Academic literature on the topic 'Defacement of'
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Journal articles on the topic "Defacement of"
Hoang, Xuan Dau, and Ngoc Tuong Nguyen. "Detecting Website Defacements Based on Machine Learning Techniques and Attack Signatures." Computers 8, no. 2 (May 8, 2019): 35. http://dx.doi.org/10.3390/computers8020035.
Full textBergadano, Francesco, Fabio Carretto, Fabio Cogno, and Dario Ragno. "Defacement Detection with Passive Adversaries." Algorithms 12, no. 8 (July 29, 2019): 150. http://dx.doi.org/10.3390/a12080150.
Full textYoung, Kevin. "Defacement." Callaloo 20, no. 2 (1997): 292–93. http://dx.doi.org/10.1353/cal.1997.0067.
Full textBarber, Charles. "Defacement." Yearbook of Comparative Literature 56, no. 1 (2010): 104–15. http://dx.doi.org/10.1353/cgl.2010.0011.
Full textHariyadi, Dedy. "Analisis Serangan Web Defacement pada Situs Web Pemerintah Menggunakan ELK Stack." JISKA (Jurnal Informatika Sunan Kalijaga) 4, no. 1 (November 16, 2019): 1. http://dx.doi.org/10.14421/jiska.2019.41-01.
Full textAlbalawi, Mariam, Rasha Aloufi, Norah Alamrani, Neaimh Albalawi, Amer Aljaedi, and Adel R. Alharbi. "Website Defacement Detection and Monitoring Methods: A Review." Electronics 11, no. 21 (November 1, 2022): 3573. http://dx.doi.org/10.3390/electronics11213573.
Full textAryapranata, Ariawan, Sigit Hermanto, Yogi Priya Agsena, Yuliansyah Al Rasyid, and Fachrul Husain Habibie. "Pencegahan Web Defacement." Jurnal Esensi Infokom : Jurnal Esensi Sistem Informasi dan Sistem Komputer 8, no. 1 (May 31, 2024): 10–19. http://dx.doi.org/10.55886/infokom.v8i1.816.
Full textMantzios, George. "Cold War image-myths: A crime scene ethnography of defacement and historical redress from Athens, Greece." International Journal of Cultural Studies 24, no. 5 (March 5, 2021): 749–66. http://dx.doi.org/10.1177/1367877921996371.
Full textZayid, Elrasheed, Ibrahim Isah, Nadir Farah, Yagoub Adam, and Omar Alshehri. "Exploiting the Capabilities of Classifiers to Examine a Website Defacement Data Set." International Journal of Computers and Informatics 3, no. 3 (March 31, 2024): 9–41. http://dx.doi.org/10.59992/ijci.2024.v3n3p1.
Full textDavidson, Tonya. "Mica, Pedagogy, and Defacement." Public Historian 38, no. 2 (May 1, 2016): 42–61. http://dx.doi.org/10.1525/tph.2016.38.2.42.
Full textDissertations / Theses on the topic "Defacement of"
Davanzo, Giorgio. "Machine learning in engineering applications." Doctoral thesis, Università degli studi di Trieste, 2011. http://hdl.handle.net/10077/4520.
Full textNowadays the available computing and information-storage resources grew up to a level that allows to easily collect and preserve huge amount of data. However, several organizations are still lacking the knowledge or the tools to process these data into useful informations. In this thesis work we will investigate several issues that can be solved effectively by means of machine learning techniques, ranging from web defacement detection to electricity prices forecasting, from Support Vector Machines to Genetic Programming. We will investigate a framework for web defacement detection meant to allow any organization to join the service by simply providing the URLs of the resources to be monitored along with the contact point of an administrator. Our approach is based on anomaly detection and allows monitoring the integrity of many remote web resources automatically while remaining fully decoupled from them, in particular, without requiring any prior knowledge about those resources—thus being an unsupervised system. Furthermore, we will test several machine learning algorithms normally used for anomaly detection on the web defacement detection problem. We will present a scrolling system to be used on mobile devices to provide a more natural and effective user experience on small screens. We detect device motion by analyzing the video stream generated by the camera and then we transform the motion in a scrolling of the content rendered on the screen. This way, the user experiences the device screen like a small movable window on a larger virtual view, without requiring any dedicated motion-detection hardware. As regards information retrieval, we will present an approach for information extraction for multi-page printed document; the approach is designed for scenarios in which the set of possible document classes, i.e., document sharing similar content and layout, is large and may evolve over time. Our approach is based on probability: we derived a general form for the probability that a sequence of blocks contains the searched information. A key step in the understanding of printed documents is their classification based on the nature of information they contain and their layout; we will consider both a static and a dynamic scenario, in which document classes are/are not known a priori and new classes can/can not appear at any time. Finally, we will move to the edge of machine learning: Genetic Programming. The electric power market is increasingly relying on competitive mechanisms taking the form of day-ahead auctions, in which buyers and sellers submit their bids in terms of prices and quantities for each hour of the next day. We propose a novel forecasting method based on Genetic Programming; key feature of our proposal is the handling of outliers, i.e., regions of the input space rarely seen during the learning.
