A flexible service selection for executing virtual services

[EN] With the adoption of a service-oriented paradigm on the Web, many software services are likely to fulfil similar functional needs for end-users. We propose to aggregate functionally equivalent software services within one single virtual service, that is, to associate a functionality, a graphical user interface (GUI), and a set of selection rules. When an end user invokes such a virtual service through its GUI to answer his/her functional need, the software service that best responds to the end-user s selection policy is selected and executed and the result is then rendered to the end-user through the GUI of the virtual service. A key innovation in this paper is the flexibility of our proposed service selection policy. First, each selection policy can refer to heterogeneous parameters (e.g., service price, end-user location, and QoS). Second, additional parameters can be added to an existing or new policy with little investment. Third, the end users themselves define a selection policy to apply during the selection process, thanks to the GUI element added as part of the virtual service design. This approach was validated though the design, implementation, and testing of an end-to-end architecture, including the implementation of several virtual services and utilizing several software services available today on the Web.This work was partially supported in part by SERVERY (Service Platform for Innovative Communication Environment), a CELTIC project that aims to create a Service Marketplace that bridges the Internet and Telco worlds by merging the flexibility and openness of the former with the trustworthiness and reliability of the latter, enabling effective and profitable cooperation among actors.Laga, N.; Bertin, E.; Crespi, N.; Bedini, I.; Molina Moreno, B.; Zhao, Z. (2013). A flexible service selection for executing virtual services. World Wide Web. 16(3):219-245. doi:10.1007/s11280-012-0184-2S219245163Aggarwal, R., Verma, K., Miller, J., and Milnor, W.: Constraint Driven Web Service Composition in METEOR-S. In Proceedings of the 2004 IEEE international Conference on Services Computing (September 2004). IEEE Computer Society, Washington, DC, 23–30.Apple Inc. Apple app store.: Available at: www.apple.com/iphone/appstore/ , accessed on May 22nd, 2012.Atzeni, P., Catarci, T., Pernici, B.: Multi-Channel adaptive information Systems. World Wide Web 10(4), 345–347 (2007)Baresi, L., Bianchini, D., Antonellis, V.D., Fugini, M.G., Pernici, B., Plebani, P.: Context-aware Composition of e-Service. In Technologies for E-Services: Third International Workshop, vol. 2819, 28–41, TES 2003, Berlin, German, 2003.Ben Hassine, A., Matsubara, S., Ishida, T.: In Proceedings of the 5th international conference on The Semantic Web (ISWC’06), Isabel Cruz, Stefan Decker, Dean Allemang, Chris Preist, and Daniel Schwabe (Eds.). Springer-Verlag, Berlin, Heidelberg, 130–143 (2006).Blum, N., Dutkowski, S., Magedanz, T.: InSeRt - An Intent-based Service Request API for Service Exposure in Next Generation Networks. In Proceedings of 32nd Annual IEEE Software Engineering Workshop. Porto Sani Resort, Kassandra, Greece, 2008 pp21–30.Boussard, M., Fodor, S., Crespi, N., Iribarren, V., Le Rouzic, J.P., Bedini, I., Marton, G., Moro Fernandez, D., Lorenzo Duenas, O., Molina, B.: SERVERY: the Web-Telco marketplace. ICT-Mobile Summit 2009, Santander (2009)Cabrera, Ó., Oriol, M., Franch, X., Marco, J., López, L., Fragoso, O., Santaolaya, R.: WeSSQoS: A Configurable SOA System for Quality-aware Web Service Selection. CoRR 2011, abs/1110.5574.Casati, F., Ilnicki, S., Jin, L., Krishnamoorthy, V., Shan, M.: Adaptive and Dynamic Service Composition in eFlow. Lecture Notes in Computer Science, Volume 1789/2000, 13–31, 2000.Cibrán, M. A., Verheecke, B., Vanderperren, W., Suvée, D., and Jonckers, V.: “Aspect-oriented Programming for Dynamic Web Service Selection, Integration and Management.” In Proc. World Wide Web 2007, pp. 211–242.Crespi, N., Boussard, M. Fodor, S.: Converging Web 2.0 with telecommunications. eStrategies Projects, Vol. 10, 108–109. British Publishers, ISSN 1758–2369, June 2009.Dey, A.K., Salber, D., Abowd, G.D.: A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Hum. Comput. Interact. 