Fake name generator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

Fake name generator的問題,我們搜遍了碩博士論文和台灣出版的書籍,推薦Allain, Rhett/ Lenkov, Peter M (FRW)/ Till, Lucas (INT)寫的 The Official Macgyver Survival Manual: 155 Ways to Save the Day 可以從中找到所需的評價。

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國立成功大學 電腦與通信工程研究所 林輝堂所指導 王子夏的 應用頻譜分析與群體結構辨識於網路攻擊偵防之研究 (2016),提出Fake name generator關鍵因素是什麼,來自於網路安全、頻譜分析、分群演算法、網域生成演算法、殭屍網路、女巫攻擊。

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除了Fake name generator,大家也想知道這些:

The Official Macgyver Survival Manual: 155 Ways to Save the Day

為了解決Fake name generator的問題,作者Allain, Rhett/ Lenkov, Peter M (FRW)/ Till, Lucas (INT) 這樣論述:

155 field-tested hacks, tips, and on-the-fly solutions for the next time you're captured by Russian spies. For over 30 years, the name MacGyver has been synonymous with astonishing feats of ingenuity, from fixing a car with nothing but water and egg whites to busting out of jail using a hairpin and

a pair of repurposed handcuffs to, of course, saving the world with his favorite weapon, a simple paperclip. What you might not know is that every trick that the resourceful secret agent pulls off on CBS's hit show has been tested and fact-checked by experts, and really works . . . most of the time

. No one is saying that you should craft a DIY airplane out of trash bags and a lawnmower engine. But with this book, you could. The first official how-to guide to the MacGyver universe, this book is packed with how-to drawings and step-by-step descriptions of the hacks that made this character the

world's most resourceful secret agent. Based on the hit new series, with shout-outs to the classic show that started it all. Each section introduced by Dr. Rhett Alain, the show's resident physicist, who helps ensure the show's science is based in . . . something resembling reality. Full-color ph

otos illustrate Angus MacGyver in his element (which is to say, danger ), and illustrated how-to drawings show exactly how it was done. The best hacks to try at home for yourself are highlighted (as well the ones you really, really should never do without a team of physicists and a first aid kit han

dy). So grab a paper clip, a pen knife, and some duct tape and prepare to save the day Contents include: Breaking In + Out: Dozens of hacks for when you're in a tight spot--or want to get closer to one, including: Break Out of Handcuffs Using a Hairpin Using a Toothbrush to Pick a Lock Detect an

Intruder Make a Battering Ram Cut Through Steel Escape from Zip Ties or Duct Tape Use Vacuums to Scale a Wall, Spidey-Style Tools + Technology: Making the most of what you've got on hand, in the most unexpected of ways, including: Make a Stove from a Soup Can Tie Essential Knots Light a Fire with a

Battery The Science of Stun Guns Build a Drone Fake a Crime Scene Make Buckets of Fake Blood Could I Do That? Rig a Spy Microphone Lift a Fingerprint Traps + Getaways: Lure the bad guys in, then get out of Dodge Catch Bad Guy in a Net Tie Them Up with a Tarp Stop a Car with a Piece of Paper Boob

ytrap a Manhole Burn Your Bridges Steal a Car Set a Tripwire Fly Away with Balloons Fake a Parachute Repairs + Rescues: When the chips are down and the stakes are big, it's time for the really wild stuff, including: Make a Flour Bomb Patch a Gun Shot Wound with a Credit Card Put Out Fire with Soun

d Waves Transport Explosives Safely Make a Generator from Your Mope

應用頻譜分析與群體結構辨識於網路攻擊偵防之研究

為了解決Fake name generator的問題,作者王子夏 這樣論述:

網際網路的便利性讓使用者忽略了其背後許多資訊安全層面的議題,對於網路服務的過度依賴讓使用者經常曝露在未經保護的網路環境中,而在眾多資安議題中,殭屍網路 (Botnet)透過網際網路進行垃圾郵件散佈、竊取隱私資料、架設釣魚網站、散播惡意程式以及分散式服務阻斷等攻擊惡意行為,儼然成為具有高度威脅性的資訊安全隱憂。然而隨著資安防護能力的提升,驅使著殭屍網路產生多種不同規避偵測的型態以提高存活率,其中網域生成演算法 (Domain Generation Algorithm, DGA) 型態之殭屍網路透過演算法產生大量的備選控制網域以混淆偵查,大幅提升殭屍網路存活機率並增加傳統防禦機制辨識上之困難度,

是目前相當主流的殭屍網路型態之一。另一方面,社群網站的興盛除了吸引一般使用者之外也引起惡意攻擊者的注意,其中女巫攻擊 (Sybil Attack) 透過佈建大量虛假帳號以癱瘓系統是目前新興的社群網路攻擊行為之一。而不論是DGA殭屍網路之連線行為或是女巫攻擊中虛假帳號與真實帳號的連結關係,如將之對應到網路拓樸上時均可發現兩者都有特殊的社群結構。因此,本研究提出一基於頻譜分析之分群演算法,針對網路群體進行分群以配合後續之偵測機制,與過往分群演算法不同之處在於,本研究提出的分群演算法不需要事先確認分群數量便可以自適應式根據群體結構產生最合適之分群結果。基於此一分群演算法,針對DGA型態殭屍網路提出一

偵防機制,此偵防機制透過觀察與分析DGA型態殭屍網路在網路流量中的行為特徵,利用受感染主機與控制中心通聯時所產生之大量失效查詢流量進行辨識。研究結果顯示本偵測機制可以佈建於真實網路環境中,並且準確偵測出已知與未知的DGA型態殭屍網路。另一方面,針對女巫攻擊,本研究提出一偵防機制,此方法透過群體結構特性進行辨識,並改善過往研究須事先知曉系統中哪些是正常節點方可進行偵測的缺點,本偵防機制無此限制即可進行有效的偵測,並且透過真實社群資料進行驗證,研究結果顯示本機制確實能夠在未知正常節點的情況下有效的偵測女巫攻擊下之假帳號。