Oggigiorno le risorse disponibili in termini computazionali e di archiviazione sono cresciute ad un livello tale da permettere facilmente di raccogliere e conservare enormi quantità di dati. Comunque, molte organizzazioni mancano ancora della conoscenza o degli strumenti necessari a processare tali dati in informazioni utili. In questo lavoro di tesi si investigheranno svariati problemi che possono essere efficacemente risolti attraverso strumenti di machine learning, spaziando dalla rilevazione di web defacement alla previsione dei prezzi della corrente elettrica, dalle Support Vector Machine al Genetic Programming. Si investigherà una infrastruttura per la rilevazione dei defacement studiata per permettere ad una organizzazione di sottoscrivere il servizio in modo semplice, fornendo l'URL da monitorare ed un contatto dell'amministratore. L'approccio presentato si basa sull'anomaly detection e permette di monitorare l'integrità di molte risorse web remote in modo automatico e sconnesso da esse, senza richiedere alcuna conoscenza a priori di tali risorse---ovvero, realizzando un sistema non supervisionato. A questo scopo verranno anche testati vari algoritmi di machine learning solitamente usati per la rilevazione di anomalie. Si presenterà poi un sistema di scorrimento da usare su dispositivi mobili capace di fornire una interfaccia naturale ed efficace anche su piccoli schermi. Il sistema rileva il movimento del dispositivo analizzando il flusso video generato dalla macchina fotografica integrata, trasformando lo spostamento rilevato in uno scorrimento del contenuto visualizzato sullo schermo. In questo modo, all'utente sembrerà che il proprio dispositivo sia una piccola finestra spostabile su una vista virtuale più ampia, senza che sia richiesto alcun dispositivo dedicato esclusivamente alla rilevazione dello spostamento. Verrà anche proposto un sistema per l'estrazione di informazioni da documenti stampati multi pagina; l'approccio è studiato per scenari in cui l'insieme di possibili classi di documenti (simili per contenuto ed organizzazione del testo) è ampio e può evolvere nel tempo. L'approccio si basa sulla probabilità: è stata studiata la probabilità che una sequenza di blocchi contenga l'informazione cercata. Un elemento chiave nel comprendere i documenti stampati è la loro classificazione in base alla natura delle informazioni che contengono e la loro posizione nel documento; verranno considerati sia uno scenario statico che uno dinamico, in cui il numero di classi di documenti è/non è noto a priori e nuove classi possono/non possono apparire nel tempo. Infine, ci si muoverà verso i confini del machine learning: il Genetic Programming. Il mercato della corrente elettrica si basa sempre più su aste in cui ogni giorno venditori ed acquirenti fanno delle offerte per l'acquisto di lotti di energia per il giorno successivo, con una granularità oraria della fornitura. Verrà proposto un nuovo metodo di previsione basato sul Genetic Programming; l'elemento chiave della soluzione qui presentata è la capacità di gestire i valori anomali, ovvero valori raramente osservati durante il processo di apprendimento.
XXIII Ciclo
1981
Medvet, Eric. "Techniques for large-scale automatic detection of web site defacements." Doctoral thesis, Università degli studi di Trieste, 2008. http://hdl.handle.net/10077/2579.