16, 1–67 (2001)Ding, Q., Li, X., and Zhou, X.: Reputation Based Service Selection in Grid Environment. In Proceedings of the 2008 international Conference on Computer Science and Software Engineering - Volume 03 (December. 2008). CSSE. IEEE Computer Society, Washington, DC, 58–61.Fielding, R.T.: Architectural Styles and the Design of Network-based Software Architectures. Thesis dissertation, 2000.Franch, X., Grünbacher, P., Oriol, M., Burgstaller, B., Dhungana, D., López, L., Marco, J., Pimentel, J.: Goal-driven Adaptation of Service-Based Systems from Runtime Monitoring Data. REFS 2011.Frolund, S., Koisten, J.: QML: A Language for Quality of Service Specification. HP Labs technical reports. Available at http://www.hpl.hp.com/techreports/98/HPL-98-10.html , accessed on May 22nd, 2012.Google. Android market.: Available at: www.android.com/market/ , accessed on May 22nd, 2012.Google. Intents and Intent Filters.: Available at http://developer.android.com/guide/topics/intents/intents-filters.html , accessed on May 22nd, 2012.Gu, X., Nahrstedt, K., Yuan, W., Wichadakul, D., Xu, D.: An Xml-Based Quality of Service Enabling Language for the Web. Technical Report. UMI Order Number: UIUCDCS-R-2001-2212., University of Illinois at Urbana-Champaign.Laga, N., Bertin, E., and Crespi, N.: Building a User Friendly Service Dashboard: Automatic and Non-intrusive Chaining between Widgets. In Proceedings of the 2009 Congress on Services - I (July 06–10, 2009). SERVICES. IEEE Computer Society, Washington, DC, 484–491.Laga, N., Bertin, E., and Crespi, N.: Business Process Personalization Through Web Widgets. In Proceedings of the 2010 IEEE international Conference on Web Services (July 05–10, 2010). ICWS. IEEE Computer Society, Washington, DC, 551–558.Liu, Y., Ngu, A. H., and Zeng, L. Z.: QoS computation and policing in dynamic web service selection. In Proceedings of the 13th international World Wide Web Conference on Alternate Track Papers &Amp; Posters (New York, NY, USA, May 19–21, 2004). WWW Alt. ’04. ACM, New York, NY, 66–73.Malik, Z., Bouguettaya, A.: Rater credibility assessment in Web services interactions. World Wide Web 12(1), 3–25 (2009)Martin, D. et al.: OWL-S: Semantic Markup for Web Services. W3C member submission, available at http://www.w3.org/Submission/2004/SUBM-OWL-S-20041122/ , accessed on May 22nd, 2012.Nestler, T., Namoun, A., Schill, A.: End-user development of service-based interactive web applications at the presentation layer. EICS 2011: 197–206.Newcomer, E.: Understanding Web Services: XML, Wsdl, Soap, and UDDI. Addison, Wesley, Boston, Mass., May 2002.O’Reilly, T.: What Is Web 2.0, Design Patterns and Business Models for the Next Generation of Software.Piessens, F., Jacobs, B., Truyen, E., Joosen, W.: Support for Metadata-driven Selection of Run-time Services in .NET is Promising but Immature. vol. 3, no. 2, Special issue: .NET: The Programmer’s Perspective: ECOOP Workshop, 27–35. 2003.Rasch, K;, Li, F., Sehic, S., Ayani R., and Dustdar, S.: “Context-driven personalized service discovery in pervasive environments,” in Proc World Wide Web, 2011, pp. 295–319.Reichl, P.: From ‘Quality-of-Service’ and ‘Quality-of-Design’ to ‘Quality-of-Experience’: A holistic view on future interactive telecommunication ser-vices. In 15th International Conference on Software, Telecommunications and Computer Networks, 2007. Soft-COM 2007. Sept. 2007. vol., no.,1–6, 27–29.Rolland, C., Kaabi, R.S., Kraiem, N.: On ISOA: Intentional Services Oriented Architecture. In Advanced Information Systems Engineering, volume 4495/2007, 158–172, June 2007.Sanchez, A., Carro, B., Wesner, S.: Telco services for end customers: European Perspective. In Communications Magazine. IEEE 46(2), 14–18 (2008)Santhanam, G. R., Basu, S., and Honavar, V.: On Utilizing Qualitative Preferences in Web Service Composition: A CP-net Based Approach. In Proceedings of IEEE Congress