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Implementing Distributed Internet Security using a Firewall Collaboration Framework. Lane Thames and Randal Abler Georgia Institute of Technology Distributed Network Applications Laboratory . Outline. Introduction Computer security overview Firewall technology overview Related Work

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implementing distributed internet security using a firewall collaboration framework

Implementing Distributed Internet Security using a Firewall Collaboration Framework

Lane Thames and Randal Abler

Georgia Institute of Technology

Distributed Network Applications Laboratory

outline
Outline
  • Introduction
  • Computer security overview
  • Firewall technology overview
  • Related Work
  • Firewall Collaboration Framework
  • Future Work and Conclusions
introduction
Introduction
  • The Internet is growing
  • The growth appears to be accelerating
internet growth and attack trends
Internet Growth and Attack Trends
  • As the phenomenal growth of the Internet continues, malicious activities will continue to increase as well.
  • Hacking: Computer activity with malicious intentions.
hacking trends
Hacking Trends
  • Paradigm shift taking place in the Hacking Community.
  • Whereas hackers once performed their malicious deeds for Internet notoriety, there are now large numbers that do this for profit.
hacking trends1
Hacking Trends
  • According to PC World News, Jeanson Ancheta was arrested by the FBI in 2006 and was the first hacker to be prosecuted in the US for creating malicious code for a profit.
hacking trends2
Hacking Trends
  • According to Symantec, spammers and phishers pay on average about $350.00 per week for a botnet of 5500 zombie computers.
hacking trends3
Hacking Trends
  • Corporate extortion, information espionage, and identity theft are Internet commodities for malicious users.
  • Protx—British online payment processing company. Attacks brought their system down in 2005. The extortionists warned that the attacks would continue unless a $10,000 fee was paid.
hacking trends4
Hacking Trends
  • Identity theft—huge ROI for hackers
  • According to anti-spam provider Cloudmark, credit card data sells for up to $100.00 per account.
the engineering need
The Engineering Need
  • What does the data tell us?
  • There still exists an engineering need to continue developing reliable and robust computer security systems that can thwart the actions of malicious users as their tools and techniques continue to evolve.
  • Because of the financial incentives now presented to hackers, the need is even greater than in the past.
computer security overview
Computer Security Overview
  • The field of computer security provides the technologies to prevent users with malicious intent from doing damage
computer security services
Computer Security Services
  • The five main services:
    • Confidentiality
    • Authenticity
    • Integrity
    • Availability
    • Access Control
computer network attack types
Computer/Network Attack Types
  • Common Attack Types
    • Buffer Overflow Exploits
    • Denial of Service
    • Password Attacks
computer network attack types1
Computer/Network Attack Types
  • Common Attack Types
    • Exponential Attacks
    • Trojan Horses, Spyware, Adware
    • Spam and Phishing
    • TCP/IP protocol exploitation
overview of firewall technology
Overview of Firewall Technology
  • Firewalls—devices that limit network access
  • Firewalls are access control mechanisms
  • They are components inserted between two networks that filter network traffic according to a LOCAL security policy
firewall types
Firewall Types
  • Packet Filtering Devices
  • Application Filtering Devices
  • Stateful Packet Filtering Devices
firewall strengths
Firewall Strengths
  • Disallows incoming connections to hosts that do not offer public network services
  • Reduces the amount of dangerous noise flowing through networks (probes)
  • Allows administrators tools to control their networks from the inside and outside (i.e. do you allow your users to get access to the Web?)
firewall weaknesses
Firewall Weaknesses
  • Because of increasing line speeds and computation-intensive protocols (IPSec), the firewall can become a congestion point
  • There exist protocols that are difficult to process at the firewall
  • Classical firewall design assumes that all internal users can be trusted
firewall weaknesses1
Firewall Weaknesses
  • Large networks tend to have high numbers of ingress points. This makes administration difficult, both from a practical point of view and with regard to policy consistency
  • End-to-end encryption can be a threat to firewalls as it prevents the firewalls from looking at the packet fields necessary for certain types of filtering
related work
Related Work
  • Bellovin, et al—First to describe a distributed firewall system.
  • Many firewalls within an institute’s network, all being centrally managed
  • Overcome issues like multiple ingress points and trusting inside users
related work1
Related Work
  • Smith, et al—Cascade model of distributed firewalls
  • Zou, et al—Defense in Depth model of distributed firewalls
  • These two works are similar in nature
related work2
Related Work
  • Schnackenberg, et al—Infrastructure for Intrusion Detection and Response
  • Intrusion Detection and Isolation Protocol (IDIP)
  • Similar in nature to the FCF, but designed with IDS at the core
firewall collaboration framework
Firewall Collaboration Framework
  • Some factors driving the design and development of this framework
spam statistics 3 2006
Spam Statistics [3](2006)
  • Email considered spam: 40% of all email
  • Daily spam emails sent: 12.4 billion
  • Daily spam received per person: 6
  • Email address changes due to spam: 16%
  • Wasted corporate time per spam email: 4-5 seconds
  • Estimated spam increase by end of 2007: 63%
exponential attacks internet worms
Exponential Attacks-Internet Worms
  • The Logistics equation is commonly used to model worm propagation. It can be derived (not just assumed)
  • The logistics equation describes the rate of growth of epidemics in finite systems when all entities are equally likely to infect any other entity
worm propagation model
Worm Propagation Model
  • N(t): the number of infected hosts at t
  • S: the total number of susceptible hosts
  • α: the rate at which one machine can compromise another
  • T: the time where ½ of the total number of susceptible hosts are infected
the philosophy of this work
The Philosophy of this Work
  • Limit the impact of malware such as worms, viruses, and spam as well as the actions of malicious users by attempting to stop the malicious behavior as close to the source as possible thus preserving network resources for intended applications
high level system description
High Level System Description
  • Create a federation of firewalls that collaborate with each other and share a “global” pool of information.
  • Use advanced algorithms to classify malicious activities in real-time.
  • Distribute the new attack classification information to members of the federation
framework components
Framework Components