Full textWeb site defacement, the process of introducing unauthorized modifications to a web site, is a very common form of attack. This thesis describes the design and experimental evaluation of a framework that may constitute the basis for a defacement detection service capable of monitoring thousands of remote web sites sistematically and automatically. With this framework an organization may join the service by simply providing the URL of the resource to be monitored along with the contact point of an administrator. The monitored organization may thus take advantage of the service with just a few mouse clicks, without installing any software locally nor changing its own daily operational processes. The main proposed approach is based on anomaly detection and allows monitoring the integrity of many remote web resources automatically while remaining fully decoupled from them, in particular, without requiring any prior knowledge about those resources. During a preliminary learning phase a profile of the monitored resource is built automatically. Then, while monitoring, the remote resource is retrieved periodically and an alert is generated whenever something "unusual" shows up. The thesis discusses about the effectiveness of the approach in terms of accuracy of detection---i.e., missed detections and false alarms. The thesis also considers the problem of misclassified readings in the learning set. The effectiveness of anomaly detection approach, and hence of the proposed framework, bases on the assumption that the profile is computed starting from a learning set which is not corrupted by attacks; this assumption is often taken for granted. The influence of leaning set corruption on our framework effectiveness is assessed and a procedure aimed at discovering when a given unknown learning set is corrupted by positive readings is proposed and evaluated experimentally. An approach to automatic defacement detection based on Genetic Programming (GP), an automatic method for creating computer programs by means of artificial evolution, is proposed and evaluated experimentally. Moreover, a set of techniques that have been used in literature for designing several host-based or network-based Intrusion Detection Systems are considered and evaluated experimentally, in comparison with the proposed approach. Finally, the thesis presents the findings of a large-scale study on reaction time to web site defacement. There exist several statistics that indicate the number of incidents of this sort but there is a crucial piece of information still lacking: the typical duration of a defacement. A two months monitoring activity has been performed over more than 62000 defacements in order to figure out whether and when a reaction to the defacement is taken. It is shown that such time tends to be unacceptably long---in the order of several days---and with a long-tailed distribution.
Il web site defacement, che consiste nell'introdurre modifiche non autorizzate ad un sito web, è una forma di attacco molto comune. Questa tesi descrive il progetto, la realizzazione e la valutazione sperimentale di una sistema che può costituire la base per un servizio capace di monitorare migliaia di siti web remoti in maniera sistematica e automatica. Con questo sistema un'organizzazione può avvalersi del servizio semplicemente fornendo l'URL della risorsa da monitorare e un punto di contatto per l'amministratore. L'organizzazione monitorata può quindi avvantaggiarsi del servizio con pochi click del mouse, senza dover installare nessun software in locale e senza dover cambiare le sue attività quotidiane. Il principale approccio proposto è basato sull'anomaly detection e permette di monitorare l'integrita di molte risorse web remote automaticamente rimanendo completamente distaccato da queste e, in particolare, non richiedendo nessuna conoscenza a priori delle stesse. Durante una fase preliminare di apprendimento viene generato automaticamente un profilo della risorsa. Successivamente, durante il monitoraggio, la risorsa è controllata periodicamente ed un allarme viene generato quando qualcosa di "unusuale" si manifesta. La tesi prende in considerazione l'efficacia dell'approccio in termini di accuratezza di rilevamento---cioè, attacchi non rilevati e falsi allarmi generati. La tesi considera anche il problema dei reading mal classificati presenti nel learning set. L'efficiacia dell'approccio anomaly detection, e quindi del sistema proposto, si basa sull'ipotesi che il profilo è generato a partire da un learning set che non è corrotto dalla presenza di attacchi; questa ipotesi viene spesso data per vera. Viene quantificata l'influenza della presenza di reading corrotti sull'efficacia del sistema proposto e viene proposta e valutata sperimentalmente una procedura atta a rilevare quando un learning set ignoto è corrotto dalla presenza di reading positivi. Viene proposto e valutato sperimentalmente un approccio per la rilevazione automatica dei defacement basato sul Genetic Programming (GP), un metodo automatico per creare programmi in termini di evoluzione artificiale. Inoltre, vengono valutate sperimentalmente, in riferimento all'approccio proposto, un insieme di tecniche che sono state utilizzate per progettare Intrusion Detection Systems, sia host based che network-based. Infine, la tesi presenta i risultati di uno studio su larga scala sul tempo di reazione ai defacement. Ci sono diverse statistiche che indicano quale sia il numero di questo tipo di attacchi ma manca un'informazione molto importante: la durata tipica di un defacement. Si è effettuato un monitoraggio di oltre 62000 pagine defacciate per circa due mesi per scoprire se e quando viene presa una contromisura in seguito ad un defacement. Lo studio mostra che i tempi sono inaccettabilmente lunghi---dell'ordine di molti giorni---e con una distribuzione a coda lunga.
