Honey Pot Research And Decision By Hanh Thi Hong Nguyen Venkata Krishna Mahesh Kumar Kondraju Kieran Andrews.

Slides:



Advertisements
Similar presentations
ETHICAL HACKING A LICENCE TO HACK
Advertisements

Loss-Sensitive Decision Rules for Intrusion Detection and Response Linda Zhao Statistics Department University of Pennsylvania Joint work with I. Lee,
New Communication Technologies in the Fight against Corruption Rebecca LI Assistant Director of Operations Independent Commission Against Corruption Hong.
Uzair Masood MASYU001.  What is a honey Pot ? “ A honey pot is an information system resource whose value lies in unauthorized or illicit use.
HONEYPOTS Mathew Benwell, Sunee Holland, Grant Pannell.
Honeypot Group 1E Zahra Kamali (KAMZY001) Pratik Doshi (DOSPY001) Tapan Dave (DAVTH001)
Honeypot Research Hung Nguyen Brendan Roberts Comp 4027 Forensic and Analytical Computing.
Firewalls Dr.P.V.Lakshmi Information Technology GIT,GITAM University
Guide to Computer Forensics and Investigations1 Network Forensics Overview Network forensics –Systematic tracking of incoming and outgoing traffic To ascertain.
2 Issues of the information age Computer _______ and mistakes –Preventing computer related waste & mistakes Computer crime –Computer as tool to commit.
Honeypot 서울과학기술대학교 Jeilyn Molina Honeypot is the software or set of computers that are intended to attract attackers, pretending to be weak.
Honey Pots: Natures Dessert or Cyber Defense Tool? Eric Richardson.
Honeypots and Honeynets Source: The HoneyNet Project Book: Know Your Enemy (2 nd ed) Presented by: Mohammad.
Security Firewall Firewall design principle. Firewall Characteristics.
Student : Wilson Hidalgo Ramirez Supervisor: Udaya Tupakula Filtering Techniques for Counteracting DDoS Attacks.
Intrusion Detection Systems and Practices
8.1 © 2007 by Prentice Hall 8 Chapter Securing Information Systems.
8.1 © 2007 by Prentice Hall 8 Chapter Securing Information Systems.
Firewalls1 Firewalls Mert Özarar Bilkent University, Turkey
Lesson 13-Intrusion Detection. Overview Define the types of Intrusion Detection Systems (IDS). Set up an IDS. Manage an IDS. Understand intrusion prevention.
Lecture 11 Intrusion Detection (cont)
Network security policy: best practices
Discovering Computers 2010
Role of Technology in Combating Crime Against Woman and Children Presented by Detective Constable Janelle Blackadar Child Exploitation Section Toronto.
6 th Annual Workshop on the Teaching Computer Forensics 6 th Annual Teaching Computer Forensics Workshop Enhancing the Experience in Network Incident Investigations.
Intrusion Detection Chapter 12.
Improving Intrusion Detection System Taminee Shinasharkey CS689 11/2/00.
What is FORENSICS? Why do we need Network Forensics?
HONEYPOT.  Introduction to Honeypot  Honeytoken  Types of Honeypots  Honeypot Implementation  Advantages and Disadvantages  Role of Honeypot in.
HoneyD (Part 2) Small Business NIDS This presentation demonstrates the ability for Small Businesses to emulate virtual operating systems and conduct.
Honeypots. Introduction A honeypot is a trap set to detect, deflect, or in some manner counteract attempts at unauthorized use of information systems.
Dr Richard Overill Department of Informatics King’s College London Cyber Sleuthing or the Art of the Digital Detective.