FederationManagement

Trust Relationship Management

Policy Management

Network Traffic Classification

Information Management

Resource Management

federation management
Federation Management
  • Control membership of new firewalls to the federation
  • Responsible for establishing initial trust between the new firewall and the federation
trust relationship management
Trust Relationship Management
  • Maintain trust relationships between members
  • Information authentication
  • Credential management
policy management
Policy Management
  • Responsible for differentiating “Local” security policy from “Global” security policy
network traffic classification
Network Traffic Classification
  • Let’s look a little closer at some attack types
buffer overflow case study1

buf

Other data

Return Address

* str=input buffer

Rest of Stack

Buffer Overflow—Case Study
  • Abstract view of the memory stack before the call to strcpy
attack case studies summary
Attack Case Studies--Summary
  • With each of the previous mentioned case studies, data flows can be collected from end hosts and from within the network
  • The collected data flows can be analyzed with algorithms, and behavioral classification can be performed
  • The behavioral classification allows the observation of malicious behavior to be made
network traffic classification1
Network Traffic Classification
  • Classical Types of Classification
    • Statistical based anomaly detection
    • Rule based anomaly detection
    • Signature based anomaly detection
    • Artificial intelligence and machine learning techniques [4]
  • Main goal: Classify traffic in real-time and send information vectors to the federation
information management
Information Management
  • Information transport
    • Centralized, peer-to-peer, hybrid
  • Information caching and staleness
  • Information confidentiality and integrity
resource management
Resource Management
  • Provide mechanisms needed for scalability, reliability, and robustness
experimental evaluation
Experimental Evaluation
  • Linux IPtables firewall mechanism
  • PortSentry scan detection tool
  • netcat and Perl scripting
  • nmap scanning tool
experimental evaluation1
Experimental Evaluation
  • Stop at source? YES
  • Preemptive protection? YES
  • Is denial of service a major threat? YES
future work
Future Work
  • The framework is in its initial design stage
  • Solution spaces for the framework components will be evaluated
  • In depth analysis of the solution space for the network traffic classification component as it is the major component of the framework
conclusion
Conclusion
  • Computer network attacks evolve on a daily basis. Financial incentives will drive the evolution of these attacks. We believe the FCF will be a useful tool for protecting networks against attack. The framework will allow malicious data flows to be stopped at or close to the source, and it will allow for preemptive protection.
references
References
  • CERT—Computer Emergency Response Team, http://www.cert.org
  • “Internet traffic growth: Sources and implications,” A.M. Odlyzko, Proceedings of SPIE, 2003
  • http://spam-filter-review.toptenreviews.com, D. Evett, 2006
  • “Hybrid Intelligent Systems for Network Security,” J.L.Thames, R. Abler, A. Saad, Proceedings of the ACM Southeast Conference, 2006
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