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Prentvæn Útgáfa Af Orðasafninu Með Líku Sniði Og Fyrri Útgáfur
Tölvuorðasafn Íslenskt-enskt, enskt-íslenskt 5. útgáfa, aukin og endurbætt Gefið út sem rafrænt rit Orðanefnd Skýrslutæknifélags Íslands tók saman Reykjavík 2013 Tölvuorðasafn Rit orðanefndar Skýrslutæknifélags Íslands: 1. Skrá yfir orð og hugtök varðandi gagnavinnslu. 2. útgáfa. Skrifuð sem hand- rit. Orðanefnd Skýrslutæknifélags Íslands tók saman. Skýrslutæknifélag Íslands. [Reykjavík] 1974. 2. Tölvuorðasafn. Íslenskt-enskt, enskt-íslenskt. Orðanefnd Skýrslutæknifélags Íslands tók saman. [Ritstjóri: Sigrún Helgadóttir.] Hið íslenska bókmenntafélag. Reykjavík 1983. 3. Örfilmutækni. Íslensk-ensk orðaskrá með skýringum og ensk-íslensk orðaskrá. Orðanefnd Skýrslutæknifélags Íslands tók saman í samvinnu við nokkra áhuga- menn. Tölvumál 1985, 10. árg., 2. tbl., bls. 7–25. 4. Tölvuorðasafn. Íslenskt-enskt, enskt-íslenskt. 2. útgáfa, aukin og endurbætt. Orðanefnd Skýrslutæknifélags Íslands tók saman. Ritstjóri: Sigrún Helgadóttir. Íslensk málnefnd. Reykjavík 1986. 5. Tölvuorðasafn. Íslenskt-enskt, enskt-íslenskt. 3. útgáfa, aukin og endurbætt. Orðanefnd Skýrslutæknifélags Íslands tók saman. Ritstjóri: Stefán Briem. Íslensk málnefnd. Reykjavík 1998. 6. Íslensk táknaheiti. Orðanefnd Skýrslutæknifélags Íslands tók saman. Ritstjóri: Stefán Briem. Íslensk málnefnd. Reykjavík 2003. 7. Tölvuorðasafn. Íslenskt-enskt, enskt-íslenskt. 4. útgáfa, aukin og endurbætt. Orðanefnd Skýrslutæknifélags Íslands tók saman. Ritstjóri: Stefán Briem. Hið íslenska bókmenntafélag í samvinnu við orðanefnd Skýrslutæknifélags Íslands. Reykjavík 2005. 8. Tölvuorðasafn. 5. útgáfa, -
Syngress.Force.Emerging.Threat.Analysis.From.Mischief.To.Malicious.Oct.2006.Pdf
367_SF_Threat_FM.qxd 10/6/06 3:50 PM Page i Visit us at www.syngress.com Syngress is committed to publishing high-quality books for IT Professionals and delivering those books in media and formats that fit the demands of our cus- tomers. We are also committed to extending the utility of the book you purchase via additional materials available from our Web site. SOLUTIONS WEB SITE To register your book, visit www.syngress.com/solutions. Once registered, you can access our [email protected] Web pages. There you may find an assortment of value-added features such as free e-booklets related to the topic of this book, URLs of related Web site, FAQs from the book, corrections, and any updates from the author(s). ULTIMATE CDs Our Ultimate CD product line offers our readers budget-conscious compilations of some of our best-selling backlist titles in Adobe PDF form. These CDs are the perfect way to extend your reference library on key topics pertaining to your area of exper- tise, including Cisco Engineering, Microsoft Windows System Administration, CyberCrime Investigation, Open Source Security, and Firewall Configuration, to name a few. DOWNLOADABLE E-BOOKS For readers who can’t wait for hard copy, we offer most of our titles in download- able Adobe PDF form. These e-books are often available weeks before hard copies, and are priced affordably. SYNGRESS OUTLET Our outlet store at syngress.com features overstocked, out-of-print, or slightly hurt books at significant savings. SITE LICENSING Syngress has a well-established program for site licensing our e-books onto servers in corporations, educational institutions, and large organizations. -
A Privacy-Preserving Big Data Platform for Collaborative Spam Detection
IEEE TRANSACTIONS ON BIG DATA, VOL. , NO. , OCTOBER 2016 1 Spamdoop: A privacy-preserving Big Data platform for collaborative spam detection Abdelrahman AlMahmoud, Member, IEEE, Ernesto Damiani, Senior Member, IEEE, Hadi Otrok, Senior Member, IEEE, Yousof Al-Hammadi, Member, IEEE Abstract—Spam has become the platform of choice used by cyber-criminals to spread malicious payloads such as viruses and trojans. In this paper, we consider the problem of early detection of spam campaigns. Collaborative spam detection techniques can deal with large scale e-mail data contributed by multiple sources; however, they have the well-known problem of requiring disclosure of e-mail content. Distance-preserving hashes are one of the common solutions used for preserving the privacy of e-mail content while enabling message classification for spam detection. However, distance-preserving hashes are not scalable, thus making large-scale collaborative solutions difficult to implement. As a solution, we propose Spamdoop, a Big Data privacy-preserving collaborative spam detection platform built on top of a standard Map Reduce facility. Spamdoop uses a highly parallel encoding technique that enables the detection of spam campaigns in competitive times. We evaluate our system’s performance using a huge synthetic spam base and show that our technique performs favorably against the creation and delivery overhead of current spam generation tools. Index Terms—Spam Campaign, Privacy-Preserving Analysis, Map Reduce. F 1 INTRODUCTION HE word spam was originally used to describe ring it. The effort led to the gradual decline of spamming T unsolicited e-mails sent in bulk. It is hard to define activities which lead many to believe that spam was no lon- the term spam more accurately. -
E-Mail Security and Spam
Internet Technology & Web Engineering Email Security & Spam Dr.-Ing. Matthäus Wander Universität Duisburg-Essen User Authentication ∙ IMAP and POP have authentication built-in ∘ Original SMTP provided no authentication ∘ Anyone could send emails via any MTA ∙ Idea: Check sender From address ∘ Insecure, can be spoofed ∙ Authenticate by source IP address range ∘ Works for closed groups, not for public email service provider ∙ SMTP after POP (or POP before SMTP) ∘ Authenticate via POP, save client IP address ∘ Allow SMTP afterwards if IP address matches Verteilte Systeme Matthäus Wander 2 Universität Duisburg-Essen SMTP Authentication ∙ SMTP AUTH protocol extension ∘ Requires Extended SMTP ∙ Plaintext login ∘ Base64-encoded (for compatibility, not security) ∘ Secure only if SMTP connection encapsulated by TLS ∙ Digest authentication (hashed password) ∘ Server sends challenge (arbitrary, unique string) ∘ Client „encrypts“ challenge with password, sends response ∘ Server checks response with known password ∘ Password hidden, but dictionary attacks on response possible Verteilte Systeme Matthäus Wander 3 Universität Duisburg-Essen PLAIN Authentication by Example S: 220-smtp.example.com ESMTP Server C: EHLO client.example.com S: 250-smtp.example.com Hello client.example.com S: 250 AUTH GSSAPI DIGEST-MD5 PLAIN C: AUTH PLAIN dGVzdAB0ZXN0ADEyMzQ= S: 235 2.7.0 Authentication successful ∙ Base64-encoded username and password ∘ base64(identity || 0x00 || identityauth || 0x00 || password) ∘ Decoded example: test, test, 1234 ∙ Base64 is not an encryption