Fast Packet Classification for Snort by Native Compilation of Rules

نویسندگان

  • Alok Tongaonkar
  • Sreenaath Vasudevan
  • R. Sekar
چکیده

Signature matching, which includes packet classification and content matching, is the most expensive operation of a signature-based network intrusion detection system (NIDS). In this paper, we present a technique to improve the performance of packet classification of Snort, a popular open-source NIDS, based on generating native code from Snort signatures. An obvious way to generate native code for packet classification is to use a low-level language like C to access the contents of a packet by treating it as a sequence of bytes. Generating such low-level code manually can be cumbersome and error prone. Use of a high-level specification language can simplify the task of writing packet classification code. Such a language needs features that minimize the likelihood of common errors as errors in the packet processing code can crash the intrusion detection system, which may leave it open to attacks. To overcome these problems, we use a rule-based specification language with a type system for specifying the structure and contents of packets. The compiler for the specification language generates C code for packet classification. This code can be compiled into native code using a C-compiler and loaded into Snort as shared library. Our experiments using real and synthetic traces show that the use of native code results in a speedup of the packet classification of Snort up to a factor of five.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fast Packet Classification Using Condition Factorization

Rule-based packet classification plays a central role in network intrusion detection systems such as Snort. To enhance performance, these rules are typically compiled into a matching automaton that can quickly identify the subset of rules that are applicable to a given network packet. The principal metrics in the design of such an automaton are its size and the time taken to match packets at ru...

متن کامل

SNORTRAN: An Optimizing Compiler for Snort Rules

We developed an optimizing compiler for intrusion detection rules popularized by an open-source Snort Network Intrusion Detection System (www.snort.org). While Snort and Snort-like rules are usually thought of as a list of independent patterns to be tested in a sequential order, we demonstrate that common compilation techniques are directly applicable to Snort rule sets and are able to produce ...

متن کامل

Improvement and parallelization of Snort network intrusion detection mechanism using graphics processing unit

Nowadays, Network Intrusion Detection Systems (NIDS) are widely used to provide full security on computer networks. IDS are categorized into two primary types, including signature-based systems and anomaly-based systems. The former is more commonly used than the latter due to its lower error rate. The core of a signature-based IDS is the pattern matching. This process is inherently a computatio...

متن کامل

On the fly pattern matching for intrusion detection with Snort

Intrusion Detection Systems are becoming necessary tools for system administrators to protect their network. However they find more and more difficulties with high speed networks. To enhance their capacity and deal with evasion techniques, frequently used by hackers, we have introduced a new method to filter the network traffic. The detection method, while being stateful, processes each packet ...

متن کامل

Analysis and Data Retrieval by Filtering Packets in High Speed Routers

In this paper, we are going to decompose the operation of multimatch packet classification from the complicated multidimensional search to several single-dimensional searches, and present an asynchronous pipeline architecture based on a signature tree structure to combine the intermediate results returned from single-dimensional searches. By spreading edges of the signature tree across multiple...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008