HONEYPOT.  Introduction to Honeypot  Honeytoken  Types of Honeypots  Honeypot Implementation  Advantages and Disadvantages  Role of Honeypot in.

Slides:



Advertisements
Similar presentations
Honeynet Introduction Tang Chin Hooi APAN Secretariat.
Advertisements

Honey Pot Research And Decision By Hanh Thi Hong Nguyen Venkata Krishna Mahesh Kumar Kondraju Kieran Andrews.
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)
1 Chapter 7 Intrusion Detection. 2 Objectives In this chapter, you will: Understand intrusion detection benefits and problems Learn about network intrusion.
Honeypots Presented by Javier Garcia April 21, 2010.
Honeypot 서울과학기술대학교 Jeilyn Molina Honeypot is the software or set of computers that are intended to attract attackers, pretending to be weak.
Honeypots and Network Security Research by: Christopher MacLellan Project Mentor: Jim Ward EPSCoR and Honors Program.
Honey Pots: Natures Dessert or Cyber Defense Tool? Eric Richardson.
Aktueller Status How Hackers Cover Their Tracks ECE 4112 May 1st, 2007 Group 1 Chris Garyet Christopher Smith Introduction Lab Content Conclusions Questions.
Presented by Stanley Chand & Damien Prescod
Honeypots and Honeynets Source: The HoneyNet Project Book: Know Your Enemy (2 nd ed) Presented by: Mohammad.
Honeypots Margaret Asami. What are honeypots ? an intrusion detection mechanism entices intruders to attack and eventually take over the system, while.
8.1 © 2007 by Prentice Hall 8 Chapter Securing Information Systems.
8.1 © 2007 by Prentice Hall 8 Chapter Securing Information Systems.
Intrusion Prevention System DYNAMIC HONEYNET by Rosenfeld Asaf advisor Uritzky Max.
Lesson 13-Intrusion Detection. Overview Define the types of Intrusion Detection Systems (IDS). Set up an IDS. Manage an IDS. Understand intrusion prevention.
John Felber.  Sources  What is an Intrusion Detection System  Types of Intrusion Detection Systems  How an IDS Works  Detection Methods  Issues.
Network Infrastructure Security. LAN Security Local area networks facilitate the storage and retrieval of programs and data used by a group of people.
Lecture 11 Intrusion Detection (cont)
© 2012 Cisco and/or its affiliates. All rights reserved. 1 CCNA Security 1.1 Instructional Resource Chapter 5 – Implementing Intrusion Prevention.
Introduction to Honeypot, Botnet, and Security Measurement
SEC835 Database and Web application security Information Security Architecture.
Why do we need Firewalls? Internet connectivity is a must for most people and organizations  especially for me But a convenient Internet connectivity.
IIT Indore © Neminah Hubballi
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.
Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Business Plug-In B6 Information Security.
Honeypot and Intrusion Detection System
Principles of Computer Security: CompTIA Security + ® and Beyond, Third Edition © 2012 Principles of Computer Security: CompTIA Security+ ® and Beyond,
Honeypots. Your Speaker Lance Spitzner –Senior Security Architect, Sun Microsystems –Founder of the Honeynet Project –Author of Honeypots: Tracking Hackers.
Honeypots and Honeynets A New Response to Cybercrime Analysis NAAG Seattle 04/14/03.
Honeypots “The more you know about the enemy, the better you can protect about yourself” Rohan Rajeevan Srikanth Vanama Rakesh Akkera.
