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Journal articles on the topic 'Defacement'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

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.

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Defacement attacks have long been considered one of prime threats to websites and web applications of companies, enterprises, and government organizations. Defacement attacks can bring serious consequences to owners of websites, including immediate interruption of website operations and damage of the owner reputation, which may result in huge financial losses. Many solutions have been researched and deployed for monitoring and detection of website defacement attacks, such as those based on checksum comparison, diff comparison, DOM tree analysis, and complicated algorithms. However, some solutions only work on static websites and others demand extensive computing resources. This paper proposes a hybrid defacement detection model based on the combination of the machine learning-based detection and the signature-based detection. The machine learning-based detection first constructs a detection profile using training data of both normal and defaced web pages. Then, it uses the profile to classify monitored web pages into either normal or attacked. The machine learning-based component can effectively detect defacements for both static pages and dynamic pages. On the other hand, the signature-based detection is used to boost the model’s processing performance for common types of defacements. Extensive experiments show that our model produces an overall accuracy of more than 99.26% and a false positive rate of about 0.27%. Moreover, our model is suitable for implementation of a real-time website defacement monitoring system because it does not demand extensive computing resources.

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Bergadano, 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.

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A novel approach to defacement detection is proposed in this paper, addressing explicitly the possible presence of a passive adversary. Defacement detection is an important security measure for Web Sites and Applications, aimed at avoiding unwanted modifications that would result in significant reputational damage. As in many other anomaly detection contexts, the algorithm used to identify possible defacements is obtained via an Adversarial Machine Learning process. We consider an exploratory setting, where the adversary can observe the detector’s alarm-generating behaviour, with the purpose of devising and injecting defacements that will pass undetected. It is then necessary to make to learning process unpredictable, so that the adversary will be unable to replicate it and predict the classifier’s behaviour. We achieve this goal by introducing a secret key—a key that our adversary does not know. The key will influence the learning process in a number of different ways, that are precisely defined in this paper. This includes the subset of examples and features that are actually used, the time of learning and testing, as well as the learning algorithm’s hyper-parameters. This learning methodology is successfully applied in this context, by using the system with both real and artificially modified Web sites. A year-long experimentation is also described, referred to the monitoring of the new Web Site of a major manufacturing company.

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3

Young, Kevin. "Defacement." Callaloo 20, no. 2 (1997): 292–93. http://dx.doi.org/10.1353/cal.1997.0067.

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4

Barber, Charles. "Defacement." Yearbook of Comparative Literature 56, no. 1 (2010): 104–15. http://dx.doi.org/10.1353/cgl.2010.0011.

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Hariyadi, 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.

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Web defacement merupakan serangan yang dikategorikan sebagai serangan siber yang berpotensi. Dampak dari serangan web defacement adalah proses pengembalian ke kondisi semula yang memerlukan mitigasi khusus. Pemantauan serangan web defacement dapat dilakukan dari dua sisi, yaitu sisi internal dan eksternal. Pada penelitian ini pemantauan dan analisis serangan web defacement dari sisi eksternal. Oleh sebab itu diperlukan aplikasi khusus untuk mendapatkan informasi dari OSINT Source penyedia informasi serangan web defacement yang merupakan hasil laporan dari peretas. Informasi yang didapatkan selanjutnya diolah menggunakan ELK Stack untuk mempermudah analisis dalam bentuk visualisasi pada Dashboard.Web defacement merupakan serangan yang dikategorikan sebagai serangan siber yang berpotensi. Dampak dari serangan web defacement adalah proses pengembalian ke kondisi semula yang memerlukan mitigasi khusus. Pemantauan serangan web defacement dapat dilakukan dari dua sisi, yaitu sisi internal dan eksternal. Pada penelitian ini pemantauan dan analisis serangan web defacement dari sisi eksternal. Oleh sebab itu diperlukan aplikasi khusus untuk mendapatkan informasi dari OSINT Source penyedia informasi serangan web defacement yang merupakan hasil laporan dari peretas. Informasi yang didapatkan selanjutnya diolah menggunakan ELK Stack untuk mempermudah analisis dalam bentuk visualisasi pada Dashboard.

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Albalawi, 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.

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Web attacks and web defacement attacks are issues in the web security world. Recently, website defacement attacks have become the main security threats for many organizations and governments that provide web-based services. Website defacement attacks can cause huge financial and data losses that badly affect the users and website owners and can lead to political and economic problems. Several detection techniques and tools are used to detect and monitor website defacement attacks. However, some of the techniques can work on static web pages, dynamic web pages, or both, but need to focus on false alarms. Many techniques can detect web defacement. Some are based on available online tools and some on comparing and classification techniques; the evaluation criteria are based on detection accuracies with 100% standards and false alarms that cannot reach 1.5% (and never 2%); this paper presents a literature review of the previous works related to website defacement, comparing the works based on the accuracy results, the techniques used, as well as the most efficient techniques.

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Aryapranata, 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.

