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Thou Shalt Discuss Security: Quantifying the Impacts of Instructions to RFC Authors

Published:11 November 2019Publication History

ABSTRACT

The importance of secure development of new technologies is unquestioned, yet the best methods to achieve this goal are far from certain. A key issue is that while significant effort is given to evaluating the outcomes of development (e.g., security of a given project), it is far more difficult to determine what organizational practices result in secure projects. In this paper, we quantitatively examine efforts to improve the consideration of security in Requests for Comments (RFCs)--- the design documents for the Internet and many related systems --- through the mandates and guidelines issued to RFC authors. We begin by identifying six metrics that quantify the quantity and quality of security informative content. We then apply these metrics longitudinally over 8,437 documents and 49 years of development to determine whether guidance to RFC authors changed these security metrics in later documents. We find that even a simply worded --- but effectively enforced --- mandate to explicitly consider security created a significant effect in increased discussion and topic coverage of security content both in and outside of a mandated security considerations section. We find that later guidelines with more detailed advice on security also improve both volume and quality of security informative content in RFCs. Our work demonstrates that even modest amounts of guidance can correlate to significant improvements in security focus in RFCs, indicating a promising approach for other network standards bodies.

References

  1. 2019. Internet Engineering Task Force. https://www.ietf.org/.Google ScholarGoogle Scholar
  2. 2019. RFC Editor. https://www.rfc-editor.orgGoogle ScholarGoogle Scholar
  3. Y. Acar, C. Stransky , D. Wermke, C. Weir , M. L. Mazurek, and S. Fahl. 2017. Developers Need Support, Too: A Survey of Security Advice for Software Developers. In 2017 IEEE Cybersecurity Development (SecDev). 22--26.Google ScholarGoogle Scholar
  4. Chetan Arora, Mehrdad Sabetzadeh, Lionel C. Briand, and Frank Zimmer. 2015. Automated Checking of Conformance to Requirements Templates Using Natural Language Processing. IEEE Transactions on Software Engineering, Vol. 41 (2015), 944--968.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. David Basin, Jannik Dreier, Lucca Hirschi, Saga Radomirovic, Ralf Sasse, and Vincent Stettler. 2018. A Formal Analysis of 5G Authentication. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security (CCS '18). ACM, New York, NY, USA, 1383--1396. https://doi.org/10.1145/3243734.3243846Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. M. Bjorklund, J. Schoenwaelder, P. Shafer, K. Watsen, and R. Wilton. 2018. Network Management Datastore Architecture (NMDA). RFC 8342. RFC Editor.Google ScholarGoogle Scholar
  7. D Ceccarelli and Y Lee. 2018. Framework for Abstraction and Control of TE Networks (ACTN). RFC 8453. RFC Editor.Google ScholarGoogle Scholar
  8. Taejoong Chung, Roland van Rijswijk-Deij, Balakrishnan Chandrasekaran, David Choffnes, Dave Levin, Bruce M Maggs, Alan Mislove, and Christo Wilson. 2017. A Longitudinal, End-to-End View of the DNSSEC Ecosystem. In 26th USENIX Security Symposium. 1307--1322.Google ScholarGoogle Scholar
  9. Cas Cremers and Martin Dehnel-Wild. 2019. Component-Based Formal Analysis of 5G-AKA: Channel Assumptions and Session Confusion. In Proceedings 2019 Network and Distributed System Security Symposium. Internet Society, San Diego, CA. https://doi.org/10.14722/ndss.2019.23394Google ScholarGoogle ScholarCross RefCross Ref
  10. Steve Crocker. 1969. Host Software. RFC 1. RFC Editor.Google ScholarGoogle Scholar
  11. Breno Dantas Cruz, Bargav Jayaraman, Anurag Dwarakanath, and Collin McMillan. 2017. Detecting Vague Words & Phrases in Requirements Documents in a Multilingual Environment. 2017 IEEE 25th International Requirements Engineering Conference (RE) (2017), 233--242.Google ScholarGoogle ScholarCross RefCross Ref
