Acrobat JavaScript的問題,透過圖書和論文來找解法和答案更準確安心。 我們找到下列懶人包和總整理

Acrobat JavaScript的問題,我們搜遍了碩博士論文和台灣出版的書籍,推薦Harder, Jennifer寫的 Enhancing Adobe Acrobat DC Forms With Javascript 和Sahlin, Doug的 How to Do Everything Adobe Acrobat X都 可以從中找到所需的評價。

另外網站How to Execute Code in the Acrobat JavaScript Console on a ...也說明:Acrobat's JavaScript is a great tool to extend the application, or to automate recurring tasks. There are several ways a JavaScript can be ...

這兩本書分別來自 和所出版 。

國立交通大學 資訊管理研究所 古政元所指導 楊秉叡的 一個基於模糊雜湊的惡意PDF偵測方法 (2019),提出Acrobat JavaScript關鍵因素是什麼,來自於逆向擬態攻擊、惡意可攜式文件格式、模糊雜湊。

而第二篇論文臺北市立大學 心理與諮商學系 危芷芬所指導 郭怡秀的 不同曖昧關係類型的未來關係走向:以嫉妒為中介變項 (2017),提出因為有 曖昧關係、嫉妒、嫉妒喚起情境、曖昧關係未來關係走向的重點而找出了 Acrobat JavaScript的解答。

最後網站禁用Acrobat Javascript 避开“零日攻击” - 51CTO則補充:Adobe Acrobat Reader是全球最流行办公软件之一,此次漏洞涉及Acrobat Reader的几乎所有版本,因此影响颇大。该漏洞可以使得恶意攻击通过PDF文件进行蔓延, ...

接下來讓我們看這些論文和書籍都說些什麼吧:

除了Acrobat JavaScript,大家也想知道這些:

Enhancing Adobe Acrobat DC Forms With Javascript

為了解決Acrobat JavaScript的問題,作者Harder, Jennifer 這樣論述:

Take your PDF forms to the next level. In this book, you'll learn various ways to further improve your PDF Forms using simple JavaScript coding. You'll also discover how a few lines of code can speed up your workflow when working with multiple PDFs in Action Wizard.Enhancing Adobe Acrobat DC Forms w

ith JavaScript covers up-to-date, real working examples that you can easily download, practice with, and edit to suit your own projects. Using screenshots from Adobe Acrobat DC, users or previous versions will also be able to utilize these techniques. This book also shows workarounds and solutions t

o various form issues you might encounter. Feel empowered by it and improve your PDF documents JavaScript has been a part of Adobe Acrobat for many versions. However, few people use its features and focus mainly on using the basic form properties, never delving deeper into Acrobat's full capabilitie

s. While information on the web can be helpful, if you don't know enough about how to use JavaScript in Acrobat you will be left with poor results. JavaScript can be difficult to learn, but it does not need to be scary. This book explains it in simple steps at a beginner to intermediate level so you

can take full advantage of Acrobat's capabilities in your own projects.What You'll LearnCreate calculations, rating forms, and QR code stamps using the form elementsExplore simplified field notation and basic JavaScript for AcrobatWork with buttons that can be used for navigationUtilize complex for

ms that include drop down and list boxes in combination with other form fieldsWork with Action Wizard and JavaScriptImprove form navigation and printing of formsAdd various types of alerts and custom validations to improve client-entered-dataWho This Book Is ForAnyone who needs to create forms for c

lients or websites: students, lawyers, accountants, and human resource personnel. ​Jennifer Harder has worked in the graphic design industry for over 10 years. She has a degree in Graphic Communications and is currently teaching Acrobat, InDesign, and Dreamweaver courses at Langara College. As a f

reelancer, Jennifer frequently works with Adobe PDFs and checks them before they go to print or are uploaded to the web. She enjoys talking about Adobe Software and her interests include: writing, illustration, and working on her websites.

一個基於模糊雜湊的惡意PDF偵測方法

為了解決Acrobat JavaScript的問題,作者楊秉叡 這樣論述:

從2020年,根據知名的惡意樣本資料庫VirusTotal統計,每周蒐集到的可攜式文件格式(Portable Document Format,以下簡稱PDF)樣本的數量至少有大約一百萬個。原因不只是因為它是目前最常用的檔案格式,還有其寬鬆又彈性的檔案結構,因此常被攻擊者作為惡意樣本的載體。一般常見的惡意PDF樣本可能會嵌入Javascript指令來利用已知的漏洞,或是從駭客的伺服器下載惡意樣本。因此當受害者點開含有惡意內容的PDF時,嵌入在裡面的惡意指令就會暗中地在受害者電腦中執行惡意的行為。有許多相關研究發現這類的PDF惡意樣本其結構上會和良性的有所差異,因此有許多利用機器學習來訓練判別P

