PPT-Malware

Author : stefany-barnette | Published Date : 2015-10-12

Computer Forensics Attack Phases Computer Forensics 2013 Hacking Phases of a Targeted Attack Reconnaissance Scanning Gaining Access Expanding Access Covering Tracks

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Malware: Transcript


Computer Forensics Attack Phases Computer Forensics 2013 Hacking Phases of a Targeted Attack Reconnaissance Scanning Gaining Access Expanding Access Covering Tracks Antiforensics Reconnaissance. 2012 . IEEE/IPSJ 12. th. . International . Symposium on Applications and the . Internet. 102062596 . 陳盈妤. 1. /10. Outline. Introduction of proposed method. Previous works by catching random behavior. Sophisticated Criminals or . Babytown. Frolics?. Ryan Merritt. Josh Grunzweig. Who We Are. Josh Grunzweig. Security Researcher. Malware Reverser. Dabbles in Ruby. Homebrewer. Ryan Merritt. Security Researcher. Analysis. Part 4. Veronica Kovah. vkovah.ost. at . gmail. See notes for citation. 1. http://. opensecuritytraining.info. /. MalwareDynamicAnalysis.html. All . materials is licensed under . a Creative . Chapter 11: Malware Behavior. Chapter 12: Covert Malware Launching. Chapter 13: Data Encoding. Chapter 14: Malware-focused Network Signatures. Chapter 11: Malware . Behavior. Common functionality. Downloaders. A Look at Cuckoo Sandbox. Introduction. What is Malware?. (. mãl'wâr. ') - . Malicious . computer software that interferes with normal computer . functions. What is Automated Malware Analysis?. Taking what has been done by highly skilled professionals in extremely time consuming tasks and making it, quick, easy and repeatable. Automated Malware Analysis is being touted as the “Next Generation Anti-Virus” solution.. with . DroidRide. : And How Not To. Min Huang, Kai Bu, . Hanlin. Wang, . Kaiwen. Zhu. Zhejiang University. CyberC. 2016. Reviving Android Malware. with . DroidRide. : And How Not To. ?. Reviving Android Malware. CS 598: Network Security. Michael Rogers & Leena Winterrowd. March 26, 2013. Types of Malware. Image courtesy of prensa.pandasecurity.com. Types of Malware. Viruses 16,82%. Trojan horses. 69.99%. Newbies. A guide for those of you who want to break into the fun world of malware.. What We’re Going To Cover. Basic x86/64 ASM. Tools of the trade. Setting up an environment. Intro to the Debugger . Spam:. Spam is unsolicited or undesired electronic junk mail. Characteristics of spam are:. Mass . mailing to large number of recipients. Usually a commercial advertisement. Annoying but usually harmless unless coupled with a fraud based phishing scam . Outline. Introduction. Types . of Malware. Malware examples. How . Malware Spreads. Prevention. AndroRAT. Hands-on Lab. Introduction. Mobile Security has become a fast growing issue. Nearly 100,000 new malicious programs for mobile devices were detected in 2013 (Kaspersky Lab). Nael Abu-Ghazaleh. Joint work with Khaled . Khasawneh. , Dmitry . Ponomarev. and Lei Yu. Malware is Everywhere!. Malware is Everywhere!. Over 250,000 malware registered every day! . Hardware Malware Detectors (HMDs). Grace. M, Zhou. Y, . Shilong. . Z, Jiang. . X. RiskRanker. analyses the paths within an android application. Potentially malicious security risks are flagged for investigation. Summary. This application showcases how reverse engineering. Chien-Chung Shen. cshen. @udel.edu. Malware. NIST . defines malware as:. “. a program that is inserted into a system, . usually covertly. , . with the . intent of compromising the confidentiality, integrity, . A. ttacks. Vaibhav . Rastogi. , . Yan Chen. , and . Xuxian. Jiang. 1. Lab for Internet and Security Technology, Northwestern University. †. North Carolina State University. Android Dominance. Smartphone sales already exceed PC sales.

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