XX Ciclo
1979
Scott, Helen E. "Confronting nightmares : responding to iconoclasm in Western museums and art galleries." Thesis, St Andrews, 2009. http://hdl.handle.net/10023/788.
Full textCucuzzella, Jean Moore. "The Destruction of the Imagery of Saint Thomas Becket." Thesis, University of North Texas, 1998. https://digital.library.unt.edu/ark:/67531/metadc278647/.
Full textWu, Meng-jung, and 吳孟容. "WsP: A Websites Protector against Web Defacement Attacks." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/97189847976160234384.
Full text國立中央大學
資訊工程研究所
96
Along with the fast development of Internet, the web servers become the important platforms of learning, educating, entertainment, information exchange and commercial service. Because of the growing importance of the web pages, altering web pages becomes the way that the attackers destroy the image of enterprises or expresses different ideology. In addition, more and more attackers intrude the web server and do not change web pages appear on the browser, but to alter the web pages make the original web pages become fishing pages or insert the command of downloading files in the web pages. As the user browses the web pages its browser downloads the malware which the attackers set up to user’s computer automatically and the malware may carry out broken or stolen the user’s data or even capture the control of user''s computer and then user''s computer becomes the springboard of next attacks. On the basis of the reasons of the above, how to prevent web pages to be defaced fast and effectively turn into a very important thing. In this research ,we propose a protect mechanism which is based on operating system kernel against web defacement attacks-- WsP(Websites Protector). WsP is base on malbehavior approach to detect attacks, even the attackers utilizes the loophole of web servers, eg.the buffer overflow vulnerability of Apache web server, to attack web servers and then gain Super User privileges of the servers.The attacker still unable to deface web pages directly unless the attacker start new operating system but this action will possibly cause the systematic administrator’s attention. Our mechanism at the same time dose not change the existing administrator''s management, that is to say, our mechanism is totally transparent and unfeeling for user but WsP can resist the attacker’s attacks accurately.
Tsai, Yueh-chi, and 蔡岳記. "High Availability-based Self-Recovery System for Web Defacement." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/07166903681575489598.
Full text逢甲大學
資訊電機工程碩士在職專班
99
Web defacement is a kind of remote attacks that subverts web contents of a web site by exploiting system vulnerabilities. Although some researches focus their solutions on feature match of integrity of web pages, they lack of system availability and serviceability while web defacement occurs and lack of automatic self-recovery in real-time. Here we propose an approach called High-Availability Based Self-Recovery System (HASRS) to achieve the goal of fast service handoff and self-recovery. Based on the concept of “Intrusion Tolerance”, we assume the web server will always be compromised under undetected intrusion. To restrict attack time , we set time slice(ΔT)to force periodic service takeover among cluster nodes. Within ΔT , while the web server is brought offline to do self-recovery of web contents, other nodes will select one to be brought online to take over the web service. Our approach shows self-recovery and service handoff are executed automatically and periodically according to the time slice we set, regardless the web defacement occurs or not, and the the set of time slice will reduce the exposure time of web server to internet, restrict the intruders in a very short time window to deface web contents, and quickly recover defaced contents to avoid greater loss.
POYU, WANG, and 王伯宇. "The Creation and Research of “Defacement” on Interactive Media Art." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/27846956861218353147.