DF檔案結構的模型的方法開始被提出,其判別惡意PDF樣本的成效顯卓。直到近年,駭客開始利用像是對抗式機器學習的模型來找出機器學型模型偵測的弱點,進而產生出能混淆模型的樣本,像是侵入式攻擊(Evasion Attack)。或是在一個含有大量良性內容的PDF中嵌入像是可攜式執行檔(Portable Executable)或是另一個惡意PDF的方式,試圖欺騙這些基於機器學習的偵測模型,這種攻擊方式被稱為逆向擬態攻擊(Reverse MimicryAttack)。本研究旨在探討一種不只能夠偵測一般的惡意樣本,也能夠辨識出侵入式惡意樣本的模糊雜湊偵測方法,目標是希望能不容易受到上述嵌入式攻擊的影響,又能

達到和機器學習模型差不多的分類成效。我們建立一個PDF特徵擷取模組將PDF惡意樣本中共通的特徵擷取出來,再透過模糊雜湊模組計算該樣本的模糊雜湊值,並透過設計過的雜湊距離演算法將兩樣本的模糊雜湊值算出其相似度。最後利用特別挑選的數個良性樣本和惡意樣本的模糊雜湊值作為比對的基準,利用我們設計的相似度算法找到最相似的樣本來決定樣本的是否為惡意,進而達到偵測的效果。

How to Do Everything Adobe Acrobat X

為了解決Acrobat JavaScript的問題,作者Sahlin, Doug 這樣論述:

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Unlock the full potential of Adobe Acrobat X Now it's easier than ever to create interactive electronic docum

ents that retain the look and feel of the originals. How to Do Everything: Adobe Acrobat X shows you how to create, secure, optimize, and distribute PDFs. Get tips for adding multimedia features, collaborating with other users, streamlining document reviews, and collecting different file types in a

PDF Portfolio. Based on Acrobat X Pro, which includes all the features of Acrobat X Standard and more, this hands-on guide helps you maximize the capabilities of this powerful software in no time.Convert virtually any document to PDFUse Quick Tools and set Acrobat preferencesCreate PDF documents in

authoring applications, including Microsoft Office 2010Capture PDF documents from a scanner or Web pageCreate navigation devices, including bookmarks, thumbnails, and linksUse the Action Wizard and JavaScript to add interactivityReview, edit, and annotate PDF documentsAdd digital signatures and docu

ment securityOptimize PDF documents for print, CD/DVD applications, the Web, and other usesUse Acrobat onlineCreate interactive PDF formsAdd multimedia elements

不同曖昧關係類型的未來關係走向:以嫉妒為中介變項

為了解決Acrobat JavaScript的問題,作者郭怡秀 這樣論述:

  本研究旨在研究曖昧關係中純曖昧與準愛情關係對曖昧關係走向的預測,以嫉妒為中介變項進行檢核。  曖昧關係是介於友誼關係與愛情關係之間,一種「朋友以上,戀人未滿」未能言明的關係,依照個人維持曖昧關係之動機,又可細分為純曖昧與準愛情(郭怡秀、危芷芬,2012;Kuo & Wei, 2013)。前者指個人僅想維持朋友以上,戀人未滿的曖昧關係;後者則是以曖昧關係為跳板,期望與對方發展為親密關係(Kuo & Wei, 2013)。純曖昧與準愛情關係中,關係不確定性容易產生負向感受,也可能將關係轉化(Afifi & Reichert, 1996; Bevan, 2004; Dainton & Aylo

r, 2001; Knobloch, 2006; Knobloch & Solomon, 2002; Knobloch & Theiss, 2011)。Bevan(2004)指出,當個人經驗到嫉妒時,可以主動因應以降低不確定性。故研究者欲探討純曖昧與準愛情在嫉妒狀態下,是否會發展出不同的關係走向,而使兩種曖昧關係更能被區分與辨識。  研究者依照本研究之架構與假設,編製自陳式問卷包含「嫉妒情境量表」、「曖昧關係走向量表」與「基本資料」等三部分。本研究於Facebook與批踢踢實業坊(PTT)招募20歲(含)以上之成年人參與者,採取便利抽樣及滾雪球抽樣,然後邀請參與者在mysurvey網路問卷平台

填答問卷,共獲得有效問卷282份,參與者年齡平均為26.51歲,包含115位男性、165位女性以及1為其他性別者。研究者設計篩選題排除沒有維持曖昧關係經驗者,再請參與者依照近一次的曖昧經驗選擇曖昧類型,接著以JavaScript語法隨機分派受試者填寫三種嫉妒情境版本之一:性親密、受他人吸引以及過去戀情。參與者依經驗填答隨機分派嫉妒情境之嫉妒情緒後,回答曖昧關係的走向:疏離曖昧對象、繼續維持曖昧關係與欲邁入愛情關係。  本研究採用多變項變異數分析、階層迴歸以及Sobel’s t考驗進行假設檢驗,研究結果支持H1:曖昧關係類型預測曖昧關係走向;H3:曖昧關係類型預測嫉妒情緒;H4:嫉妒情境預測嫉妒

情緒;H5:嫉妒情緒預測曖昧關係走向。並部分支持H2:嫉妒情境預測曖昧關係走向;H6:嫉妒情緒為曖昧關係類型、嫉妒情境對曖昧關係走向的中介變項。