Beyond Blacklists: Learning to Detect Malicious Web Sites from Suspicious URLs

Oct 04, 2013

220 likes | 348 Views

Share Presentation

Embed Code

Link

orly

Download Presentation

Beyond Blacklists: Learning to Detect Malicious Web Sites from Suspicious URLs

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Malicious Code and Intruders

Malicious Code and Intruders. Dr. Ron Rymon Efi Arazi School of Computer Science IDC, Herzliya, 2010/11. Pre-requisite: Basic Cryptography, Authentication. Overview. Malicious Code (Viruses) Intrusion Detection and Prevention Denial of Service. Malicious Code (Viruses).

870 views • 58 slides

Malicious Code

Malicious Code. CS 419: Computer Information Security Kati Reiland Wed. March 5, 2003. What I’ll Cover. Short Timeline of Malicious Code Definition of Malicious Code Closer Look at Viruses and Worms A Specific Look at the LoveBug Virus. Timeline.

585 views • 19 slides

Malicious Software

Malicious Software. Han Zhang & Ruochen Sun. Malicious Software. http://www.youtube.com/watch?v=uvEz8dNilvo&feature=channel_video_title. Backdoor or Trapdoor. secret entry point into a program allows those who know access bypassing usual security procedures

528 views • 30 slides

How can we detect viruses?

How can we detect viruses?. Identifying the etiology of a new disease. Learning objectives. Describe how viruses are isolated. Explain the theory and procedures of various virus identification methods.

312 views • 10 slides

Fighting the WebBots

Fighting the WebBots. A webbot is a program that visits web sites for all kinds of purposes. For example, Google webbots make copies of all web sites for their search engines. The challenge is to stop malicious webbots. Webbots and Spam.

297 views • 14 slides

Web Crawler & Distributed IR

Web Crawler & Distributed IR. Rong Jin. A Basic Crawler. Initialize queue with URLs of known seed pages Repeat Take URL from queue Fetch and parse page Extract URLs from page Add URLs to queue Fundamental assumption The web is well linked. Challenges.

672 views • 23 slides

Malicious Software CIS 4361

Malicious Software CIS 4361. Eng. Hector M Lugo-Cordero, MS Feb. 2012. Most Slides are From. Computer Security: Principles and Practice. Chapter 7 – Malicious Software. First Edition by William Stallings and Lawrie Brown Lecture slides by Lawrie Brown. Malicious Software.

544 views • 36 slides

Free Bookmarking Sites List

bookmarkinglistonline.comBookmarking list online is reviewed daily to bring you with updated URLs of free and high pr social bookmarking sites. Use new social networking site with our list.

231 views • 6 slides

Malicious Attacks

Malicious Attacks. Angela Ku Adeline Li Jiyoung You Selena Yuen. Intro/Background. Malicious Attacks – electronic attacks in which an attacker attempts to access, steal, or destroy a user’s data without his or her permission. Trojan. A type of virus that hides within a set of programs

226 views • 0 slides

Malicious Software

Malicious Software. High-tech section of chapter 3. Malicious Software. Application software consists of programs designed to make users more productive and/or assist with personal tasks. Growth of internet simplified the spread of malware

442 views • 17 slides

Z39.50 URLs

Z39.50 URLs. December 2000 ZIG. Chair : Kevin Gamiel.

413 views • 22 slides

Suspicious

Suspicious. By: Krysten Collins. “Be suspicious of anything that works perfectly- it’s probably because two errors are canceling each other out” - Dave Bartley. Su spi ci ous Definition- Distrustful Synonym- Doubtful, Cautious Antonym- Innocent, Trustworthy

205 views • 2 slides

Malicious Attacks

Malicious Attacks. By: Albert, Alex, Andon , Ben, Robert. Examples of Malicious Attacks. Malware Infectious Concealment Spyware Phishing Spam Active Hacking. How Computers Become Infected.

301 views • 10 slides

Suspicious and Anomalous Behavior

A Framework for Detection of Anomalous and Suspicious Behavior from Agent’s Spatio -Temporal Traces. Boštjan Kaluža Depratment of Intelligent Systems, Jožef Stefan Institute December 12, 2012, Ljubljana, Slovenia. Suspicious and Anomalous Behavior. -. Suspicious behavior detection

336 views • 15 slides

Malicious Attacks

Alex Heinricher Kun H. Lee Adrian Trejo Angela DiTaranto. Malicious Attacks. What Are Malicious Attacks. Any attempt to gain information through social or software engineering Phishing Malware Viruses Trojan Horses Worms. Background: Then. First Virus: Creeper, 1971

316 views • 9 slides

Learning to Detect A Salient Object

Learning to Detect A Salient Object. Reporter: 鄭綱 (3/2) . Outline. Introduction CRF Formulation of Static Salient Object Strong Contrast Center-Surround Histogram Color Spatial-Distribution Learning & Inference for the Model Formulation of Dynamic Salient Object Results Conclusion

522 views • 30 slides

An ANN approach to identify malicious URLs

An ANN approach to identify malicious URLs. ECE 539 – Final Project Jayneel Gandhi. Motivation. Prevent users from visiting malicious webpage Lot of effort into reducing internet crimes Try to learn which URL is malicious from different sources

230 views • 8 slides

Malicious Hubs

Malicious Hubs. Sarah Jaffer. Malicious Hubs. PCs monitored by users Varying levels of security Autonomous Systems (AS) monitored by sysadmin Same security within a system Which is more valuable in a botnet?. Malicious Hubs. Some AS have poor security

230 views • 7 slides

Crawling

Crawling. Slides adapted from Information Retrieval and Web Search, Stanford University, Christopher Manning and Prabhakar Raghavan. Sec. 20.2. Begin with known “seed” URLs Fetch and parse them Extract URLs they point to Place the extracted URLs on a queue

362 views • 21 slides

URLs in CCS Catalog Records

URLs in CCS Catalog Records. Dos and Don’ts December 1, 2004. The Three R’s of URL’s. Add (or retain) URLs that:. reproduce the cataloged work or the information in it relate directly to the cataloged work refer the user to additional information on the subject of the cataloged work.

609 views • 51 slides

Designing URLs for UCL

Designing URLs for UCL. Dan Jackson, Senior Web Architect. http://www.flickr.com/photos/psteichen/3915657914 /. Why URLs matter. If you start at 15.35 you will hear him talk about URLs. http :// vimeo.com /53317254.

361 views • 23 slides

More Related

Beyond Blacklists: Learning to Detect Malicious Web Sites from Suspicious URLs

Beyond Blacklists: Learning to Detect Malicious Web Sites from Suspicious URLs

Presentation Transcript

Malicious Code and Intruders

Malicious Code

Malicious Software

How can we detect viruses?

Fighting the WebBots

Web Crawler &amp; Distributed IR

Malicious Software CIS 4361

Free Bookmarking Sites List

Malicious Attacks

Malicious Software

Z39.50 URLs

Suspicious

Malicious Attacks

Suspicious and Anomalous Behavior

Malicious Attacks

Learning to Detect A Salient Object

An ANN approach to identify malicious URLs

Malicious Hubs

Crawling

URLs in CCS Catalog Records

Designing URLs for UCL

Web Crawler & Distributed IR