that a test-time image blocking defense reduces attack success rate by a large margin for transformers. We show that such blocking mechanisms can be incorporated during the training process to improve robustness even further. We believe our findings will encourage the community to make better design choices in developing novel architectures robust to backdoor attacks.</div>
    <div><br></div>
    </div>
]]>
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<Summary>PhD Dissertation Defense     Backdoor Attacks in Computer Vision: Towards Adversarially Robust Machine Learning Models     PhD Candidate: Aniruddha Saha (Computer Science)     12-2 ET Friday, 18...</Summary>
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<NewsItem contentIssues="false" id="129138" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129138">
<Title>Talk: Myths in Cybersecurity: Pros &amp; Cons of Analogies</Title>
<Tagline>Avoiding the hazards and pitfalls that derail us</Tagline>
<Body>
<![CDATA[
    <div class="html-content">
    <div><strong>The UMBC Cyber Defense Lab presents</strong></div>
    <div><br></div>
    <h4>Myths in Cybersecurity: Pros and Cons of Analogies</h4>
    <div><br></div>
    <h5>
    <strong><a href="https://josiahdykstra.com/" rel="nofollow external" class="bo">Dr. Josiah Dykstra<br></a></strong><strong>Technical Fellow, National Security Agency</strong>
    </h5>
    <div><br></div>
    <h5><strong>12-1<span> pm, Friday, 18 November 2022 via <a href="https://umbc.webex.com/meet/sherman" rel="nofollow external" class="bo">WebEx</a></span></strong></h5>
    <div><br></div>
    <h5><strong>Joint work with Dr. Eugene H. Spafford and Dr. Leigh Metcalf</strong></h5>
    <div><br></div>
    <div>Cybersecurity is rich with analogies, from keys and locks to Trojan horses. We look for the "needle in the haystack" and "evict malware resident on our systems." We debate "baked-in" versus "bolted-on" security. We do not mean all these things literally, of course. The language and analogies we use in this field are borrowed from many different domains. Analogies can help explain basic cybersecurity concepts, but too often they omit or overgeneralize important details. They can mislead, sometimes deliberately, because the experience they purport to connect might be out of proportion. <span>Despite their shortcoming and imprecision, using an analogy or an abstraction might be helpful in appropriate situations. Using analogies, abstractions, and metaphors shapes technology's development, practice, and policies. The analogies are more than simple figures of speech. They have a normative dimension; sometimes, they can be used to help the imaginary shape reality. </span>
    </div>
    <div><br></div>
    <div>This talk explores the use and misuse of analogies and metaphors across cybersecurity. We consider analogies from the physical world, medicine and biology, war and military, and law before discussing tips for avoiding pitfalls in using analogies and metaphors.  This talk is adapted from material in the forthcoming book <a href="https://www.amazon.com/Cybersecurity-Myths-Misconceptions-Avoiding-Pitfalls/dp/0137929234" rel="nofollow external" class="bo">Cybersecurity Myths and Misconceptions: Avoiding the Hazards and Pitfalls That Derail Us</a> by Drs. Spafford, Metcalf, and Dykstra. The book presents 175+ common myths and misconceptions held by users, leaders, and cybersecurity professionals, along with tips for how to avoid them.</div>
    <div><br></div>
    <div>
    <strong><a href="https://josiahdykstra.com/" rel="nofollow external" class="bo">Josiah Dykstra</a></strong> is a Technical Fellow in the Cybersecurity Collaboration Center at the National Security Agency (NSA) and the owner of Designer Security, LLC. In 2013, he earned his PhD in computer science from UMBC studying cloud forensics with Dr. Sherman. He is interested in cybersecurity science, especially where humans intersect with technology. He has studied stress in hacking, action bias in incident response, and economics of cyber threat intelligence. Dr. Dykstra is a frequent author and speaker, including at the Black Hat and RSA Conference. He received the CyberCorps Scholarship for Service (SFS) fellowship and is one of seven people in the SFS Hall of Fame. In 2017, he received the Presidential Early Career Award for Scientists and Engineers (PECASE) from then President Barack Obama.  Dr. Dykstra is a Fellow of the American Academy of Forensic Sciences and a Distinguished Member of the Association for Computing Machinery (ACM). He is the author of numerous research papers and two books.</div>