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Meningkatnya penggunaan internet memiliki risiko semakin masifnya ancaman peretasan. Badan Siber dan Sandi Negara (BSSN) mencatat hingga April 2022, serangan siber di Indonesia mencapai angka 100 juta kasus. Web defacement selalu masuk ke dalam tiga teratas insiden yang masuk dalam layanan BSSN, Web Defacement adalah tindakan merusak dan mengubah tampilan website, dan dapat merusak reputasi bisnis serta mengancam kepercayaan pengunjung. Metode penelitian tindakan (action Research) digunakan untuk langkah-langkah penerapan pencegahan web defacement yang menjadi bagian integral dari strategi keamanan website.

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8

Mantzios, 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.

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This article develops an experimental ethnographic investigation into defacement as a popular modality of historical redress. It takes as its point of departure artistic remediations of archival materials pertaining to the commission, transport, and defacement of the statue of Harry S. Truman in Athens, Greece. At the forefront of the analysis is a consideration of such artistic remediations as extensions of the acts of defacement they (re)present. A political aesthetics of defacement is then elaborated through an experimental ethnography of Cold War historical redress centered around a crime scene investigation into the whereabouts and status of Harry S. Truman in present-day Athens. The experiment involves shifting the terms of historical redress from a focus on the statue of Harry S. Truman as a historiographical object of analytical study to the phantasmagoric modes of its ongoing defacement and (re)presentations in and from post-war Greece.

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Zayid, 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.

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Website defacement is the illegal electronic act of changing a website. In this paper, the capabilities of robust machine learning classifiers are exploited to select the best input feature set for evaluation of a website’s defacement risk. A defacement mining data set was obtained from Zone-H, a private organization, and a sample consisting of 93,644 data points was pre-processed and used for modelling purposes. Using multi-dimensional features as input, enormous modelling computations were carried out to determine the optimal outputs, in terms of performance. Reason and hackmode presented the highest contributions for the evaluation of website defacement, and were thus chosen as outputs. Various machine learning models were examined, and decision tree (DT), k-nearest neighbours (k-NN), and random forest (RF) were found to be the most powerful algorithms for prediction of the target model. The input variables 'domain', 'system', 'web_server', 'redefacement', 'type', 'def_grade', and 'reason/hackmode' were tested and used to shape the final model. Using the cross-validation (CV) technique, the key performance factors of the models were calculated and reported. After calculating the average scores for the hyperparameter metrics (i.e., max-depth, min-sample-leaf, weight, max-features, and CV), both targets were evaluated, and the learning algorithms were ranked as RF > DT > k-NN. The reason and hackmode variables were thoroughly analysed, and the average score accuracies for the reason and hackmode targets were 0.85 and 0.585, respectively. The results comprise a significant development, in terms of modelling and optimizing website defacement risk. This study successfully addresses key cybersecurity concerns, particularly website defacement.

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10

Davidson, 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.

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This article examines four interactions with Canada’s National War Memorial: ongoing skateboarding, an act of public urination in 2006, the 2008 “Vigil Project,” and the 2006 placement of the Valiants Memorial. It argues that these interactions with the monument demonstrate its potential as a site at which to learn about Canada’s military past and to embody the memories of others, thereby learning from the past. These types of learning are possible because the monument operates as an assemblage of material and virtual components.

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Soetomo, Mohammad Amin, and Rio Asepta. "Risks Mitigation of Defacement Attack Vectors on Educational Institution Websites by Using OWASP and Risk IT Frameworks." ACMIT Proceedings 3, no. 1 (March 18, 2019): 14–23. http://dx.doi.org/10.33555/acmit.v3i1.22.

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According to an article published by The Hacker News in 2006 [1] 21.549 websites defaced by Turkish hacker team, Iskorpitx. It was the largest defacement in web history. Zone-h, the largest defaced website archives [2] listing 11.107.846 websites became the victims of defacement attack. So how about educational institution websites? Are they become the target of defacement attack? In point of fact, University of Maryland, North Dakota University, Butler University, Indiana University and Arkansas State University became the victims of data breach by malicious attacker, the data breach was larger than data breach attack on Sony [3]. After analysing the data filtered from Zone-h archives, we retrieved that the defaced websites belong to educational institution in ASEAN countries; Indonesia (11.615 websites), Malaysia (3.512 websites), Singapore (312 websites), Vietnam (3.294 websites), Thailand (9.860 websites), Brunei Darussalam (30 websites), Cambodia (65 websites), LAO PDR (9 websites), Myanmar (6 websites), Philippines (978 websites) have been efaced in 2015. This paper will analyse the motive, attack methods, risks, impacts and mitigations of defacement attack in educational institutions. MECEES, OWASP and Risk IT will be used as framework. Hacked educational institutions will lead to critical risks .

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12

Mondragón, Oscar, Andrés Felipe Mera Arcos, Christian Urcuqui, and Andrés Navarro Cadavid. "Security control for website defacement." Sistemas y Telemática 15, no. 41 (August 1, 2017): 45–55. http://dx.doi.org/10.18046/syt.v15i41.2442.