on Services, Services - Part I, vol., no.,538–544, 2008.Spanoudakis, G., Mahbub, K., Zisman, A.: A Platform for Context Aware Runtime Web Service Discovery. In Proc IEEE ICWS, 2007, pp233-240.Tsesmetzis, D., Roussaki, I., Sykas, E.: Modeling and Simulation of QoS-aware Web Service Selection for Provider Profit Maximization. Simulation 83(1), 93–106 (2007)Wang, P., Chao, K., Lo, C., Farmer, R., and Kuo, P.: A Reputation-Based Service Selection Scheme. In Proceedings of the 2009 IEEE international Conference on E-Business Engineering (October 21–23, 2009). ICEBE. IEEE Computer Society, Washington, DC, 501–506.Wang, H., Yang, D., Zhao, Y., and Gao, Y.: Multiagent System for Reputation--based Web Services Selection. In Proceedings of the Sixth international Conference on Quality Software (October 27–28, 2006). QSIC. IEEE Computer Society, Washington, DC, 429–434.Wholesale Applications Community.: WAC Informational Whitepaper. Available at http://www.wholesaleappcommunity.com/About-Wac/BACKGROUND%20TO%20WAC/whitepaper.pdf , accessed on May 22nd, 2012.Windows Marketplace.: Available at http://marketplace.windowsphone.com/default.aspx , accessed on May 22nd, 2012.Xu, Z., Martin, P., Powley, W., Zulkernine, F.: Reputation-Enhanced QoS-based Web Services Discovery. Web Services, 2007. In proceedings of IEEE International Conference on Web Services, ICWS 2007. 249, 256, 9–13 July 2007.Yu, Q., Bouguettaya,A.: “Multi-attribute optimization in service selection”. In Proc World Wide Web,2012, pp. 1–31.Yu, T., Zhang, Y., Lin, K. Efficient algorithms for Web services selection with end-to-end QoS constraints. ACM Transaction Web 1, 1. Article 6, 26 pages. (May 2007),

SSPFA: Effective Stack Smashing Protection for Android OS

[EN] In this paper, we detail why the stack smashing protector (SSP), one of the most effective techniques to mitigate stack bufferoverflow attacks, fails to protect the Android operating system and thus causes a false sense of security that affects all Androiddevices. We detail weaknesses of existing SSP implementations, revealing that current SSP is not secure. We propose SSPFA,the first effective and practical SSP for Android devices. SSPFA provides security against stack buffer overflows withoutchanging the underlying architecture. SSPFA has been implemented and tested on several real devices showing that it is notintrusive, and it is binary-compatible with Android applications. Extensive empirical validation has been carried out over theproposed solution.This work was partially funded by Universitat Politecnica de Valencia (Grant No. 20160251-ASLR-NG).Marco Gisbert, H.; Ripoll Ripoll, JI. (2019). SSPFA: Effective Stack Smashing Protection for Android OS. International Journal of Information Security. 18(4):519-532. https://doi.org/10.1007/s10207-018-00425-8S519532184Buchanan, W.J., Chiale, S., Macfarlane, R.: A methodology for the security evaluation within third-party android marketplaces. Digit. Investig. 23(Supplement C), 88–98 (2017). https://doi.org/10.1016/j.diin.2017.10.002Tian, D., Jia, X., Chen, J., Hu, C., Xue, J.: A practical online approach to protecting kernel heap buffers in kernel modules. China Commun. 1, 143–152 (2016)One, A.: Smashing the stack for fun and profit. Phrack, 7(49) (1996)Younan, Y., Pozza, D., Piessens, F., Joosen, W.: Extended protection against stack smashing attacks without performance loss. In: In Proceedings of ACSAC (2006)Abadi, M., Budiu, M., Erlingsson, U., Ligatti, J.: Control-flow Integrity. In: Proceedings of the 12th ACM Conference on Computer and Communications Security, Series CCS ’05, pp. 340–353. ACM, New York (2005). https://doi.org/10.1145/1102120.1102165Wartell, R., Mohan, V., Hamlen, K.W., Lin, Z.: Binary stirring: self-randomizing instruction addresses of legacy x86 binary code. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security, Series CCS ’12, pp. 157–168. ACM, New York (2012). https://doi.org/10.1145/2382196.2382216Roglia, G.F., Martignoni, L., Paleari, R., Bruschi, D.: Surgically returning to randomized lib(c). In: Proceedings of the 2009 Annual Computer Security Applications Conference, Series ACSAC ’09, pp. 60–69. IEEE Computer Society, Washington (2009). https://doi.org/10.1109/ACSAC.2009.16Roemer, R., Buchanan, E., Shacham, H., Savage, S.: Return-oriented programming: systems, languages, and applications. ACM Trans. Inf. Syst. Secur. 15(1), 2:1–2:34 (2012). https://doi.org/10.1145/2133375.2133377Pappas, V., Polychronakis, M., Keromytis, A.: Smashing the gadgets: hindering return-oriented programming using in-place code randomization. In: 2012 IEEE Symposium on Security and Privacy (SP), pp. 601–615 (2012)S. R. to Thwart Return Oriented Programming in Embedded Systems, Stack Redundancy to Thwart Return Oriented Programming in Embedded Systems, IEEE Embedded Systems Letters, vol. (first on-line), pp. 1–1 (2018)Moula, V., Niksefat, S.: ROPK++: an enhanced ROP attack detection framework for Linux operating system. In: International Conference on Cyber Security And Protection Of Digital Services (Cyber Security). IEEE (2017)Das, S., Zhang, W., Liu, Y.: A fine-grained control flow integrity approach against runtime memory attacks for embedded systems. IEEE Trans. Very Large Scale Integr. VLSI Syst. 25, 3193–3207 (2016)Alam, M., Roy, D.B., Bhattacharya, S., Govindan, V., Chakraborty, R.S., Mukhopadhyay, D.: SmashClean: a hardware level mitigation to stack smashing attacks in OpenRISC. In: ACM/IEEE International Conference on Formal Methods and Models for System Design (MEMOCODE), pp. 1–4. IEEE (2016)Kananizadeh, S., Kononenko, K.: Development of dynamic protection against timing channels. Int. J. Inf. Secur. 16, 641–651 (2017)Bhatkar, S., DuVarney, D.C., Sekar, R.: Address obfuscation: an efficient approach to combat a board range of memory error exploits. In: Proceedings of the 12th Conference on USENIX Security Symposium—volume 12, Series SSYM’03, p. 8. USENIX Association, Berkeley (2003). http://dl.acm.org/citation.cfm?id=1251353.1251361 . Accessed 18 Jan 2019Snow, K.Z., Monrose, F., Davi, L., Dmitrienko, A., Liebchen, C., Sadeghi, A.-R.: Just-in-time code reuse: on the effectiveness of fine-grained address space layout randomization. In: 2013 IEEE Symposium on Security and Privacy (SP), pp. 574–588. IEEE (2013)Kumar, K.S., Kisore, N.R.: Protection against buffer overflow attacks through runtime memory layout randomization. In: International Conference on Information Technology (ICIT). IEEE (2014)Oberheide, J.: A look at ASLR in Android ice cream sandwich 4.0 (2012). https://www.duosecurity.com/blog/a-look-at-aslr-in-android-ice-cream-sandwich-4-0 . Accessed 18 Jan 2019Zabrocki, A.P.: Scraps of notes on remote stack overflow exploitation (2010). http://www.phrack.org/issues.html?issue=67&id=13#article . Accessed 18 Jan 2019Saito, T., Watanabe, R., Kondo, S., Sugawara, S., Yokoyama, M.: A survey of prevention/mitigation against memory corruption attacks. In: 19th International Conference on Network-Based Information Systems (NBiS). IEEE (2016)Meike, G.B.: Inside the Android OS: Building, Customizing, Managing and Operating Android System Services, illustrated ed., P. Education, Ed. Pearson Education, vol. 1 (2018). https://www.amazon.com/Inside-Android-OS-Customizing-Operating/dp/0134096347?SubscriptionId=0JYN1NVW651KCA56C102&tag=techkie-20&linkCode=xm2&camp=2025&creative=165953&creativeASIN=0134096347 . Accessed 18 Jan 2019Cowan, C., Pu, C., Maier, D., Hintongif, H., Walpole, J., Bakke, P., Beattie, S., Grier, A., Wagle, P., Zhang, Q.: StackGuard: automatic adaptive detection and prevention of buffer-overflow attacks. In: Proceedings of the 7th USENIX Security Symposium, pp. 63–78 (1998)’xorl’: Linux GLibC stack canary values (2010). http://xorl.wordpress.com/2010/10/14/linux-glibc-stack-canary-values/ . Accessed 18 Jan 2019Lee, B., Lu, L., Wang, T., Kim, T., Lee, W.: From zygote to morula: fortifying weakened ASLR on Android. In: Proceedings of the 2014 IEEE Symposium on Security and Privacy, Series SP ’14, pp. 424–439. IEEE Computer Society, Washington (2014). https://doi.org/10.1109/SP.2014.34Miller, D.: Security measures in OpenSSH (2007). http://www.openbsd.org/papers/openssh-measures-asiabsdcon2007-slides.pdf . Accessed 18 Jan 2019Molnar, I.: Exec shield, new Linux security feature (2003). https://lwn.net/Articles/31032/ . Accessed 18 Jan 2019Wagle, P., Cowan, C.: StackGuard: simple stack smash protection for GCC. In: Proceedings of the GCC Developers Summit, pp. 243–256 (2003)Etoh, H.: GCC extension for protecting applications from stack-smashing attacks (ProPolice) (2003). http://www.trl.ibm.com/projects/security/ssp/ . Accessed 18 Jan 2019Erb, C., Collins, M., Greathouse, J. L.: Dynamic buffer overflow detection for GPGPUs. In: IEEE/ACM International Symposium on Code Generation and Optimization (CGO), pp. 61–73 IEEE (2017)Molnar, I.: Stackprotector updates for v3.14 (2014). https://lwn.net/Articles/584278/Shen, H.: Add a new option “-fstack-protector-strong” (2012). http://gcc.gnu.org/ml/gcc-patches/2012-06/msg00974.html . Accessed 18 Jan 2019Guan, X., Ji, J., Jiang, J., Zhang, S.: Stack overflow protection device, method, and related compiler and computing device, August 22 2013, uS Patent App. 13/772,858. https://www.google.com/patents/US20130219373 . Accessed 18 Jan 2019Backes, M., Bugiel, S., Derr, E.: Reliable third-party library detection in Android and its security applications. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, Series. CCS ’16, pp. 356–367. ACM, New York (2016)Greenberg, A.: SC magazine: trojanized Android apps steal authentication tokens, put accounts at risk (2014). www.scmagazine.com/trojanized-android-apps-steal-authentication-tokens-put-accounts-at-risk/article/342208/Enck, W., Octeau, D., McDaniel, P., Chaudhuri, S.: A study of android application security. In: Proceedings of the 20th USENIX Conference on Security, Series SEC’11, pp. 21–21. USENIX Association, Berkeley (2011) http://dl.acm.org/citation.cfm?id=2028067.2028088 . Accessed 18 Jan 2019Poll: How often do you reboot? (2014). http://www.androidcentral.com/poll-how-often-do-you-reboot . Accessed 18 Jan 2019Wang, H., Li, H., Li, L., Guo, Y., Xu, G.: Why are android apps removed from Google play? A large-scale empirical study. In Proceedings of the 15th International Conference on Mining Software Repositories, Series MSR ’18, pp. 231–242. ACM, New York (2018). http://doi.acm.org/10.1145/3196398.3196412Marco-Gisbert, H., Ripoll, I.: Preventing brute force attacks against stack canary protection on networking servers. In: 12th International Symposium on Network Computing and Applications, pp. 243–250 (2013)Petsios, T., Kemerlis, V.P., Polychronakis, M., Keromytis, A.D.: DynaGuard: armoring canary-based protections against brute-force attacks. In: Proceedings of the 31st Annual Computer Security Applications Conference, Series ACSAC 2015, pp. 351–360. ACM, New York (2015). http://doi.acm.org/10.1145/2818000.281803

Summarization of Spanish Talk Shows with Siamese Hierarchical Attention Networks

[EN] In this paper, we present an approach to Spanish talk shows summarization. Our approach is based on the use of Siamese Neural Networks on the transcription of the show audios. Specifically, we propose to use Hierarchical Attention Networks to select the most relevant sentences for each speaker about a given topic in the show, in order to summarize his opinion about the topic. We train these networks in a siamese way to determine whether a summary is appropriate or not. Previous evaluation of this approach on summarization task of English newspapers achieved performances similar to other state-of-the-art systems. In the absence of enough transcribed or recognized speech data to train our system for talk show summarization in Spanish, we acquire a large corpus of document-summary pairs from Spanish newspapers and we use it to train our system. We choose this newspapers domain due to its high similarity with the topics addressed in talk shows. A preliminary evaluation of our summarization system on Spanish TV programs shows the adequacy of the proposal.This work has been partially supported by the Spanish MINECO and FEDER founds under project AMIC (TIN2017-85854-C4-2-R). Work of Jose-Angel Gonzalez is financed by Universitat Politecnica de Valencia under grant PAID-01-17.González-Barba, JÁ.; Hurtado Oliver, LF.; Segarra Soriano, E.; García-Granada, F.; Sanchís Arnal, E. (2019). Summarization of Spanish Talk Shows with Siamese Hierarchical Attention Networks. Applied Sciences. 