  12. Alex Dekhtyar and Vivian Fong. 2017. RE Data Challenge: Requirements Identification with Word2Vec and TensorFlow. 2017 IEEE 25th International Requirements Engineering Conference (RE) (2017), 484--489.Google ScholarGoogle ScholarCross RefCross Ref
  13. Vaibhav Hemant Dixit, Adam Doupé, Yan Shoshitaishvili, Ziming Zhao, and Gail-Joon Ahn. 2018. AIM-SDN: Attacking Information Mismanagement in SDN-datastores. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. ACM, 664--676.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Alessio Ferrari, Beatrice Donati, and Stefania Gnesi. 2017. Detecting Domain-Specific Ambiguities: An NLP Approach Based on Wikipedia Crawling and Word Embeddings. 2017 IEEE 25th International Requirements Engineering Conference Workshops (REW) (2017), 393--399.Google ScholarGoogle Scholar
  15. Alessio Ferrari, Giuseppe Lipari, Stefania Gnesi, and Giorgio Oronzo Spagnolo. 2014. Pragmatic ambiguity detection in natural language requirements. 2014 IEEE 1st International Workshop on Artificial Intelligence for Requirements Engineering (AIRE) (2014), 1--8.Google ScholarGoogle ScholarCross RefCross Ref
  16. H Flanagan and S Ginoza. 2014. RFC Style Guide. RFC 7322. RFC Editor. https://www.rfc-editor.org/rfc/rfc7322.txtGoogle ScholarGoogle Scholar
  17. Deen Freelon. 2010. Intercoder Reliability Calculation as a Web Service.Google ScholarGoogle Scholar
  18. Deen Freelon. 2013. ReCal OIR: Ordinal, Interval, and Ratio Intercoder Reliability as a Web Service.Google ScholarGoogle Scholar
  19. Michael Gegick, Pete Rotella, and Laurie A. Williams. 2009. Toward Non-security Failures as a Predictor of Security Faults and Failures. In ESSoS.Google ScholarGoogle Scholar
  20. Michael Gegick, Pete Rotella, and Tao Xie. 2010. Identifying security bug reports via text mining: An industrial case study. 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010) (2010), 11--20.Google ScholarGoogle ScholarCross RefCross Ref
  21. Michael Gegick and Laurie L. Williams. 2007. Toward the Use of Automated Static Analysis Alerts for Early Identification of Vulnerability- and Attack-prone Components. Second International Conference on Internet Monitoring and Protection (ICIMP 2007) (2007), 18--18.Google ScholarGoogle Scholar
  22. Stefania Gnesi, Giuseppe Lami, and Gianluca Trentanni. 2005. An automatic tool for the analysis of natural language requirements. Comput. Syst. Sci. Eng., Vol. 20 (2005).Google ScholarGoogle Scholar
  23. Sharon Goldberg. 2014. Why is it taking so long to secure internet routing? Commun. ACM, Vol. 57, 10 (2014), 56--63.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Alessandra Gorla, Ilaria Tavecchia, Florian Gross, and Andreas Zeller. 2014. Checking app behavior against app descriptions. In Proceedings of the 36th International Conference on Software Engineering. ACM, 1025--1035.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Emitza Guzman, Rana Mohammed A. Alkadhi, and Norbert Seyff. 2016. A Needle in a Haystack: What Do Twitter Users Say about Software? 2016 IEEE 24th International Requirements Engineering Conference (RE) (2016), 96--105.Google ScholarGoogle ScholarCross RefCross Ref
  26. Hamza Harkous, Kassem Fawaz, Rémi Lebret, Florian Schaub, Kang G. Shin, and Karl Aberer. 2018. Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning. In USENIX Security Symposium.Google ScholarGoogle Scholar
  27. Ghaith Husari, Ehab Al-Shaer, Mohiuddin Ahmed, Bill Chu, and Xi Niu. 2017. TTPDrill: Automatic and Accurate Extraction of Threat Actions from Unstructured Text of CTI Sources. In Proceedings of the 33rd Annual Computer Security Applications Conference (ACSAC 2017). ACM, New York, NY, USA, 103--115.Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Georgi M. Kanchev, Pradeep K. Murukannaiah, Amit K. Chopra, and Peter Sawyer. 2017. Canary: Extracting Requirements-Related Information from Online Discussions. 2017 IEEE 25th International Requirements Engineering Conference (RE) (2017), 31--40.Google ScholarGoogle ScholarCross RefCross Ref