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Cyber-attacks to websites are increasing steadily affecting the integrity and availability of information, so the implementation of safeguards to mitigate or reduce to acceptable levels the risks generated are necessary. Computer incidents produce economic and reputational impacts to different organizations. It has identified an increase in computer attacks on different organizations where one of them, and highly reputational impact, is the “Defacement” attack, which consists of unauthorized modification or alteration to the web sites using wordpress cms , affecting the integrity of information. The result of this article proposes the development of a model for establishing a security control to perform the containment and reporting of this attack type, which currently have focused on the websites of the government entities. The development model allows online control the attack on Web sites by constant reading of certain parts of the source code making the detection and maintenance of the integrity of information.

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K Das, Ashish, Quynh Thi Nguyen, and Susan Thomas. "Entertaining Whilst Defacing Websites: Psychological Games for Hackers." Issues in Informing Science and Information Technology 14 (2017): 219–27. http://dx.doi.org/10.28945/3801.

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Aim/Purpose: This study aims to investigate various characteristics from both victims as defaced websites and defacers that linked to a risk of being defaced through a set of descriptive analysis. Background: The current figures from a spectrum of sources, both academic and non-academic reports, proved a progressive increase of website defacement attacks to numerous organisations. Methodology: This study obtains a set of data from Zone-H site, which is accessible to the public, including 99,437 defaced websites. The descriptive analysis is applied in order to understand the motives of defacers and the probability of website re-defacements through the statistical investigation. Findings: The motives for defacing websites are driven mainly due to entertaining reasons. This in turn has an implication on the type of techniques defacers attack websites.

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Marschall, Sabine. "Targeting Statues: Monument “Vandalism” as an Expression of Sociopolitical Protest in South Africa." African Studies Review 60, no. 3 (August 7, 2017): 203–19. http://dx.doi.org/10.1017/asr.2017.56.

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Abstract:Inspired by the “Rhodes Must Fall” campaign, this article examines the defacement of statues and commemorative monuments in postapartheid South Africa. The term “vandalism” is problematized and, based on observation, site visits, and media reports, various cases of statue defacement are then discussed. Local events are contextualized in relation to selected postcolonial societies in Africa and other comparative international contexts. The article argues that political discontent is not necessarily expressed in overt acts of ideologically motivated vandalism, but can manifest itself equally in acts of neglect, disrespect, silence, and disengagement.

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Lerer, Seth. "Devotion and Defacement: Reading Children's Marginalia." Representations 118, no. 1 (2012): 126–53. http://dx.doi.org/10.1525/rep.2012.118.1.126.

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The study of children's marginalia in manuscripts and printed books enables us to reassess traditional assumptions about bibliography, subjectivity, and the literary imagination in the English and American traditions. Commentaries, signatures, and scribbling defacements—together with fictional representations of young people writing in books—illustrate relationships among canonical authority, playful subversion, commodity value, and archival preservation that all contribute to (and may critique) our current fascination with book history as a discipline.

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Yusuf Raharja. "Implementasi Metode Osint untuk Mengidentifikasi Serangan Judi Online pada Website." Jurnal Informatika Polinema 10, no. 3 (May 31, 2024): 359–64. http://dx.doi.org/10.33795/jip.v10i3.4847.

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Serangan siber atau cyber-attack merupakan sebuah serangan yang dilakukan oleh suatu golongan untuk merusak, mencuri atau mengubah data dari suatu sistem komputer dengan cara memanfaatkan kerentanan sistem tersebut. Web defacement merupakan salah satu contoh dari serangan siber yang dilakukan dengan mengubah tampilan halaman dari website oleh oknum yang tidak memiliki wewenang. Serangan judi online pada website merupakan contoh dari web defacement. Judi online merupakan aktivitas taruhan yang dilakukan secara online dengan mempertaruhkan uang atau barang berharga. Serangan judi online semakin marak akibat dari perkembangan judi online yang semakin cepat. Dampak yang terjadi ketika sebuah website terkena web defacement judi online adalah situs tersebut menampilkan konten judi online. Serangan judi online sering dilakukan pada domain tingkat atas seperti .co.id, .edu, .or.id, dan .com. Penelitian ini menggunakan metode Open Source Intelligence (OSINT) dengan teknik google dork untuk mengidentifikasi serangan judi online pada website dengan domain .co.id, .edu, .or.id, dan .com. Hasil identifikasi menunjukkan bahwa sebanyak 511.000 situs web dengan domain .co.id, 61.700 situs web dengan domain .edu, 26.800 situs web dengan domain .or.id, dan 6.540.000 situs web dengan domain .com terkena serangan judi online, total 7.149.500 situs web terkena serangan judi online pada keempat domain tersebut.

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Han, Mee Lan, Byung Il Kwak, and Huy Kang Kim. "CBR-Based Decision Support Methodology for Cybercrime Investigation: Focused on the Data-Driven Website Defacement Analysis." Security and Communication Networks 2019 (December 20, 2019): 1–21. http://dx.doi.org/10.1155/2019/1901548.

