Academic literature on the topic 'Security, Fuzzing'
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Journal articles on the topic "Security, Fuzzing"
Wu, Xiao Lei. "Research on Network Security Algorithm Based on ZigBee Technology." Applied Mechanics and Materials 608-609 (October 2014): 503–6. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.503.
Full textSharkov, Ivan Vladimirovich, Vartan Andronikovich Padaryan, and Petr Vladimirovich Khenkin. "Features of fuzzing network interfaces without source codes." Proceedings of the Institute for System Programming of the RAS 33, no. 4 (2021): 211–26. http://dx.doi.org/10.15514/ispras-2021-33(4)-15.
Full textSong, Congxi, Xu Zhou, Qidi Yin, Xinglu He, Hangwei Zhang, and Kai Lu. "P-Fuzz: A Parallel Grey-Box Fuzzing Framework." Applied Sciences 9, no. 23 (November 25, 2019): 5100. http://dx.doi.org/10.3390/app9235100.
Full textVishnyakov, Alexey, Eli Kobrin, and Andrey Fedotov. "Error detection in binary code with dynamic symbolic execution." Proceedings of the Institute for System Programming of the RAS 34, no. 2 (2022): 25–42. http://dx.doi.org/10.15514/ispras-2022-34(2)-3.
Full textLi, Tong, Xuan Huang, and Rui Huang. "Research on Software Security Vulnerability Discovery Based on Fuzzing." Applied Mechanics and Materials 635-637 (September 2014): 1609–13. http://dx.doi.org/10.4028/www.scientific.net/amm.635-637.1609.
Full textHernández Ramos, Santiago, M. Teresa Villalba, and Raquel Lacuesta. "MQTT Security: A Novel Fuzzing Approach." Wireless Communications and Mobile Computing 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/8261746.
Full textSimon, Frank, and Daniel Simon. "Fuzzing: Testing Security in Maintenance Projects." Softwaretechnik-Trends 32, no. 2 (May 2012): 61–62. http://dx.doi.org/10.1007/bf03323481.
Full textGodefroid, Patrice, Michael Y. Levin, and David Molnar. "SAGE: Whitebox Fuzzing for Security Testing." Queue 10, no. 1 (January 2012): 20–27. http://dx.doi.org/10.1145/2090147.2094081.
Full textGao, Yifei, Xu Zhou, Wei Xie, Baosheng Wang, Enze Wang, and Zhenhua Wang. "Optimizing IoT Web Fuzzing by Firmware Infomation Mining." Applied Sciences 12, no. 13 (June 24, 2022): 6429. http://dx.doi.org/10.3390/app12136429.
Full textQu, Sheng, Zheng Zhang, Bolin Ma, and Yuwen Shao. "Optimization Method of Web Fuzzy Test Cases Based on Genetic Algorithm." Journal of Physics: Conference Series 2078, no. 1 (November 1, 2021): 012015. http://dx.doi.org/10.1088/1742-6596/2078/1/012015.
Full textDissertations / Theses on the topic "Security, Fuzzing"
Sayed, Shereef. "Black-Box Fuzzing of the REDHAWK Software Communications Architecture." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/54566.
Full textMaster of Science
Sletmo, Patrik. "Introducing probabilities within grey-box fuzzing." Thesis, Linköpings universitet, Databas och informationsteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-161893.
Full textMcDonough, Kenton Robert. "Torpedo: A Fuzzing Framework for Discovering Adversarial Container Workloads." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104159.
Full textMaster of Science
Over the last decade, container technology has fundamentally changed the landscape of commercial cloud computing services. By abstracting away many of the system details required to deploy software, developers can rapidly prototype, deploy, and take advantage of massive distributed frameworks when deploying new software products. These paradigms are supported with corresponding business models offered by cloud providers, who allocate space on powerful physical hardware among many potentially competing services. Unfortunately, recent work has shown that the isolation guarantees provided by containers are not absolute. Due to inconsistencies in the way containers have been implemented by the Linux kernel, there exist vulnerabilities that allow containerized programs to generate "out of band" workloads and negatively impact the performance of other containers. In general, these vulnerabilities are difficult to identify, but can be very severe. In this work, we present TORPEDO, a set of modifications to the SYZKALLER fuzzing framework that creates containerized workloads and searches for programs that negatively impact other containers. TORPEDO uses a novel technique that combines resource monitoring with code coverage approximations, and initial testing on common container software has revealed new interesting vulnerabilities and bugs.
Dutta, Rahul Kumar. "A Framework for Software Security Testing and Evaluation." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121645.
Full textDuchene, Fabien. "Detection of web vulnerabilities via model inference assisted evolutionary fuzzing." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM022/document.
