Optimal
Source-Based Filtering of Malicious Traffic
ABSTRACT:
In this
paper, we consider the problem of blocking malicious traffic on the Internet
via source-based filtering. In particular, we consider filtering via access
control lists (ACLs): These are already available at the routers today, but are
a scarce resource because they are stored in the expensive ternary content
addressable memory (TCAM). Aggregation (by filtering source prefixes instead of
individual IP addresses) helps reduce the number of filters, but comes also at
the cost of blocking legitimate traffic originating from the filtered prefixes.
We show how to optimally choose which source prefixes to filter for a variety
of realistic attack scenarios and operators’ policies. In each scenario, we
design optimal, yet computationally efficient, algorithms. Using logs from
Dshield.org, we evaluate the algorithms and demonstrate that they bring
significant benefit in practice.
EXISTING SYSTEM:
Protecting a
victim (host or network) from malicious traffic is a hard problem that requires
the coordination of several complementary components, including nontechnical
(e.g., business and legal) and technical solutions (at the application and/or
network level). Filtering support from the network is a fundamental building
block in this effort. For example, an Internet service provider (ISP) may use
filtering in response to an ongoing DDoS attack to block the DDoS traffic
before it reaches its clients. Another ISP may want to proactively identify and
block traffic carrying malicious code before it reaches and compromises
vulnerable hosts in the first place. In either case, filtering is a necessary
operation that must be performed within the network.
Filtering
capabilities are already available at routers today via access control lists
(ACLs). ACLs enable a router to match a packet header against predefined rules
and take predefined actions on the matching packets [1], and they are currently
used for enforcing a variety of policies, including infrastructure protection
[2]. For the purpose of blocking malicious traffic, a filter is a simple ACL
rule that denies access to a source IP address or prefix. To keep up with the
high forwarding rates of modern routers, filtering is implemented in hardware:
ACLs are typically stored in ternary content addressable memory (TCAM), which
allows for parallel access and reduces the number of lookups per forwarded
packet.
DISADVANTAGES OF EXISTING SYSTEM:
TCAM is more
expensive and consumes more space and power than conventional memory. The size
and cost of TCAM puts a limit on the number of filters, and this is not
expected to change in the near future.1 With thousands or tens of thousands of
filters per path, an ISP alone cannot hope to block the currently witnessed
attacks, not to mention attacks from multimillion-node botnets expected in the
near future.
PROPOSED SYSTEM:
In this
paper, we formulate a general framework for studying source prefix filtering as
a resource allocation problem. To the best of our knowledge, optimal filter
selection has not been explored so far, as most related work on filtering has
focused on protocol and architectural aspects. Within this framework, we
formulate and solve five practical source-address filtering problems, depending
on the attack scenario and the operator’s policy and constraints. Our
contributions are twofold. On the theoretical side, filter selection
optimization leads to novel variations of the multidimensional knapsack
problem.We exploit the special structure of each problem and design optimal and
computationally efficient algorithms. On the practical side, we provide a set
of cost-efficient algorithms that can be used both by operators to block
undesired traffic and by router manufacturers to optimize the use of TCAM and
eventually the cost of routers.
ADVANTAGES OF PROPOSED SYSTEM:
The proposed
system can be used to protect all network infra-structure from malicious
traffic, such as scanning, malicious code propagation, spam, and distributed
denial-of-service (DDoS) attacks.
MODULES:
ü Network
Creation Module
ü Optimal
Source based filtering module
ü Filter
Selection Module
ü Evaluation
module
HARDWARE
REQUIREMENTS:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive :
1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• Ram : 512 Mb.
SOFTWARE
REQUIREMENTS:
• Operating system : - Windows XP.
• Coding Language : VB.NET
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