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Criminal profiling is a useful technique to identify the most plausible suspects based on the evidence discovered at the crime scene. Similar to offline criminal profiling, in-depth profiling for cybercrime investigation is useful in analysing cyberattacks and for speculating on the identities of the criminals. Every cybercrime committed by the same hacker or hacking group has unique traits such as attack purpose, attack methods, and target. These unique traits are revealed in the evidence of cybercrime; in some cases, these unique traits are well hidden in the evidence such that it cannot be easily perceived. Therefore, a complete analysis of several factors concerning cybercrime can provide an investigator with concrete evidence to attribute the attacks and narrow down the scope of the criminal data and grasp the criminals in the end. We herein propose a decision support methodology based on the case-based reasoning (CBR) for cybercrime investigation. This study focuses on the massive data-driven analysis of website defacement. Our primary aim in this study is to demonstrate the practicality of the proposed methodology as a proof of concept. The assessment of website defacement was performed through the similarity measure and the clustering processing in the reasoning engine based on the CBR. Our results show that the proposed methodology that focuses on the investigation enables a better understanding and interpretation of website defacement and assists in inferring the hacker’s behavioural traits from the available evidence concerning website defacement. The results of the case studies demonstrate that our proposed methodology is beneficial for understanding the behaviour and motivation of the hacker and that our proposed data-driven analytic methodology can be utilized as a decision support system for cybercrime investigation.

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Majkut, Paul. "Media Structural Defacement and Its Philosophical Implications." Glimpse 21 (2020): 97–107. http://dx.doi.org/10.5840/glimpse20202111.

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Examples given in this paper deal with print media, but the argument applies to all media. These examples illustrate structural-linguistic principles, principles that may be extended to any medium. The approach is structuralist.The history of handwritten and printed texts in the West is an inseparable history of punctuation and lettering. Written and printed texts represent spoken language: letters are representations of segmental-phonemes (linguistically meaningful sounds); graphemic punctuation represents meaningful supra-segmental phonemes (intonation, pitch, pause, etc.).Alphabetical, graphemic representation in the West has through the ages developed many arbitrary systems of grammatic punctuation to show speech, but the semantics of speech representation remains under-developed. This is no less true of digital media as of print media. Digital print media are particularly vulnerable to ambiguity. Emoticons and emojis came about of necessity. Just as early-print punctuation was primarily invented by printers and printers’ devils, not scholars, so too emoticons are Silicon-Valley formalization of user-invented semantic punctuation. :-) becomes [smiley emoji] or [smiling alien emoji]. :-( becomes [frowning emoji] or [frowning alien emoji], and so on—and ambiguity is the hothouse of error and misreading that affects all media. We should not be surprised. It is said that a similar devil, Titivillus, caused medieval manuscript scribes to make errors in their copying.I am specifically interested in the ramifications of semantic punctuation on philosophical texts—above all, irony, though sarcasm, ridicule, double entendre, derision, mockery, satire, scorn, sneering, scoffing, gibing, taunting, acerbity, causticity, hate, trenchancy, etc., as well as positive expressions such as love, amusement, friendliness, approval, sincerity, etc. are also of semantic-punctuation representational importance. Does the failure of traditional written and printed tests to reflect, for the most part, semantic values handicap printed representational discourse? In fact, can the handicapped discussion of profound ideas be adequately represented graphemically and philosophical inquiry limited without representation of the full range of human linguistic communication?Representation of irony in print has long escaped writers and scholars. In the 17th century, John Wilkins in An Essay towards a Real Character and a Philosophical Language (1668) proposed, among other semantic punctuations, an inverted exclamation mark (¡) to indicate irony: “That is terrific work¡” for a job poorly done. “What a lovely hat you have¡” said with sarcastic irony to someone sporting a ridiculous hat. (Later, an inverted question mark was suggested for ironic statement, ¿, but confusion with Spanish inverted question marks makes it a less attractive alternative).Wilkins’ term “philosophical language” refers to language as printed representation, not speech. His argument is an early reference to what I have elsewhere argued is the failure of “bookish philosophy” that has come to typify academic philosophy, for example, the gibberish of Heidegger, Derrida, post-structuralists, post-modernists, post-humanists, numerous analytic and “linguistic” philosophers, and many others.One possible way out of these difficulties is a process of mediation, unmediation, and immediation.

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Goodyear, Anne Collins. "Digitization, Genetics, and the Defacement of Portraiture." American Art 23, no. 2 (June 2009): 28–31. http://dx.doi.org/10.1086/605708.

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Njoku, Jonathan. "Defacement of bank going concern public secrecy." International Journal of Critical Accounting 5, no. 3 (2013): 229. http://dx.doi.org/10.1504/ijca.2013.055477.

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Jain, Palak, Nikhil Kumar Singh, and Dr Deepak Singh Tomar. "Defacement of Colluding Attack Using Blowfish Algorithm." International Journal of Engineering and Technology 9, no. 3 (June 30, 2017): 2420–34. http://dx.doi.org/10.21817/ijet/2017/v9i3/1709030233.

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Urcuqui, Christian Camilo, Melisa García Peña, José Luis Osorio Quintero, and Andrés Navarro Cadavid. "Antidefacement." Sistemas y Telemática 14, no. 39 (December 1, 2016): 9–27. http://dx.doi.org/10.18046/syt.v14i39.2341.