Full textTesting is a viable approach for detecting implementation bugs which have a security impact, a.k.a. vulnerabilities. When the source code is not available, it is necessary to use black-box testing techniques. We address the problem of automatically detecting a certain class of vulnerabilities (Cross Site Scripting a.k.a. XSS) in web applications in a black-box test context. We propose an approach for inferring models of web applications and fuzzing from such models and an attack grammar. We infer control plus taint flow automata, from which we produce slices, which narrow the fuzzing search space. Genetic algorithms are then used to schedule the malicious inputs which are sent to the application. We incorporate a test verdict by performing a double taint inference on the browser parse tree and combining this with taint aware vulnerability patterns. Our implementations LigRE and KameleonFuzz outperform current open-source black-box scanners. We discovered 0-day XSS (i.e., previously unknown vulnerabilities) in web applications used by millions of users
Huang, Jin. "Detecting Server-Side Web Applications with Unrestricted File Upload Vulnerabilities." Wright State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=wright163007760528389.
Full textLone, Sang Fernand. "Protection des systèmes informatiques contre les attaques par entrées-sorties." Phd thesis, INSA de Toulouse, 2012. http://tel.archives-ouvertes.fr/tel-00863020.
Full textPotnuru, Srinath. "Fuzzing Radio Resource Control messages in 5G and LTE systems : To test telecommunication systems with ASN.1 grammar rules based adaptive fuzzer." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-294140.
Full text5G-telekommunikationssystem måste vara extremt tillförlitliga för att möta behoven för den kommande utvecklingen inom kommunikation. Systemen som används måste testas noggrant och måste överensstämma med deras standarder. Programvara och nätverksprotokoll testas ofta med tekniker som fuzzing, penetrationstest, kodgranskning, testning av överensstämmelse. Med fuzzing kan testare skicka utformade input för att övervaka System Under Test (SUT) för ett svar. 3GPP, standardiseringsorganet för telekomsystemet, producerar ofta nya versioner av specifikationer för att möta kraven och bristerna från tidigare utgåvor. Detta leder till många versioner av specifikationer för ett nätverksprotokoll som Radio Resource Control (RRC) och testare behöver ständigt uppdatera testverktygen och testmiljön. I detta arbete visar vi att genom att använda den generiska karaktären av RRC-specifikationer, som ges i beskrivningsspråket Abstract Syntax Notation One (ASN.1), kan man designa ett testverktyg för att anpassa sig till alla versioner av 3GPP-specifikationer. Detta uppsatsarbete introducerar en ASN.1-baserad adaptiv fuzzer som kan användas för att testa RRC och andra nätverksprotokoll baserat på ASN.1- beskrivningsspråk. Fuzzer extraherar kunskap om pågående RRC meddelanden med användning av protokollbeskrivningsfiler för RRC, dvs RRC ASN.1 schema från 3GPP, och använder kunskapen för att fuzz RRC meddelanden. Den adaptiva fuzzer identifierar enskilda fält, delmeddelanden och anpassade datatyper enligt specifikationer när innehållet i befintliga meddelanden muteras. Dessutom har den adaptiva fuzzer identifierat en tidigare oidentifierad sårbarhet i Evolved Packet Core (EPC) för srsLTE och openLTE, två opensource LTE-implementeringar, vilket bekräftar tillämpligheten för robusthetsprovning av RRC och andra nätverksprotokoll.
Ahmad, Abbas. "Model-Based Testing for IoT Systems : Methods and tools." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCD008/document.
Full textThe Internet of Things (IoT) is nowadays globally a mean of innovation and transformation for many companies. Applications extend to a large number of domains, such as smart cities, smart homes, healthcare, etc. The Gartner Group estimates an increase up to 21 billion connected things by 2020. The large span of "things" introduces problematic aspects, such as conformance and interoperability due to the heterogeneity of communication protocols and the lack of a globally-accepted standard. The large span of usages introduces problems regarding secure deployments and scalability of the network over large-scale infrastructures. This thesis deals with the problem of the validation of the Internet of Things to meet the challenges of IoT systems. For that, we propose an approach using the generation of tests from models (MBT). We have confronted this approach through multiple experiments using real systems thanks to our participation in international projects. The important effort which is needed to be placed on the testing aspects reminds every IoT system developer that doing nothing is more expensive later on than doing it on the go
(10746420), Hui Peng. "FUZZING HARD-TO-COVER CODE." Thesis, 2021.
Find full textBooks on the topic "Security, Fuzzing"
Takanen, Ari. Fuzzing for software security testing and quality assurance. Norwood, MA: Artech House, 2008.
Find full textFuzzing: Brute Force Vulnerability Discovery. Addison-Wesley Professional, 2007.
Find full textMichael, Sutton, Adam Greene, and Pedram Amini. Fuzzing: Brute Force Vulnerabiltiy Discovery. Pearson Education, Limited, 2007.
Find full textAri Takanen;Jared D. Demott;Charles Miller. Fuzzing for Software Security Testing and Quality Assurance. Artech House, 2018.
Find full textBook chapters on the topic "Security, Fuzzing"
Li, Xiaoting, Xiao Liu, Lingwei Chen, Rupesh Prajapati, and Dinghao Wu. "FuzzBoost: Reinforcement Compiler Fuzzing." In Information and Communications Security, 359–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15777-6_20.
Full textTakanen, Ari. "Proactive Security Testing and Fuzzing." In ISSE 2009 Securing Electronic Business Processes, 312–19. Wiesbaden: Vieweg+Teubner, 2010. http://dx.doi.org/10.1007/978-3-8348-9363-5_31.