  29. Jason King, Rahul Pandita, and Laurie A. Williams. 2015. Enabling forensics by proposing heuristics to identify mandatory log events. In HotSoS.Google ScholarGoogle Scholar
  30. Zijad Kurtanovic and Walid Maalej. 2017. Mining User Rationale from Software Reviews. 2017 IEEE 25th International Requirements Engineering Conference (RE) (2017), 61--70.Google ScholarGoogle ScholarCross RefCross Ref
  31. Walid Maalej and Hadeer Nabil. 2015. Bug report, feature request, or simply praise? On automatically classifying app reviews. 2015 IEEE 23rd International Requirements Engineering Conference (RE) (2015), 116--125.Google ScholarGoogle ScholarCross RefCross Ref
  32. Aaron K. Massey, Richard L. Rutledge, Annie I. Antón, and Peter P. Swire. 2014. Identifying and classifying ambiguity for regulatory requirements. 2014 IEEE 22nd International Requirements Engineering Conference (RE) (2014), 83--92.Google ScholarGoogle ScholarCross RefCross Ref
  33. Nadia Patricia Da Silva Medeiros, Naghmeh Ivaki, Pedro Costa, and Marco Vieira. 2017. Software Metrics as Indicators of Security Vulnerabilities. IEEE 28th International Symposium on Software Reliability Engineering (2017), 216--227.Google ScholarGoogle Scholar
  34. Patrick Morrison, Benjamin A H Smith, and Laurie A. Williams. 2017. Measuring Security Practice Use: A Case Study at IBM. 2017 IEEE/ACM 5th International Workshop on Conducting Empirical Studies in Industry (CESI) (2017), 16--22.Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Mavuto Mukaka. 2012. Statistics corner: A guide to appropriate use of correlation coefficient in medical research. Malawi medical journal: the journal of Medical Association of Malawi, Vol. 24 3 (2012), 69--71.Google ScholarGoogle Scholar
  36. Nuthan Munaiah, Andrew Meneely, and Pradeep K. Murukannaiah. 2017. A Domain-Independent Model for Identifying Security Requirements. 2017 IEEE 25th International Requirements Engineering Conference (RE) (2017), 506--511.Google ScholarGoogle ScholarCross RefCross Ref
  37. Tuong Huan Nguyen, John C. Grundy, and Mohamed Almorsy. 2014. GUITAR: An ontology-based automated requirements analysis tool. 2014 IEEE 22nd International Requirements Engineering Conference (RE) (2014), 315--316.Google ScholarGoogle ScholarCross RefCross Ref
  38. Olga Ormandjieva, Ishrar Hussain, and Leila Kosseim. 2007. Toward a text classification system for the quality assessment of software requirements written in natural language. In SOQUA .Google ScholarGoogle Scholar
  39. Rahul Pandita, Kunal Taneja, Laurie A. Williams, and Teresa Tung. 2016. ICON: Inferring Temporal Constraints from Natural Language API Descriptions. 2016 IEEE International Conference on Software Maintenance and Evolution (ICSME) (2016), 378--388.Google ScholarGoogle ScholarCross RefCross Ref
  40. Rahul Pandita, Xusheng Xiao, Wei Yang, William Enck, and Tao Xie. 2013. WHYPER: Towards Automating Risk Assessment of Mobile Applications.. In USENIX Security Symposium, Vol. 2013.Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. D. Piper. 1998. The Internet IP Security Domain of Interpretation for ISAKMP. RFC 2407. RFC Editor.Google ScholarGoogle Scholar
  42. J Postel. 1993. Instructions to RFC Authors. RFC 1543. RFC Editor. https://www.rfc-editor.org/rfc/rfc1543.txtGoogle ScholarGoogle Scholar
  43. J Postel and J Reynolds. 1997. Instructions to RFC Authors. RFC 2223. RFC Editor.Google ScholarGoogle Scholar
  44. Akond Rahman, Priysha Pradhan, Asif Partho, and Laurie A. Williams. 2017. Predicting Android Application Security and Privacy Risk with Static Code Metrics. 2017 IEEE/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft) (2017), 149--153.Google ScholarGoogle Scholar
  45. A Rajarman and J Ullman. 2011. "Mining of Massive Datasets". 1--17 pages.Google ScholarGoogle Scholar
  46. E Rescorla. 2033. Guidelines for Writing RFC Text on Security Considerations. RFC 3552. RFC Editor. https://www.rfc-editor.org/rfc/rfc3552.txtGoogle ScholarGoogle Scholar
  47. J Reynolds and J Postel. 1990. Assigned Numbers. RFC 1060. RFC Editor. https://www.rfc-editor.org/rfc/rfc1060.txtGoogle ScholarGoogle Scholar