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Internet connects around three billions of users worldwide, a number increasing every day. Thanks to this technology, people, companies and devices perform several tasks, such as information broadcasting through websites. Because of the large volumes of sensitive information and the lack of security in the websites, the number of attacks on these applications has been increasing significantly. Attacks on websites have different purposes, one of these is the introduction of unauthorized modifications (defacement). Defacement is an issue which involves impacts on both, system users and company image, thus, the researchers community has been working on solutions to reduce security risks. This paper presents an introduction to the state of the art about techniques, methodologies and solutions proposed by both, the researchers community and the computer security industry.

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Burton, Laura L. "Defacement: Indigenous Patients' Experiences in Baja Verapaz, Guatemala." Howard Journal of Communications 23, no. 2 (April 2012): 119–35. http://dx.doi.org/10.1080/10646175.2012.667723.

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Hens, H. L. S. C. "Fungal Defacement in Buildings: A Performance Related Approach." HVAC&R Research 5, no. 3 (July 1, 1999): 265–80. http://dx.doi.org/10.1080/10789669.1999.10391237.

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Kung, Ren-Yi, Nai-Hsin Pan, Charles C. N. Wang, and Pin-Chan Lee. "Application of Deep Learning and Unmanned Aerial Vehicle on Building Maintenance." Advances in Civil Engineering 2021 (April 19, 2021): 1–12. http://dx.doi.org/10.1155/2021/5598690.

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Several natural and human factors are responsible for the defacement of the external walls and tiles of buildings, and the related deterioration can be a public safety hazard. Therefore, active building maintenance and repair processes are essential for ensuring building sustainability. However, conventional inspection methods are time-, cost-, and labor-intensive processes. Therefore, herein, this study proposes a convolutional neural network (CNN) model for image-based automated detection and localization of key building defects (efflorescence, spalling, cracking, and defacement). Based on a pretrained CNN VGG-16 classifier, this model applies class activation mapping for object localization. After identifying its limitations in real-life applications, this study determined the model’s robustness and ability to accurately detect and localize defects in the external wall tiles of buildings. For real-time detection and localization, this study applied this model by using mobile devices and drones. The results show that the application of deep learning with UAV can effectively detect various kinds of external wall defects and improve the detection efficiency.

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Cho, Youngho. "Intelligent On-Off Web Defacement Attacks and Random Monitoring-Based Detection Algorithms." Electronics 8, no. 11 (November 13, 2019): 1338. http://dx.doi.org/10.3390/electronics8111338.

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Recent cyberattacks armed with various ICT (information and communication technology) techniques are becoming advanced, sophisticated and intelligent. In security research field and practice, it is a common and reasonable assumption that attackers are intelligent enough to discover security vulnerabilities of security defense mechanisms and thus avoid the defense systems’ detection and prevention activities. Web defacement attacks refer to a series of attacks that illegally modify web pages for malicious purposes, and are one of the serious ongoing cyber threats that occur globally. Detection methods against such attacks can be classified into either server-based approaches or client-based approaches, and there are pros and cons for each approach. From our extensive survey on existing client-based defense methods, we found a critical security vulnerability which can be exploited by intelligent attackers. In this paper, we report the security vulnerability in existing client-based detection methods with a fixed monitoring cycle and present novel intelligent on-off web defacement attacks exploiting such vulnerability. Next, we propose to use a random monitoring strategy as a promising countermeasure against such attacks, and design two random monitoring defense algorithms: (1) Uniform Random Monitoring Algorithm (URMA), and (2) Attack Damage-Based Random Monitoring Algorithm (ADRMA). In addition, we present extensive experiment results to validate our idea and show the detection performance of our random monitoring algorithms. According to our experiment results, our random monitoring detection algorithms can quickly detect various intelligent web defacement on-off attacks (AM1, AM2, and AM3), and thus do not allow huge attack damage in terms of the number of defaced slots when compared with an existing fixed periodic monitoring algorithm (FPMA).

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Kaulingfreks, Ruud, and René ten Bos. "On faces and defacement: the case of Kate Moss." Business Ethics: A European Review 16, no. 3 (July 2007): 302–12. http://dx.doi.org/10.1111/j.1467-8608.2007.00501.x.

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Davanzo, G., E. Medvet, and A. Bartoli. "Anomaly detection techniques for a web defacement monitoring service." Expert Systems with Applications 38, no. 10 (September 2011): 12521–30. http://dx.doi.org/10.1016/j.eswa.2011.04.038.

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Indah Septiani, Nurina, Agung Sediyono, and Abdul Rochman. "PERANCANGAN WEB DEFACEMENT MONITORING DENGAN MENGGUNAKAN METODE KOMPARASI NILAI HASH1." JIKO (Jurnal Informatika dan Komputer) 5, no. 2 (August 8, 2022): 150–55. http://dx.doi.org/10.33387/jiko.v5i2.4852.

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R, Newlin Shebiah, and Arivazhagan S. "Versatile Defacement Detection by Monitoring Video Sequences Using Deep Learning." European Journal of Engineering Research and Science 4, no. 7 (July 19, 2019): 37–41. http://dx.doi.org/10.24018/ejers.2019.4.7.1396.