Full textAl Sardy, Loui, Andreas Neubaum, Francesca Saglietti, and Daniel Rudrich. "Comparative Evaluation of Security Fuzzing Approaches." In Lecture Notes in Computer Science, 49–61. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26250-1_4.
Full textShin, MinSik, JungBeen Yu, YoungJin Yoon, and Taekyoung Kwon. "The Fuzzing Awakens: File Format-Aware Mutational Fuzzing on Smartphone Media Server Daemons." In ICT Systems Security and Privacy Protection, 219–32. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58469-0_15.
Full textOuairy, Léopold, Hélène Le-Bouder, and Jean-Louis Lanet. "Protection of Systems Against Fuzzing Attacks." In Foundations and Practice of Security, 156–72. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18419-3_11.
Full textvan Rooij, Orpheas, Marcos Antonios Charalambous, Demetris Kaizer, Michalis Papaevripides, and Elias Athanasopoulos. "webFuzz: Grey-Box Fuzzing for Web Applications." In Computer Security – ESORICS 2021, 152–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88418-5_8.
Full textShudrak, Maksim O., and Vyacheslav V. Zolotarev. "Improving Fuzzing Using Software Complexity Metrics." In Information Security and Cryptology - ICISC 2015, 246–61. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30840-1_16.
Full textKim, Hyuntae, Seongil Wi, Hyunjoo Lee, and Sooel Son. "FSF: Code Coverage-Driven Fuzzing for Software-Defined Networking." In Information Security Applications, 41–54. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39303-8_4.
Full textFan, Rong, and Yaoyao Chang. "Machine Learning for Black-Box Fuzzing of Network Protocols." In Information and Communications Security, 621–32. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89500-0_53.
Full textVinçont, Yaëlle, Sébastien Bardin, and Michaël Marcozzi. "A Tight Integration of Symbolic Execution and Fuzzing (Short Paper)." In Foundations and Practice of Security, 303–10. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08147-7_20.
Full textConference papers on the topic "Security, Fuzzing"
Smith, Christopher, and Guillermo Francia. "Security fuzzing toolset." In the 50th Annual Southeast Regional Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2184512.2184589.
Full textBottinger, Konstantin, Patrice Godefroid, and Rishabh Singh. "Deep Reinforcement Fuzzing." In 2018 IEEE Security and Privacy Workshops (SPW). IEEE, 2018. http://dx.doi.org/10.1109/spw.2018.00026.
Full textNagy, Stefan, and Matthew Hicks. "Full-Speed Fuzzing: Reducing Fuzzing Overhead through Coverage-Guided Tracing." In 2019 IEEE Symposium on Security and Privacy (SP). IEEE, 2019. http://dx.doi.org/10.1109/sp.2019.00069.
Full textGelderie, Marcus, Valentin Barth, Maximilian Luff, and Julian Birami. "Seccomp Filters from Fuzzing." In 19th International Conference on Security and Cryptography. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0011145100003283.
Full textBöhme, Marcel, Van-Thuan Pham, Manh-Dung Nguyen, and Abhik Roychoudhury. "Directed Greybox Fuzzing." In CCS '17: 2017 ACM SIGSAC Conference on Computer and Communications Security. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3133956.3134020.
Full textZhu, Xiaogang, and Marcel Böhme. "Regression Greybox Fuzzing." In CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3460120.3484596.
Full textKim, Hyoungchun, Younghan Choi, Dohoon Lee, and Donghoon Lee. "Practical Security Testing using File Fuzzing." In 2008 10th International Conference on Advanced Communication Technology. IEEE, 2008. http://dx.doi.org/10.1109/icact.2008.4494003.
Full textCha, Sang Kil, Maverick Woo, and David Brumley. "Program-Adaptive Mutational Fuzzing." In 2015 IEEE Symposium on Security and Privacy (SP). IEEE, 2015. http://dx.doi.org/10.1109/sp.2015.50.
Full textGan, Shuitao, Chao Zhang, Xiaojun Qin, Xuwen Tu, Kang Li, Zhongyu Pei, and Zuoning Chen. "CollAFL: Path Sensitive Fuzzing." In 2018 IEEE Symposium on Security and Privacy (SP). IEEE, 2018. http://dx.doi.org/10.1109/sp.2018.00040.
Full textRawat, Sanjay, Vivek Jain, Ashish Kumar, Lucian Cojocar, Cristiano Giuffrida, and Herbert Bos. "VUzzer: Application-aware Evolutionary Fuzzing." In Network and Distributed System Security Symposium. Reston, VA: Internet Society, 2017. http://dx.doi.org/10.14722/ndss.2017.23404.
Full textReports on the topic "Security, Fuzzing"
Ruthruff, Joseph R., Robert C. Armstrong, Benjamin Garry Davis, Jackson R. Mayo, and Ratish J. Punnoose. Leveraging Formal Methods and Fuzzing to Verify Security and Reliability Properties of Large-Scale High-Consequence Systems. Office of Scientific and Technical Information (OSTI), September 2012. http://dx.doi.org/10.2172/1117263.
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