DistOS-2011W Attribution

Members

• Abdelrahman Abdou
• Raghad Al-Awwad
• Omi Iyamu
• Rakhim Davletkaliyev

Meeting Briefings

Tuesday, March 1st

After 20 minutes of brainstorming, we agreed on:

• Current internet infrastructure lacks the ability of achieving highly scalable and efficient attribution mechanism.
• Attribution must be implemented in a distributed manner and must be automated and not owned.
• Threats that should be addressed include (but not limited to):
  • Computers, individuals and applications impersonation
  • All types of electronic spoofing.
• The skeleton of our project will constitute four main aspects:
  • Tracing/Tracking: baseline for attribution.
  • Human identification: a MUST to include!
  • Machine identification: to be dissolved with human identification.
  • Storage: how and where to store data traces and the identification stamps.

Thursday, March 3rd

Coming Soon!

Surveyed Papers

[1] Barik,Vladimir, Wireless device identification with radiometric signatures, 2008. PDF

• ABSTRACT

We design, implement, and evaluate a technique to identify the source network interface card (NIC) of an IEEE 802.11 frame through passive radio-frequency analysis. This technique, called PARADIS, leverages minute imperfections of transmitter hardware that are acquired at manufacture and are present even in otherwise identical NICs. These imperfections are transmitter-specific and manifest themselves as artifacts of the emitted signals. In PARADIS, we measure differentiating artifacts of individual wireless frames in the modulation domain, apply suitable machine-learning classification tools to achieve significantly higher degrees of NIC identification accuracy than prior best known schemes. We experimentally demonstrate effectiveness of PARADIS in differentiating between more than 130 identical 802.11 NICs with accuracy in excess of 99%. Our results also show that the accuracy of PARADIS is resilient against ambient noise and fluctuations of the wireless channel. Although our implementation deals exclusively with IEEE 802.11, the approach itself is general and will work with any digital modulation scheme.

[2] Subhabrata Sen, Oliver Spatscheck, Dongmei Wang, Accurate, scalable in-network identification of p2p traffic using application signatures, AT&T Labs-Research, Florham Park, NJ, 2004. PDF

• ABSTRACT

The ability to accurately identify the network traffic associated with different P2P applications is important to a broad range of network operations including application-specific traffic engineering, capacity planning, provisioning, service differentiation,etc. However, traditional traffic to higher-level application mapping techniques such as default server TCP or UDP network-port baseddisambiguation is highly inaccurate for some P2P applications.In this paper, we provide an efficient approach for identifying the P2P application traffic through application level signatures. We firstidentify the application level signatures by examining some available documentations, and packet-level traces. We then utilize the identified signatures to develop online filters that can efficiently and accurately track the P2P traffic even on high-speed network links.We examine the performance of our application-level identification approach using five popular P2P protocols. Our measurements show thatour technique achieves less than 5% false positive and false negative ratios in most cases. We also show that our approach only requires the examination of the very first few packets (less than 10packets) to identify a P2P connection, which makes our approach highly scalable. Our technique can significantly improve the P2P traffic volume estimates over what pure network port based approaches provide. For instance, we were able to identify 3 times as much traffic for the popular Kazaa P2P protocol, compared to the traditional port-based approach.

Milestones

(Under Construction)

• Problem definition
• Literature review
• ??

Project Progress

Coming Soon!

Requirements

• incremental deployability
• privacy

Readings

really hard to find anything not from psychology