A Virtual Honeypot Framework Author: Niels Provos Published in: CITI Report 03-1 Presenter: Tao Li.
23-aug-05Intrusion detection system1. 23-aug-05Intrusion detection system2 Overview of intrusion detection system What is intrusion? What is intrusion.
Honeynets Detecting Insider Threats Kirby Kuehl
Introduction 1. Introduction Goal of this Presentation: To give a better understanding of the overview of our project. Such as: Researches Researches Project.
KFSensor Vs Honeyd Honeypot System Sunil Gurung
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.
1 © 2001, Cisco Systems, Inc. All rights reserved. Cisco Info Center for Security Monitoring.
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.
John Carpenter & lecture & Information Security 2008 Lecture 1: Subject Introduction and Security Fundamentals.
A VIRTUAL HONEYPOT FRAMEWORK Author : Niels Provos Publication: Usenix Security Symposium Presenter: Hiral Chhaya for CAP6103.
Computer Network Forensics Lecture 6 – Intrusion Detection © Joe Cleetus Concurrent Engineering Research Center, Lane Dept of Computer Science and Engineering,
A Virtual Honeypot Framework Niels Provos Google, Inc. The 13th USENIX Security Symposium, August 9–13, 2004 San Diego, CA Presented by: Sean Mondesire.
Knowing What You Missed Forensic Techniques for Investigating Network Traffic.
Honeypots and Honeynets Alex Dietz. To discover methods used to breach a system To discover new root kits To learn what changes are made to a system and.
1 HoneyNets. 2 Introduction Definition of a Honeynet Concept of Data Capture and Data Control Generation I vs. Generation II Honeynets Description of.
Evaluate the Merits of Using Honeypots to Defend against Distributed Denial- of-Service Attacks on Web Servers By Cheow Lip Goh.
Wireless Intrusion Prevention System
IT Security Policy: Case Study March 2008 Copyright , All Rights Reserved.
By Daniel, Amitsinh & Alfred.  Collect small data sets which are of high value  All activity is assumed to be malicious  Able to capture encrypted.
WebWatcher A Lightweight Tool for Analyzing Web Server Logs Hervé DEBAR IBM Zurich Research Laboratory Global Security Analysis Laboratory
I NTRUSION P REVENTION S YSTEM (IPS). O UTLINE Introduction Objectives IPS’s Detection methods Classifications IPS vs. IDS IPS vs. Firewall.
HONEYPOTS An Intrusion Detection System. Index Intrusion Detection System Host bases Intrusion Detection System Network Based Intrusion Detection System.
Forensic Computing: Tools, Techniques and Investigations Assignment 1 Seminar.
UNDER THE GUIDENCE OF: Mr.M.JAYANTHI RAO,M.Tech HOD OF IT. BY: I.ADITHYA(09511A1212) HONEYPOTS.
Cryptography and Network Security
Using Honeypots to Improve Network Security Dr. Saleh Ibrahim Almotairi Research and Development Centre National Information Centre - Ministry of Interior.
O honeynet Project Lognitive.com Disclaimer This is a technical session that contain non- technical content. Get relaxed so to get ready for some details.
Security Methods and Practice CET4884
Wenjing Lou Complex Networks and Security Research (CNSR) Lab
Securing Information Systems
12/6/2018 Honeypot ICT Infrastructure Sashan
Friday, December 07, 2018 Honeypot ICT Infrastructure Sashan Kantonsspital Graubunden ICT Department.
Honeypots.
Security Overview: Honeypots
Honeypots Visit for more Learning Resources 1.
Presentation transcript:

