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Dynamic Ordering of Firewall Rules Using a Novel Swapping Window-based Paradigm

Mohan, Ratish; Yazidi, Anis; Feng, Boning; Oommen, John
Peer reviewed, Chapter
Accepted version
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Postprint (328.5Kb)
Permanent lenke
https://hdl.handle.net/10642/4060
Utgivelsesdato
2016
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Originalversjon
Mohan R, Yazidi A, Feng B, Oommen J: Dynamic Ordering of Firewall Rules Using a Novel Swapping Window-based Paradigm. In: NN N. Proceedings of the 6th International Conference on Communication and Network Security (ICCNS '16), 2016. Association for Computing Machinery (ACM) p. 11-20  
Sammendrag
Designing and implementing efficient firewall strategies in

the age of the Internet of Things (IoT) is far from trivial. This

is because, as time proceeds, an increasing number of devices

will be connected, accessed and controlled on the Internet.

Additionally, an ever-increasingly amount of sensitive information

will be stored on various networks. A good and effi-

cient firewall strategy will attempt to secure this information,

and to also manage the large amount of inevitable network

traffic that these devices create. The goal of this paper is to

propose a framework for designing optimized firewalls for

the IoT.

This paper deals with two fundamental challenges/problems

encountered in such firewalls. The first problem is associated with the so-called “Rule Matching” (RM) time problem.

In this regard, we propose a simple condition for performing

the swapping of the firewall’s rules, and by satisfying

this condition, we can guarantee that apart from preserving

the firewall’s consistency and integrity, we can also

ensure a greedy reduction in the matching time. It turns out

that though our proposed novel solution is relatively simple,

it can be perceived to be a generalization of the algorithm

proposed by Fulp [1]. However, as opposed to Fulp’s solution,

our swapping condition considers rules that are not necessarily

consecutive. It rather invokes a novel concept that

we refer to as the “swapping window”.

The second contribution of our paper is a novel “batch”-

based traffic estimator that provides network statistics to the

firewall placement optimizer. The traffic estimator is a subtle

but modified batch-based embodiment of the Stochastic

Learning Weak Estimator (SLWE) proposed by Oommen and

Rueda [2].

The paper contains the formal properties of this estimator.

Further, by performing a rigorous suite of experiments, we

demonstrate that both algorithms are capable of optimizing

the constraints imposed for obtaining an efficient firewall
Utgiver
Association for Computing Machinery (ACM)

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