Full text國立臺灣藝術大學
多媒體動畫藝術學系
95
Technology brings convenience and plenty of possibilities to life. In the meantime, modern media provides arts with new materials and chances of combination among different fields. On the other hand, the development of technology gives the issue of over-urbanization. Over-urbanization makes people rush their everyday life. Therefore, it is getting more and more difficult for people to spend enough time to get below the surface of everything’s value; such as the shape of commodities, people’s dressing, package of products and so forth. It eventually forms contemporary social sense of value. The work of “Defacement” emerged from my own perception. It combines videos, interactive installations, sounds, instant transportation, and finally displays by interactive installations. This paper contains five sections of Introduction, literature review, methodology, conception and conclusions. Based on the media used and conception of creation, the literature begins with “what is new media art?” Then it leads into discussion and research of the development, attributes, concept of new media art, and the characteristic, application, connection of media. It also analyzes the topic about bodies, deconstruction, nihility and reality in new media art. Finally, it engages the results of discussion, research and analysis with the conception of creation step by step. The main conception of “Defacement” is the reconstruction of the monitored environment in today’s life. The audiences touch the sensor unconsciously. Scanners capture their appearances and actions. Then it deconstructs and re-combines the pictures with sounds and displays by interactive installations. During the audiences’ interaction with this work, they not only realize the creator’s perspective, but also find out that the appearance by sight gradually influences the tracks of life. This display of motive graphics shows the twist of people’s appearance because of contemporary social sense of value. It recalls people to deconstruct image and emphasize self consciousness.
Blas, Zachary Marshall. "Informatic Opacity: Biometric Facial Recognition and the Aesthetics and Politics of Defacement." Diss., 2014. http://hdl.handle.net/10161/9047.
Full textConfronting the rapidly increasing, worldwide reliance on biometric technologies to surveil, manage, and police human beings, my dissertation
Dissertation
Serfontein, Theodoris Erens. "Collection security in Natal libraries." Thesis, 1995. http://hdl.handle.net/10530/287.
Full textThe purpose of this study was to determine if there was a collection security problem in South African libraries, with specific reference to Natal, to determine the extent of the problem, to find out why these problems exist, and to see if the countermeasures applied by the Natal libraries were effective-Data collection was done by means of a literature study, three empirical surveys, and a sample stocktaking exercise at the four libraries included in this project, to determine their loss rate. The results show that theft/loss and mutilation of library materials are problems of considerable magnitude, locally and internationally. (In 1991 it was estimated that in the United Kingdom library materials to the value of ± £100 million were lost) - The stocktake completed at three of the four Natal libraries included in this study
Books on the topic "Defacement of"
Ostenrik, Teguh. Defacement: Teguh Ostenrik solo exhibition. Jakarta, Indonesia: Ide Global Art, 2009.
Find full textTaussig, Michael T. Defacement: Public secrecy and the labor of the negative. Stanford, Calif: Stanford University Press, 1999.
Find full textDemandt, Alexander. Vandalismus: Gewalt gegen Kultur. Berlin: Siedler, 1997.
Find full textMekhitarian, Arpag. La misère des tombes thébaines. Bruxelles: Fondation égyptologique Reine Elisabeth, 1994.
Find full textPin, Alʹbert. Mosty cherez veka. Moskva: Izd-vo "Znanie", 1985.
Find full textLouis, Réau. Histoire du vandalisme: Les monuments détruits de l'art français. Paris: R. Laffont, 1994.
Find full textKruszelnicki, Zygmunt. Toruń nie istniejący. Warszawa: Państwowe Wydawn. Nauk., 1987.
Find full textMarija, Skirmantienė, and Varnauskas Jonas, eds. Nukentėję paminklai. Vilnius: Mokslo ir enciklopedijų Leidykla, 1994.
Find full textHamel, Christopher De. Cutting up manuscripts for pleasure and profit. Charlottesville, Va: Book Arts Press, 1996.
Find full textGonzález, Antoni. Patrimoni : memòria o malson? =: Patrimonio : memoria o pesadilla? : memoria 1990-1992. Barcelona: Diputació de Barcelona, 1995.
Find full textBook chapters on the topic "Defacement of"
Reichert, Ramón. "III. Faciales Regime - Defacement." In Selfies - Selbstthematisierung in der digitalen Bildkultur, 117–78. Bielefeld, Germany: transcript Verlag, 2023. http://dx.doi.org/10.14361/9783839436653-003.
Full textBarreira, Eva, Vasco Peixoto de Freitas, and João M. P. Q. Delgado. "Biological Defacement of External Thermal Insulation Composite Systems." In Hygrothermal Behavior, Building Pathology and Durability, 23–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31158-1_2.
Full textOrlemanski, Julie. "Desire and Defacement In The Testament of Cresseid." In Reading Skin in Medieval Literature and Culture, 161–81. New York: Palgrave Macmillan US, 2013. http://dx.doi.org/10.1057/9781137084644_9.
Full textHoang, Xuan Dau. "A Website Defacement Detection Method Based on Machine Learning." In Advances in Engineering Research and Application, 116–24. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04792-4_17.