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The main objective of this paper is to detect vandal and vandalism by monitoring recorded video sequences. Vandalism is one of the most commonly occurring crimes in the society that indirectly affects the economy of the country. The proposed algorithm takes in the input from the video extracted from surveillance camera which prevails in public places. Further, it is converted into frames and subtracted with the background to detect the foreground object. The background subtracted image contains both human and non-human moving objects. In order to differentiate human pixels and other moving objects in the video sequence, discriminative features are extracted using deep architecture and classified using SVM classifier. Deep features proved to be highly discriminative when compared with the handcrafted Histogram of Oriented Gradients features. By analyzing the dwell time of the person in the restricted scene and his motion pattern with time and significant change in background vandalism act is declared and the person is considered as vandal. The proposed method was evaluated on the videos collected from You Tube with the contents taken during night time, multiple vandals, car vandals etc.

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R, Newlin Shebiah, and Arivazhagan S. "Versatile Defacement Detection by Monitoring Video Sequences Using Deep Learning." European Journal of Engineering and Technology Research 4, no. 7 (July 19, 2019): 37–41. http://dx.doi.org/10.24018/ejeng.2019.4.7.1396.

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The main objective of this paper is to detect vandal and vandalism by monitoring recorded video sequences. Vandalism is one of the most commonly occurring crimes in the society that indirectly affects the economy of the country. The proposed algorithm takes in the input from the video extracted from surveillance camera which prevails in public places. Further, it is converted into frames and subtracted with the background to detect the foreground object. The background subtracted image contains both human and non-human moving objects. In order to differentiate human pixels and other moving objects in the video sequence, discriminative features are extracted using deep architecture and classified using SVM classifier. Deep features proved to be highly discriminative when compared with the handcrafted Histogram of Oriented Gradients features. By analyzing the dwell time of the person in the restricted scene and his motion pattern with time and significant change in background vandalism act is declared and the person is considered as vandal. The proposed method was evaluated on the videos collected from You Tube with the contents taken during night time, multiple vandals, car vandals etc.

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Schwyzer, Philip. "Fallen idols, broken noses: Defacement and memory after the Reformation." Memory Studies 11, no. 1 (January 2018): 21–35. http://dx.doi.org/10.1177/1750698017736835.

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The Henrician and Edwardian Reformations of the 1530s and 1540s were marked by successive waves of iconoclasm in English churches and cathedrals. Statues, screens, wall paintings, and windows were among the idols targeted. While some objects and artworks were destroyed or effaced entirely, others remained in situ, bearing the marks of iconoclastic violence. Even today, many English cathedrals harbour numerous examples of defaced images which have suffered beheading or scoring of the face and hands, but have been neither repaired nor removed. This article explores how various post-Reformation observers including Protestants, Catholics, antiquaries, and poets understood and responded to defaced images, arguing that traditionalists and reformers found a paradoxical common cause in the curation of iconoclasm.

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Brook, Scott. "Touring the Phantom Agent: Recognition, Defacement and the Vietnamese Australian War Memorial." Journal of Intercultural Studies 27, no. 1-2 (February 2006): 133–49. http://dx.doi.org/10.1080/07256860600607900.

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Ashby, Richard. "Face-off: defacement, ethics and the ‘neighbour’ in The Comedy of Errors." Textual Practice 32, no. 8 (January 20, 2017): 1255–75. http://dx.doi.org/10.1080/0950236x.2016.1275757.

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Ramos, N. M. M., E. Barreira, M. L. Simões, and J. M. P. Q. Delgado. "Probabilistic Risk Assessment Methodology of Exterior Surfaces Defacement Caused by Algae Growth." Journal of Construction Engineering and Management 140, no. 12 (December 2014): 05014012. http://dx.doi.org/10.1061/(asce)co.1943-7862.0000909.

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Collins, Katie. "“Her Ruined Head”: Defacement and Bodyminds in Jean Stafford’s Life and Work." Journal of Modern Literature 45, no. 1 (January 2021): 121–36. http://dx.doi.org/10.2979/jmodelite.45.1.08.

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Kavyashree, K., C. N. Sowmyarani, and P. Dayananda. "Transmission Control Protocol Off Path Exploits in Web." Journal of Computational and Theoretical Nanoscience 17, no. 9 (July 1, 2020): 3995–98. http://dx.doi.org/10.1166/jctn.2020.9006.

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The network community in the current scenario has faced lot of potential threats like restricted access to unauthorized network; break in through other organizations, making the system unavailable and so on. An off-path attacker can perform various attacks like Browser page read, Web phishing, website Spoofing and defacement to know the 4 tuples in Transmission Control Protocol. The attacker can also carry out Cross Site Scripting to know the sensitive information on websites. Cross Site Request Forgery which performs defective exploit on web. This helps in detecting the four tuples Sequence number, Acknowledgement number, Global IPID Counter and ports.

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Essien, D. "Economic implications of superstition and the defacement of the currency notes: Nigeria experience." African J. of Economic and Sustainable Development 3, no. 1 (2014): 65. http://dx.doi.org/10.1504/ajesd.2014.061635.