    <div><br></div>
    <div>Host: Alan T. Sherman, <a href="mailto:sherman@umbc.edu">sherman@umbc.edu</a>. Support for this event was provided in part by the National Science Foundation under SFS grant DGE-1753681.  The UMBC Cyber Defense Lab meets biweekly Fridays 12-1pm. All meetings are open to the public.  Upcoming CDL meetings: Dec 2, Peter Peterson (UMN Duluth), Adversarial Thinking Dec 20, 10:30am-12:30pm, 3 In-Person presentations from the UMBC fall 2022 cybersecurity research class, location TBA SFS/CySP Research Study: January 2-6, 2023 (tentative)</div>
    </div>
]]>
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<Summary>The UMBC Cyber Defense Lab presents     Myths in Cybersecurity: Pros and Cons of Analogies     Dr. Josiah Dykstra Technical Fellow, National Security Agency     12-1 pm, Friday, 18 November 2022...</Summary>
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<PostedAt>Fri, 11 Nov 2022 15:41:46 -0500</PostedAt>
<EditAt>Fri, 11 Nov 2022 20:37:31 -0500</EditAt>
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<NewsItem contentIssues="true" id="129109" important="false" status="posted" url="https://my3.my.umbc.edu/groups/ieee/posts/129109">
<Title>TALK: Can We Build the Universe Using only Math?</Title>
<Tagline>Prof. Manil Suri defends the thesis of his new book, 11/14</Tagline>
<Body>
<![CDATA[
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    <div>
    <h4><strong>Can We Build the Universe Using Only Math?<br></strong></h4>
    <h4>Professor Manil Suri</h4>
    <h5>5:30-6:45 pm Mon. 14 Nov. 2022<br>Albin O. Kuhn Library Gallery, UMBC</h5>
    <div><br></div>
    <div>UMBC professor <a href="https://www.manilsuri.com/" rel="nofollow external" class="bo"><strong>Manil Suri</strong></a> defends the thesis of his new book, <a href="https://wwnorton.com/books/9781324007036" rel="nofollow external" class="bo"><strong>The Big Bang of Numbers: How to Build the Universe Using Only Math</strong></a>, by answering questions posed by an interdisciplinary panel of faculty.  His "thesis committee" includes:</div>
    <div><ul>
    <li><span>Dr. Philip Rous, Physics</span></li>
    <li>Dr. Michele Osherow, English</li>
    <li>Dr. Preminda Jacob, Visual Arts</li>
    <li>Dr. Kathleen Hoffman, Math &amp; Biology</li>
    </ul></div>
    <div>Dr. William LaCourse, Dean of the College of Natural and Mathematical Sciences, will introduce the defense. Reception and book-signing to follow All are welcome!</div>
    <div><br></div>
    <div>Manil Suri is a distinguished university professor in mathematics at the University of Maryland, Baltimore County. He is the author of three award-winning novels, including <a href="https://wwnorton.com/books/The-Death-of-Vishnu" rel="nofollow external" class="bo"><strong>The Death of Vishnu</strong></a>, which have been cumulatively translated into 27 languages. He is a former contributing opinion columnist at the New York Times, for which he has written several essays on mathematics. His new book, The Big Bang of Numbers: How to Build the Universe Using Only Math will be available for purchase and signing at the event.</div>
    <div><br></div>
    <div>Presented by the College of Natural and Mathematical Sciences, and the UMBC Honors College</div>
    </div>
    <div><br></div>
    </div>
]]>
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<Summary>Can We Build the Universe Using Only Math?   Professor Manil Suri  5:30-6:45 pm Mon. 14 Nov. 2022 Albin O. Kuhn Library Gallery, UMBC     UMBC professor Manil Suri defends the thesis of his new...</Summary>
<Website>https://www.manilsuri.com/</Website>
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<PostedAt>Fri, 11 Nov 2022 10:35:42 -0500</PostedAt>
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