Full textReichert, Ramón. "Defacement – Faciales Regime, „Selfies“ und Gesichtsauflösung in Sozialen Medien." In De-Mediatisierung, 113–26. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-14666-5_6.
Full textMasango, Mfundo, Francois Mouton, Palesa Antony, and Bokang Mangoale. "An Approach for Detecting Web Defacement with Self-healing Capabilities." In Transactions on Computational Science XXXII, 29–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-56672-5_3.
Full textViswanathan, N., and Arun Mishra. "Dynamic Monitoring of Website Content and Alerting Defacement Using Trusted Platform Module." In Emerging Research in Computing, Information, Communication and Applications, 117–26. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0287-8_11.
Full textChiesa, Raoul, and Marco De Luca Saggese. "Data Breaches, Data Leaks, Web Defacements: Why Secure Coding Is Important." In Proceedings of 4th International Conference in Software Engineering for Defence Applications, 261–71. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27896-4_22.
Full textMedvet, Eric, and Alberto Bartoli. "On the Effects of Learning Set Corruption in Anomaly-Based Detection of Web Defacements." In Detection of Intrusions and Malware, and Vulnerability Assessment, 60–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73614-1_4.
Full text"HEGEL'S DEATH SPACE." In Defacement, 40–46. Stanford University Press, 1999. http://dx.doi.org/10.1515/9781503617131-006.
Full textConference papers on the topic "Defacement of"
Bergadano, Francesco, Fabio Carretto, Fabio Cogno, and Dario Ragno. "Defacement response via keyed learning." In 2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA). IEEE, 2017. http://dx.doi.org/10.1109/iisa.2017.8316359.
Full textMaggi, Federico, Marco Balduzzi, Ryan Flores, Lion Gu, and Vincenzo Ciancaglini. "Investigating Web Defacement Campaigns at Large." In ASIA CCS '18: ACM Asia Conference on Computer and Communications Security. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3196494.3196542.
Full textK Das, Ashish, Quynh Thi Nguyen, and Susan Thomas. "Entertaining Whilst Defacing Websites: Psychological Games for Hackers." In InSITE 2017: Informing Science + IT Education Conferences: Vietnam. Informing Science Institute, 2017. http://dx.doi.org/10.28945/3721.
Full textMasango, Mfundo, Francois Mouton, Palesa Antony, and Bokang Mangoale. "Web Defacement and Intrusion Monitoring Tool: WDIMT." In 2017 International Conference on Cyberworlds (CW). IEEE, 2017. http://dx.doi.org/10.1109/cw.2017.55.
Full textKusuma, Mandahadi, Dedy Hariyadi, and Indah Daila Sari. "Applying Visualization and Analysis Data to Investigate Cyber Crimes (Case: Web Defacement)." In The 6th International Conference on Science and Engineering. Switzerland: Trans Tech Publications Ltd, 2024. http://dx.doi.org/10.4028/p-9jbcba.
Full textHoang, Xuan Dau, and Ngoc Tuong Nguyen. "A Multi-layer Model for Website Defacement Detection." In the Tenth International Symposium. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3368926.3369730.
Full textMao, Barerem-Melgueba, and Kanlanfei Damnam Bagolibe. "A Contribution to Detect and Prevent a Website Defacement." In 2019 International Conference on Cyberworlds (CW). IEEE, 2019. http://dx.doi.org/10.1109/cw.2019.00062.
Full textHoang, Xuan Dau. "A Website Defacement Detection Method Based on Machine Learning Techniques." In the Ninth International Symposium. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3287921.3287975.
Full textKumar, Atul, and Ishu Sharma. "Performance Evaluation of Machine Learning Algorithms for Website Defacement Attack Detection." In 2023 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES). IEEE, 2023. http://dx.doi.org/10.1109/icsses58299.2023.10201194.
Full textAyunda, Shakira Putri, Nurul Qomariasih, Raden Budiarto Hadiprakoso, and Herman Kabetta. "Comparative Analysis of Deep Learning Models for Web Defacement Detection Based on Textual Context." In 2023 IEEE International Conference on Cryptography, Informatics, and Cybersecurity (ICoCICs). IEEE, 2023. http://dx.doi.org/10.1109/icocics58778.2023.10276697.
Full text