HONEYPOT

 Introduction to Honeypot  Honeytoken  Types of Honeypots  Honeypot Implementation  Advantages and Disadvantages  Role of Honeypot in Network Security  Legal issues faced by Honeypot  Vulnerabilities and Solutions  Difference between Honeypot and IDS

 “ A honeypot is a security resource whose value lies in being probed, attacked or compromised.” Lance Spitzner, Honeypots: Tracking Hackers  A decoy computer  A computer system – to capture all the traffic directed to it

 A honeypot:- not a computer  A digital entity  Flexible tool to detect malicious attempt  Enter a fake credit card number in database  Configure the IDS to watch access to that number  E.g excel file, powerpoint presentation, databse entry, fake login etc..

HONEYPOTPurposeResearchProductionInteractionLowMediumHigh

 Study of ◦ Attackers ◦ Attack pattern ◦ Attackers motives and behavior  Users: ◦ Universities ◦ Governments ◦ Military or large corporations interested in learning more about threats ◦ Students or researchers to study cyberthreats

 Security level: Provides very low security to the organization  Uses: ◦ Tremendous value to research field ◦ Instrumental in discovering worms

 Used within an commercial organization  Security level: Provides immediate security to the organization  Working  They mirror the production network of the company  Thus invites attackers and expose them to organization vulnerabilities  Gives lesser information about the attackers then research honeypot

 Level of interaction between the intruder and the system  Emulates some part of the services of the system  No access to the OS  Passive IDS : Can’t modify  Easy to deploy,maintain  Used to analyze spammers  E.g Honeyd: Figure 1: honeyd [1] [1]

 No OS in the systems  Complicated simulated services  Better illusion of the OS to attacker  e.g. Mwcollect, nepenthes, honeytrap  More complex attacks can be logged and analyzed Figure 2: Medium interaction [2][2]

 Most complex and time consuming  Contain actual OS  Attacker has more resources to attack  Closely monitored  Large amount of data acquired E.g Honeynet Figure 3: Honeynet [3][3]

 Factors to consider : ◦ What kind of data used in honeypot systems? ◦ How to prevent honeypot as source of attack? ◦ Whether to build a honeypot or not to do so? ◦ Location of your honeypot.

 Data Value ◦ Provides with less but valuable data  Resource ◦ No resource exhaustion  Simplicity ◦ No fancy algorithms, ◦ No database  Return of investments ◦ Justifies it’s own value, ◦ Also investments in other security resources

 Narrow vision of honeypot ◦ Alarms only when attacked  Fingerprinting ◦ Can be used when detected by attacker  Risk ◦ Introduce risks to the environment Honeypots never used as a replacement, but play a part in providing security

 Prevention ◦ Honeypots add little value ◦ May introduce risks  Deterrence method Advertising the presence of Honeypot to attackers  Deception method Waste attackers time  As long as vulnerable systems present : No honeypot can prevent the attack

 Detection ◦ False positives: The boy who cried the wolf ◦ False negatives: System failed to detect the attack ◦ Data Aggregation: Value of data in determining an attack

 Entrapment ◦ Concern for a honeypot owners. ◦ Attackers may argue entrapment  Privacy ◦ Restrictions on monitoring the network ◦ Privacy policies, terms of agreement etc..  Liability ◦ Potential lawsuits filed against owners

1] Identifying a Honeypot ◦ The value diminishes upon detection ◦ Many tools to discover the honeypots ◦ e.g Spamming industries - Honeypot Hunter  Solution: ◦ Decide how important detection is to you. ◦ Customize your honeypot.

2] Exploiting a Honeypot ◦ Effect on the environment after the honey pot is detected by attacker  Solution: ◦ Several layers of control ◦ Close monitoring of high interaction honeypot ◦ Terminating connections in case of an outbound attack.

3] Attacker Clientele ◦ Effect of deploying incorrect type of honeypot. ◦ Using RedHat 7.3 for protecting e-commerce website.  Solution: ◦ Locate Honeypot in proper place, and at proper time ◦ Honeypot should have correct bait. ◦ Use of CVS is required for e-commerce website.

IDS Honeypot Alerting about the attack May not issue alert: Attack is recent No such issue False positives alarmYes: Untuned IDS alerts too many False positives No Volume of DataCan’t cope with network traffic on large network All the data received is unauthorised

 Honeypots are interesting sociological and technical experiment.  In future attacks will use more advanced type of spoofing techniques  Role of honeypots will hence become more important  Also in future honeypot or honeynet can be implemented as a part of a computing lab

[1] Honeyd Research: Honeypots Against Spam- [2] Honeypot and Honeynet - [3] Intrusion Prevention Systems- week=12 [5] Iyatiti Mokube and Michele Adams, “Honeypots: Concepts, Approaches, and Challenges”, Armstrong Atlantic State University, Savannah [6] Problems and Challenges faced by Honeypots by Lance Spitzner; [7] Kyumin Lee, James Caverleee, Steve Webb, “The Social Honeypot Project: Protecting Online Communities from Spammers” Texas A&M University, College Station, Texas, and Georgia Institute of Technology Atlanta [8] The value of honeypots Chapter 4- “Honeypots: Tracking Hackers” by Lance Spitzner