9(18):1-13. https://doi.org/10.3390/app9183836S113918Carbonell, J., & Goldstein, J. (1998). The use of MMR, diversity-based reranking for reordering documents and producing summaries. Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR ’98. doi:10.1145/290941.291025Erkan, G., & Radev, D. R. (2004). LexRank: Graph-based Lexical Centrality as Salience in Text Summarization. Journal of Artificial Intelligence Research, 22, 457-479. doi:10.1613/jair.1523Lloret, E., & Palomar, M. (2011). Text summarisation in progress: a literature review. Artificial Intelligence Review, 37(1), 1-41. doi:10.1007/s10462-011-9216-zSee, A., Liu, P. J., & Manning, C. D. (2017). Get To The Point: Summarization with Pointer-Generator Networks. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). doi:10.18653/v1/p17-1099Narayan, S., Cohen, S. B., & Lapata, M. (2018). Ranking Sentences for Extractive Summarization with Reinforcement Learning. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). doi:10.18653/v1/n18-1158González, J.-Á., Segarra, E., García-Granada, F., Sanchis, E., & Hurtado, L.-F. (2019). Siamese hierarchical attention networks for extractive summarization. Journal of Intelligent & Fuzzy Systems, 36(5), 4599-4607. doi:10.3233/jifs-179011Furui, S., Kikuchi, T., Shinnaka, Y., & Hori, C. (2004). Speech-to-Text and Speech-to-Speech Summarization of Spontaneous Speech. IEEE Transactions on Speech and Audio Processing, 12(4), 401-408. doi:10.1109/tsa.2004.828699Shih-Hung Liu, Kuan-Yu Chen, Chen, B., Hsin-Min Wang, Hsu-Chun Yen, & Wen-Lian Hsu. (2015). Combining Relevance Language Modeling and Clarity Measure for Extractive Speech Summarization. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 23(6), 957-969. doi:10.1109/taslp.2015.2414820Yang, Z., Yang, D., Dyer, C., He, X., Smola, A., & Hovy, E. (2016). Hierarchical Attention Networks for Document Classification. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. doi:10.18653/v1/n16-1174Conneau, A., Kiela, D., Schwenk, H., Barrault, L., & Bordes, A. (2017). Supervised Learning of Universal Sentence Representations from Natural Language Inference Data. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/d17-1070Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391-407. doi:10.1002/(sici)1097-4571(199009)41:63.0.co;2-

Myoelectric forearm prostheses: State of the art from a user-centered perspective

User acceptance of myoelectric forearm prostheses is currently low. Awkward control, lack of feedback, and difficult training are cited as primary reasons. Recently, researchers have focused on exploiting the new possibilities offered by advancements in prosthetic technology. Alternatively, researchers could focus on prosthesis acceptance by developing functional requirements based on activities users are likely to perform. In this article, we describe the process of determining such requirements and then the application of these requirements to evaluating the state of the art in myoelectric forearm prosthesis research. As part of a needs assessment, a workshop was organized involving clinicians (representing end users), academics, and engineers. The resulting needs included an increased number of functions, lower reaction and execution times, and intuitiveness of both control and feedback systems. Reviewing the state of the art of research in the main prosthetic subsystems (electromyographic [EMG] sensing, control, and feedback) showed that modern research prototypes only partly fulfill the requirements. We found that focus should be on validating EMG-sensing results with patients, improving simultaneous control of wrist movements and grasps, deriving optimal parameters for force and position feedback, and taking into account the psychophysical aspects of feedback, such as intensity perception and spatial acuity