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1. Pathogen‐driven coevolution across the CBP60 plant immune regulator subfamilies confers resilience on the regulator module

   https://doi.org/10.1111/nph.17769  

   Zheng, Qi; Majsec, Kristina; Katagiri, Fumiaki (October 2021, New Phytologist)

   Summary Components of the plant immune signaling network need mechanisms that confer resilience against fast‐evolving pathogen effectors that target them. Among eight Arabidopsis CaM‐Binding Protein (CBP) 60 family members, AtCBP60g and AtSARD1 are partially functionally redundant, major positive immune regulators, and AtCBP60a is a negative immune regulator. We investigated possible resilience‐conferring evolutionary mechanisms among the CBP60a, CBP60g and SARD1 immune regulatory subfamilies.Phylogenetic analysis was used to investigate the times of CBP60 subfamily neofunctionalization. Then, using the pairwise distance rank based on the newly developed analytical platform Protein Evolution Analysis in a Euclidean Space (PEAES), hypotheses of specific coevolutionary mechanisms that could confer resilience on the regulator module were tested.The immune regulator subfamilies diversified around the time of angiosperm divergence and have been evolving very quickly. We detected significant coevolutionary interactions across the immune regulator subfamilies in all of 12 diverse core eudicot species lineages tested. The coevolutionary interactions were consistent with the hypothesized coevolution mechanisms.Despite their unusually fast evolution, members across the CBP60 immune regulator subfamilies have influenced the evolution of each other long after their diversification in a way that could confer resilience on the immune regulator module against fast‐evolving pathogen effectors. 

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2. RegulaTor: A Straightforward Website Fingerprinting Defense

   https://doi.org/10.2478/popets-2022-0049  

   Holland, James K; Hopper, Nicholas (March 2022, Proceedings on Privacy Enhancing Technologies)

   Abstract Website Fingerprinting (WF) attacks are used by local passive attackers to determine the destination of encrypted internet traffic by comparing the sequences of packets sent to and received by the user to a previously recorded data set. As a result, WF attacks are of particular concern to privacy-enhancing technologies such as Tor. In response, a variety of WF defenses have been developed, though they tend to incur high bandwidth and latency overhead or require additional infrastructure, thus making them difficult to implement in practice. Some lighter-weight defenses have been presented as well; still, they attain only moderate effectiveness against recently published WF attacks. In this paper, we aim to present a realistic and novel defense, RegulaTor, which takes advantage of common patterns in web browsing traffic to reduce both defense overhead and the accuracy of current WF attacks. In the closed-world setting, RegulaTor reduces the accuracy of the state-of-the-art attack, Tik-Tok, against comparable defenses from 66% to 25.4%. To achieve this performance, it requires 6.6% latency overhead and a bandwidth overhead 39.3% less than the leading moderate-overhead defense. In the open-world setting, RegulaTor limits a precision-tuned Tik-Tok attack to an F 1 -score of. 135, compared to .625 for the best comparable defense. 

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3. On Approximating Polynomial-Quadratic Regulator Problems

   https://doi.org/10.1016/j.ifacol.2021.06.090  

   Borggaard, Jeff; Zietsman, Lizette (January 2021, IFAC-PapersOnLine)

   null (Ed.)
4. Regulator: Dynamic Analysis to Detect ReDoS

   McLaughlin, R. (August 2022, Proceedings of the USENIX conference)

   Regular expressions (regexps) are a convenient way for programmers to express complex string searching logic. Sev- eral popular programming languages expose an interface to a regexp matching subsystem, either by language-level primi- tives or through standard libraries. The implementations be- hind these matching systems vary greatly in their capabilities and running-time characteristics. In particular, backtracking matchers may exhibit worst-case running-time that is either linear, polynomial, or exponential in the length of the string being searched. Such super-linear worst-case regexps expose applications to Regular Expression Denial-of-Service (Re- DoS) when inputs can be controlled by an adversarial attacker. In this work, we investigate the impact of ReDoS in back- tracking engines, a popular type of engine used by most programming languages. We evaluate several existing tools against a dataset of broadly collected regexps, and find that despite extensive theoretical work in this field, none are able to achieve both high precision and high recall. To address this gap in existing work, we develop REGULATOR, a novel dy- namic, fuzzer-based analysis system for identifying regexps vulnerable to ReDoS. We implement this system by directly instrumenting a popular backtracking regexp engine, which increases the scope of supported regexp syntax and features over prior work. Finally, we evaluate this system against three common regexp datasets, and demonstrate a seven-fold in- crease in true positives discovered when comparing against existing tools. 

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5. Asynchronous Heterogeneous Linear Quadratic Regulator Design

   https://doi.org/10.1109/CDC56724.2024.10885806  

   Toso, Leonardo F; Wang, Han; Anderson, James (December 2024, IEEE)