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Powell, M. A., R. A. Eaton, and J. F. Webber. "The role of micro-arthropods in the defacement of sawn lumberby sapstain and mould fungi." Canadian Journal of Forest Research 25, no. 7 (July 1, 1995): 1148–56. http://dx.doi.org/10.1139/x95-127.

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Fungal sap stain, mould, and basidiomycete defacement of boards sawn from the sapwood of freshly felled logs of Corsican pine (Pinusnigra var. maritima (Aiton) Melville) was assessed during a 14-week field trial at a sawmill in southern England. The boards were placed in nonstickered stacks to reduce moisture loss, and stacks were constructed in a nest arrangement to allow experimental untreated board samples to be positioned centrally in each stack. The experimental samples were placed in plastic tanks, and the open tank faces were left either uncovered or were covered with a fine-mesh nylon screen to prevent entry of micro-arthropods. All the experimental samples were sterilized by γ-radiation prior to the tanks being installed into the board stacks. The outer casing boards, which surrounded the experimental tanks in each stack, were dip treated with a fungicide, a broad-spectrum insecticide-acaricide, a combination of the fungicide and the insecticide-acaricide, or water, which served as a control. After 8 and 14 weeks of exposure, casing boards were inspected for fungal infestation. The experimental sample boards removed from the centre of the stacks at the 8-week inspection were also assessed for fungal infestation. Boards that were accessible to arthropods (i.e., in open tanks surrounded by non-insecticide-treated boards) suffered severe sap stain. Experimental boards protected from arthropods by a mesh screen and (or) casing timbers treated with the insecticide chemical had minimal sap stain. In contrast, colonization by moulds was not reduced when either physical or chemical barriers were in place, suggesting that mould spores were mainly transmitted by air currents. Micro-arthropods were clearly implicated as primary agents of sap-stain transmission on green sawn lumber. They may also graze the moulds and therefore limit the intensity of defacement by these fungi.

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Huang, Wenzhi. "“Defacing the Leader’s Portrait and Quotations”: An Archival Study of Four Cases." Rural China 16, no. 2 (October 7, 2019): 243–92. http://dx.doi.org/10.1163/22136746-01602004.

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During the Cultural Revolution, Mao’s portrait and quotations were everywhere in China. This modern form of cult was manifested in two ways: the cult of the Leader’s personality through the use of his likenesses and quotes by government authorities and the populace, and the defilement of the objects emblematic of the Leader by certain individuals. Based on an analysis of newly discovered archives on a number of cases involving defaced portraits, photos, and quotations of the Leader, this article reveals the micro-level mechanisms of political events, by which the “enemies” were identified and treated, and further tackles some theoretical issues concerning defacement, stigmatization and de-stigmatization, and the allegation of counter-revolutionary crimes in political campaigns.

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Breen, Colin, and John Raven. "Archaeological investigations at Kinbane Castle, County Antrim and its Scottish connections." Proceedings of the Society of Antiquaries of Scotland 144 (November 30, 2015): 311–22. http://dx.doi.org/10.9750/psas.144.311.322.

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Kinbane Castle is positioned at the base of steep cliffs on the north Antrim coast, with views northwards to Rathlin Island and Islay and eastwards to Kintyre. Recent investigations have demonstrated that this headland was fortified in the 1540s by certain MacDonalds who had arrived in Antrim from Islay. The site was built to act as a bridgehead into Ulster as this family, and its associated mercenaries, attempted to establish themselves as a major force amongst the Gaelic lordships of west Ulster. Its occupation was short-lived, since it was effectively abandoned in the 1550s following defacement by English forces and the reconfiguration of MacDonald settlement across north-east Antrim and the Southern Hebrides.

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Meskill, Lynn S. "Jonson and the Alchemical Economy of Desire: Creation, Defacement and Castration in The Alchemist." Cahiers Élisabéthains: A Journal of English Renaissance Studies 62, no. 1 (October 2002): 47–63. http://dx.doi.org/10.7227/ce.62.1.6.

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Howell, C. Jordan, George W. Burruss, David Maimon, and Shradha Sahani. "Website defacement and routine activities: considering the importance of hackers’ valuations of potential targets." Journal of Crime and Justice 42, no. 5 (October 20, 2019): 536–50. http://dx.doi.org/10.1080/0735648x.2019.1691859.

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Jennings, Margaret, and Francis P. Kilcoyne. "Defacement: Practical Theology, Politics, or Prejudice: The Case of the North Portal of Bourges." Church History 72, no. 2 (June 2003): 276–303. http://dx.doi.org/10.1017/s0009640700099856.

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The Cathedral of St. Étienne at Bourges, which Ribault justly styles “un chef d'oeuvre gothique” (a Gothic masterpiece), did not escape the Huguenot depredations of 1562. Especially vulnerable to the pikes and pry-bars of the Reformers were the choir screen in front of the main altar, the north and south doorways commemorating respectively Mary in Majesty and Christ in Majesty, and several areas of the West facade: the jamb statues (whose subjects are currently unknown), the spandrel sculptures under the dado that celebrated events of the Christian scriptures and of the book of Genesis, and the five extensively carved tympana dedicated from right to left as one faces them:

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Mitchell, Beverly Eileen. "The Struggle for Human Dignity in a Consumer-Oriented Culture." Anglican Theological Review 98, no. 1 (September 2016): 111–23. http://dx.doi.org/10.1177/000332861609800109.

