PPT-Intrusion Detection Techniques using Machine Learning

What is an IDS An I ntrusion D etection System is a wall of defense to confront the attacks of computer systems on the internet The main assumption of the IDS is that the behavior of intruders is different from legal users. 11. Intrusion Detection (. cont. ). modified from slides of . Lawrie. Brown. Security Intrusion. : A security event, or a combination of multiple security events, that constitutes a security incident in which an intruder gains, or attempts to gain, access to a system (or system resource) without having authorization to do so.. Stephen Huang. Sept. 20, 2013. News. 2. http://arstechnica.com/security/2013/09/meet-hidden-lynx-the-most-elite-hacker-crew-youve-never-heard-of/. 3. Jobs. http://www.homelandsecuritynewswire.com/dr20130809-cybersecurity-jobs-average-over-100-000-a-year. Main Advantages. H . 2. 1. Fiber Optics Technology. . -Covert design. Caused no physical alteration to present building outlook. -Full Fiber Structure thus immune to lightning strike and EMI. Intruders. Classes (from [ANDE80]:. two most publicized threats to security are malware and intruders. generally referred to as a . hacker. or . cracker. Examples of Intrusion. remote root compromise. Paper by: T. Bowen. Presented by: Tiyseer Al Homaiyd. 1. Introduction: . Intrusions: show observable events that deviate from the . norm.. Survivable system usually focus on detecting intrusions rather than preventing or containing damage. . Lecture . 4. Multilayer . Perceptrons. G53MLE | Machine Learning | Dr Guoping Qiu. 1. Limitations of Single Layer Perceptron. Only express linear decision surfaces. G53MLE | Machine Learning | Dr Guoping Qiu. &. Intrusion . Detection Systems. 1. Intruders. Three classes of intruders:. Examples of Intrusion. Performing a remote root compromise of an e-mail server. Defacing a Web server. Guessing and cracking passwords. /dr. x. Logistics. Programming homework: extra 4 days. Midterm date: Wednesday, March 1. Duration: 60 mins. Presentations: next . Rich Nelson. Reports: can you see my comments, feedback on Oaks?. L1: many reports did not even have a sentence with intro/conclusions. /dr. x. Logistics. Command Line Lab on Thursday: please bring your laptops. Keep up with the reading . – Midterm on March 2. nd. . . Computer Networks Basics: OSI stack, subnets, Basic protocols: ARP, ICMP, NAT, DHCP, DNS, TCP/IP. modified from slides of . Lawrie. Brown. Classes of Intruders – Cyber Criminals. Individuals or members of an organized crime group with a goal of financial reward. Their activities may include: . An Overview of Machine Learning Speaker: Yi-Fan Chang Adviser: Prof. J. J. Ding Date : 2011/10/21 What is machine learning ? Learning system model Training and testing Performance Algorithms Machine learning Milad Ghaznavi. 1. Outline. Introduction. Dataset. Multi Layer Perceptron. Convolutional Neural Network. Evaluation. Related Work. Conclusion. 2. Introduction. Intrusion Detection. Background. 3. Intrusion Detection. CS 469: Security Engineering. These slides are modified with permission from Bill Young (. Univ. of Texas). Coming up: Intrusion Detection. 1. Intrusion . Detection. An . intrusion detection system . Yonggang Cui. 1. , Zoe N. Gastelum. 2. , Ray Ren. 1. , Michael R. Smith. 2. , . Yuewei. Lin. 1. , Maikael A. Thomas. 2. , . Shinjae. Yoo. 1. , Warren Stern. 1. 1 . Brookhaven National Laboratory, Upton, USA.