  48. Shlomo S Sawilowsky. 2009. New effect size rules of thumb. (2009).Google ScholarGoogle Scholar
  49. Yonghee Shin, Andrew Meneely, Laurie A. Williams, and Jason A. Osborne. 2011. Evaluating Complexity, Code Churn, and Developer Activity Metrics as Indicators of Software Vulnerabilities. IEEE Transactions on Software Engineering, Vol. 37 (2011), 772--787.Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Yonghee Shin and Laurie A. Williams. 2011. An initial study on the use of execution complexity metrics as indicators of software vulnerabilities. In SESS@ICSE .Google ScholarGoogle Scholar
  51. Maninder Singh. 2018. Automated Validation of Requirement Reviews: A Machine Learning Approach. 2018 IEEE 26th International Requirements Engineering Conference (RE) (2018), 460--465.Google ScholarGoogle Scholar
  52. Ben H. Smith and Laurie A. Williams. 2011. Using SQL Hotspots in a Prioritization Heuristic for Detecting All Types of Web Application Vulnerabilities. 2011 Fourth IEEE International Conference on Software Testing, Verification and Validation (2011), 220--229.Google ScholarGoogle Scholar
  53. John W. Stamey and Ryan A. Rossi. 2009. Automatically identifying relations in privacy policies. In SIGDOC.Google ScholarGoogle Scholar
  54. M. Stapp, T. Lemon, and A. Gustafsson. 2006. A DNS Resource Record (RR) for Encoding Dynamic Host Configuration Protocol (DHCP) Information (DHCID RR). RFC 4701. RFC Editor.Google ScholarGoogle Scholar
  55. M. Stiemerling, J. Quittek, and T. Taylor. 2005. Middlebox Communications (MIDCOM) Protocol Semantics. RFC 3989. RFC Editor.Google ScholarGoogle Scholar
  56. Saurabh Tiwari and Mayank Laddha. 2017. UCAnalyzer: A Tool to Analyze Use Case Textual Descriptions. 2017 IEEE 25th International Requirements Engineering Conference (RE) (2017), 448--449.Google ScholarGoogle ScholarCross RefCross Ref
  57. Alexander van den Berghe, Koen Yskout, Riccardo Scandariato, and Wouter Joosen. 2018. A Lingua Franca for Security by Design. 2018 IEEE Cybersecurity Development (SecDev) (2018), 69--76.Google ScholarGoogle Scholar
  58. Mathy Vanhoef and Frank Piessens. 2017. Key Reinstallation Attacks: Forcing Nonce Reuse in WPA2. In Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security (CCS '17). ACM, New York, NY, USA, 1313--1328. https://doi.org/10.1145/3133956.3134027Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. Theresa Wilson, Janyce Wiebe, and Paul Hoffmann. 2005. Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing.Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. Xusheng Xiao, Amit M. Paradkar, Suresh Thummalapenta, and Tao Xie. 2012. Automated extraction of security policies from natural-language software documents. In SIGSOFT FSE .Google ScholarGoogle Scholar
  61. Hui Yang, Anne N. De Roeck, Vincenzo Gervasi, Alistair Willis, and Bashar Nuseibeh. 2011. Analysing anaphoric ambiguity in natural language requirements. Requirements Engineering, Vol. 16 (2011), 163--189.Google ScholarGoogle ScholarDigital LibraryDigital Library
  62. Razieh Nokhbeh Zaeem, Rachel L. German, and K. Suzanne Barber. 2018. PrivacyCheck: Automatic Summarization of Privacy Policies Using Data Mining. ACM Trans. Internet Techn., Vol. 18 (2018), 53:1--53:18.Google ScholarGoogle ScholarDigital LibraryDigital Library
  63. Thomas Zimmermann, Nachiappan Nagappan, and Laurie A. Williams. 2010. Searching for a Needle in a Haystack: Predicting Security Vulnerabilities for Windows Vista. 2010 Third International Conference on Software Testing, Verification and Validation (2010), 421--428.Google ScholarGoogle ScholarDigital LibraryDigital Library

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      • Published in

        cover image ACM Conferences
        SSR'19: Proceedings of the 5th ACM Workshop on Security Standardisation Research Workshop
        November 2019
        87 pages
        ISBN:9781450368322
        DOI:10.1145/3338500

        Copyright © 2019 ACM

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        • Published: 11 November 2019

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