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This article addresses the need to ground our discussions and advocacy to rectify economic injustice in the basic affirmation that the most vulnerable victims of injustice are above all full human beings created in the image of God and that their humanness is therefore inscribed with a dignity which we are bound to respect. There are three areas in which we need to be more attentive to the ways in which our discourse and assistance unwittingly reinforce patterns of defacement even as we seek to address economic injustice: (1) addressing our biases and negative feelings about the materially disadvantaged; (2) clarifying who the materially disadvantaged are; and (3) enlisting the aid of the impoverished in seeking the solutions to economic injustice.

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Moneva, Asier, E. Rutger Leukfeldt, Steve G. A. Van De Weijer, and Fernando Miró-Llinares. "Repeat victimization by website defacement: An empirical test of premises from an environmental criminology perspective." Computers in Human Behavior 126 (January 2022): 106984. http://dx.doi.org/10.1016/j.chb.2021.106984.

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Sclocchi, Maria Carla, Lucia Kraková, Flavia Pinzari, Piero Colaizzi, Marina Bicchieri, Nikoleta Šaková, and Domenico Pangallo. "Microbial Life and Death in a Foxing Stain: a Suggested Mechanism of Photographic Prints Defacement." Microbial Ecology 73, no. 4 (December 15, 2016): 815–26. http://dx.doi.org/10.1007/s00248-016-0913-7.

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Patta, Abd Rahman, and Suhartono Suhartono. "PENGEMBANGAN SISTEM INFORMASI ABSENSI GURU DAN SISWA BERBASIS WEB DI SMA NEGERI 1 TELLULIMPOE KABUPATEN SINJAI." Jurnal Teknologi Elekterika 1, no. 1 (July 9, 2022): 76. http://dx.doi.org/10.31963/elekterika.v1i1.1216.

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Tujuan penelitian ini adalah untuk menghasilkan rancangan sistem absensi guru dan siswa berbasis web di SMA Negeri 1 Tellulimpoe Kabupaten Sinjai. Penelitian ini merupakan jenis penelitian yang menggunakan metode Research and Development (R & D) dengan menggunakan prosedur pengembangan Prototipe dan pengujian kualitas perangkat lunak berdasar ISO 9126 dengan empat karakteristik, yakni karakteristik functionality, reliability, portability dan usability. Hasil penelitian ini adalah sebuah rancangan sistem absensi guru dan siswa berbasis web di SMA Negeri 1 Tellulimpoe Kabupaten Sinjai dengan hasil pengujian dari functionality untuk sub karakteristik accurancy and suitability menunjukkan tingkat kelayakan 100% , untuk sub karakteristik security sistem dinyatakan aman dari malware, website blacklisting, injected SPAM, defacement, dan SQLInjection. Hasil pengujian reliability sistem dinyatakan sangat baik dengan tingkat kelayakan 100%, Pengujian portability menunjukan bahwa sistem ini mendukung desktop dan OS mobile, dan pada pengujian usability menunjukan tingkat kelayakan 84.88%.

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Patta, Abd Rahman, and Suhartono Suhartono. "PENGEMBANGAN SISTEM INFORMASI ABSENSI GURU DAN SISWA BERBASIS WEB DI SMA NEGERI 1 TELLULIMPOE KABUPATEN SINJAI." Jurnal Teknologi Elekterika 14, no. 1 (May 31, 2017): 76. http://dx.doi.org/10.31963/elekterika.v14i1.1216.

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Tujuan penelitian ini adalah untuk menghasilkan rancangan sistem absensi guru dan siswa berbasis web di SMA Negeri 1 Tellulimpoe Kabupaten Sinjai. Penelitian ini merupakan jenis penelitian yang menggunakan metode Research and Development (R & D) dengan menggunakan prosedur pengembangan Prototipe dan pengujian kualitas perangkat lunak berdasar ISO 9126 dengan empat karakteristik, yakni karakteristik functionality, reliability, portability dan usability. Hasil penelitian ini adalah sebuah rancangan sistem absensi guru dan siswa berbasis web di SMA Negeri 1 Tellulimpoe Kabupaten Sinjai dengan hasil pengujian dari functionality untuk sub karakteristik accurancy and suitability menunjukkan tingkat kelayakan 100% , untuk sub karakteristik security sistem dinyatakan aman dari malware, website blacklisting, injected SPAM, defacement, dan SQLInjection. Hasil pengujian reliability sistem dinyatakan sangat baik dengan tingkat kelayakan 100%, Pengujian portability menunjukan bahwa sistem ini mendukung desktop dan OS mobile, dan pada pengujian usability menunjukan tingkat kelayakan 84.88%.

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Capps†, Donald. "Stephen Pattison , Saving Face: Defacement, Shame, Theology (Farnham and Burlington, VT: Ashgate, 2013), pp. 210. £17.99." Scottish Journal of Theology 69, no. 3 (July 26, 2016): 344–47. http://dx.doi.org/10.1017/s0036930614000660.

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