Introduction to Computer Ethics
COEN 252 Computer Forensics Collecting Network-based Evidence.
Honeypot and Intrusion Detection System
Principles of Computer Security: CompTIA Security + ® and Beyond, Third Edition © 2012 Principles of Computer Security: CompTIA Security+ ® and Beyond,
1 Internet Firewalls What it is all about Concurrency System Lab, EE, National Taiwan University R355.
1Of 25. 2Of 25  Definition  Advantages & Disadvantages  Types  Level of interaction  Honeyd project: A Virtual honeypot framework  Honeynet project:
HONEYPOTS PRESENTATION TEAM: TEAM: Ankur Sharma Ashish Agrawal Elly Bornstein Santak Bhadra Srinivas Natarajan.
HONEYPOT By SIDDARTHA ELETI CLEMSON UNIVERSITY. Introduction Introduced in 1990/1991 by Clifford Stoll’™s in his book “The Cuckoo’s Egg” and by Bill Cheswick’€™s.
HIPS Host-Based Intrusion Prevention System By Ali Adlavaran & Mahdi Mohamad Pour (M.A. Team) Life’s Live in Code Life.
1 Implementing Monitoring and Reporting. 2 Why Should Implement Monitoring? One of the biggest complaints we hear about firewall products from almost.
SNORT Biopsy: A Forensic Analysis on Intrusion Detection System By Asif Syed Chowdhury.
Knowing What You Missed Forensic Techniques for Investigating Network Traffic.
 It is a branch of FORENSIC SCIENCE for legal evidence found in computer  It refers to detail investigation of the computers to carry out required tasks.
Security and Assurance in IT organization Name: Mai Hoang Nguyen Class: INFO 609 Professor: T. Rohm.
Cryptography and Network Security Sixth Edition by William Stallings.
By Daniel, Amitsinh & Alfred.  Collect small data sets which are of high value  All activity is assumed to be malicious  Able to capture encrypted.
UNDER THE GUIDENCE OF: Mr.M.JAYANTHI RAO,M.Tech HOD OF IT. BY: I.ADITHYA(09511A1212) HONEYPOTS.
ONLINE COURSES - SIFS FORENSIC SCIENCE PROGRAMME - 2 Our online course instructors are working professionals handling real-life cases related to various.
Interdisciplinary MS in Information Assurance Jim Wolfe Computer Science Department Indiana University of Pennsylvania EPASEC 2006.
Internet Privacy Define PRIVACY? How important is internet privacy to you? What privacy settings do you utilize for your social media sites?
Incident Response Christian Seifert IMT st October 2007.
Using Honeypots to Improve Network Security Dr. Saleh Ibrahim Almotairi Research and Development Centre National Information Centre - Ministry of Interior.
Firewalls. Overview of Firewalls As the name implies, a firewall acts to provide secured access between two networks A firewall may be implemented as.
Open source IP Address Management Software Review
Some Great Open Source Intrusion Detection Systems (IDSs)
Security Methods and Practice CET4884
Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. 컴퓨터와 인터넷 윤리 Professor I. J. Chung.
Securing Information Systems
Research using Registries
Real-time protection for web sites and web apps against ATTACKS
Computer Data Security & Privacy
Securing Information Systems
Honeypots and Honeynets
Intrusion Detection & Prevention
Intrusion Detection Systems (IDS)
12/6/2018 Honeypot ICT Infrastructure Sashan
Friday, December 07, 2018 Honeypot ICT Infrastructure Sashan Kantonsspital Graubunden ICT Department.
Honeypots Visit for more Learning Resources 1.
Presentation transcript:

Honey Pot Research And Decision By Hanh Thi Hong Nguyen Venkata Krishna Mahesh Kumar Kondraju Kieran Andrews

This Open Book independent Model unlike Intrusion detection systems offers or provides all necessary information regarding the resources to the Intruders Kuwatly et al. (2004) This is a Platform set by the software to detect the security violations & to monitor abnormal patterns in the system audit records. Honey pot model audit trails lists out anomalous events, typical user behaviors and security incidents. And this further leads to help system security officers in investigations Kuwatly et al. (2004)

Honey pots consist of vulnerabilities, With low-interaction honey pots the risk is limited when comparing with the high-interaction ones because low interaction honey pots do not provide a real environment, real operating system, or real services for attackers to use Spitzner (2004). However, attackers can ignore them and only focus on the real systems while administrators think that these honeypots will be attractive target and will give warning of attacks. Attackers can attack production servers while they try to avoid honey pots Scottberg et al. (2002). With high-interaction honeypots, attackers are provided real operating systems and application to interact. The attackers can control the honeypots and use them to attack production systems Spitzner (2004). If an attackers use honeypots to attack another outside system, the honeypots’ operator may be responsible to his or her damage Mokube & Adams (2007).

The main aim of Honey pots is to detect intrusions to prompt evasive measures, And further aim is to supply evidence in criminal and civil legal proceedings Krone (2005). Two determinants weight and admissibility are legally accepted in the form of evidence for the prosecution Krone (2005). The problems which courts are dealing are the differences between Scientific evidence & legal proofs Krone (2005). For successful evaluation of honey pots sources as legal proofs it needs to follow few ethics, which are recommended such as preservation of evidence, continuity of evidence and transparency in Honey pot forensics Krone (2005). Example: Honey pot is being reviewed as a cooperative preventive approach by police from Australia, Canada, UK and US. Australian Institute of criminology released an issue on International Police Operations Against Online Child Pornography. This operation focuses on police maintaining a ‘honey pot’ web site that presents itself as offering explicit child pornographic content. As browsers click through screens warning of the explicit nature of the content, they come to a screen that announces that their attempt to obtain online child pornography has been tracked and will be reported to local police Krone (2005).

Advantages: Data value: honey pots collects very little data, but what they do collect is normally of high value. Honey pots can give you the precise information you need in a quick and easy to understand format. This makes analysis much easier and reaction time much quicker Spitzner (2002). Resources: Honey pots avoid exhaustion resources. honeypots only catch activities directed to them and so the system is not overwhelmed by the traffic Spitzner (2002) Simplicity: simplicity the biggest single advantage of honey pots. There are no fancy algorithms to develop, no signature databases to maintain, simpler the concept the more reliable it is Spitzner (2002). Disadvantages: Narrow field View: Honeypots deals with the activities which are directed towards it, but unaware of the happenings or activities directed to other systems sharing the same network Spitzner (2002). Fingerprinting: Fingerprinting is when an attacker can identify the true identity of a Honey pot. Honey pots has a typical behaviour of misspelling the commands, this misspelling becomes a fingerprint for the honey pot Spitzner (2002).

The software which we recommended is honeyd, an opensource honeypot software. It is low-interactive and productive honeypot. This honeypot software has less functionality when compared with high- interaction & research honeypots, it is easy to deploy and maintain Mokube & Adams (2007). Low-interaction is less risky than high-interaction Mokube & Adams (2007). Honeyd has more features and is more flexible than other honeypots Grimes (2005). Honeyd allows us to choose the level of interaction and at the same time allows us to modify its services accordingly Spitzner (2002). An interesting ability of Honeyd is that it can monitor a large number of IP addresses at the same time. The IP addresses monitored by Honeyd are unused addresses Spitzner (2002).

References: 1) Spitzner, L 2004, ‘Problems and Challenges with Honeypots’, SecurityFocus, viewed 21 March, 2009, 2)Scottberg, B, Yurcik, W, Doss, D 2002, ’Internet Honeypots: Protection or Entrapment’, International Symposium on Technology and Society, pp )Mokube, I, Adams, M 2007, ‘Honeypots: Concepts, Approaches, and Challenges’, ACM Southeast Regional Conference, pp )Grimes, RA 2005, Honeypots for Windows, Springer Science & Business Media, Berkeley, CA. 5)Spitzner, L 2002, Honeypots: Tracking Hackers, Addison Wesley. 6)Kuwatly, I, Sraj, M, Al Masri, Z, Artail, H 2004, ‘A Dynamic Honeypot Design for Intrusion Detection’, International Conference on Pervasive Services, pp ) Krone, T 2005, ‘International Police Operations Against Online Child Pornography, Trends and Issues in crime and criminal justice ‘, Australian Institute of Criminology, viewed 23 March, 2009,