05-03-2013, 04:34 PM
Jamming Attacks Prevention in Wireless Networks Using Packet Hiding Methods
Jamming Attacks Prevention.pdf (Size: 488.52 KB / Downloads: 153)
Abstract:
The open nature of the wireless medium leaves it vulnerable to intentional interference attacks, typically referred to as jamming. Jamming can be a huge problem for wireless networks. Jamming is one of many exploits used compromise the wireless environment. It works by denying service to authorized users as legitimate traffic is jammed by the overwhelming frequencies of illegitimate traffic. If an attacker truly wanted to compromise your LAN and wireless security, the most effective approach would be to send random unauthenticated packets to every wireless station in the network. To minimize the impact of an unintentional disruption, it is important the identify its presence. Jamming makes itself known at the physical layer of the network, more commonly known as the MAC (Media Access Control) layer. The increased noise floor results in a faltered noise-to-signal ratio, which will be indicated at the client. It may also be measurable from the access point where network management features should able to effectively report noise floor levels that exceed a predetermined threshold. From there the access points must be dynamically reconfigured to transmit channel in reaction to the disruption as identified by changes at the physical layer
Introduction
Wireless networks are susceptible to numerous security threats due to the open nature of the wireless medium. Anyone with a transceiver can eavesdrop on ongoing transmissions, inject spurious messages, or block the transmission of legitimate ones. One of the fundamental ways for degrading the network performance is by jamming wireless transmissions [9], [11], [19], [20]. In the simplest form of jamming, the adversary corrupts transmitted messages by causing electromagnetic interference in the network’s operational frequencies, and in proximity to the targeted receivers [15]. For an adversary agnostic to the implementation details of the network, a typical jamming strategy is the continuous emission of high-power interference signals such as continuous wave tones, or FM modulated noise [15]. However, adopting an “always-on” jamming strategy has several disadvantages. First, the adversary has to expend a significant amount of energy to jam frequency bands of interest. Second, the continuous presence of high interference levels make this type of jamming easy to detect [11], [19], [20]. Third, these attacks are easy to mitigate either by spread spectrum communications [15], spatial retreats [20], or localization and removal of the jamming nodes. In this paper, we consider a sophisticated adversary model in which the adversary is aware of the implementation details of the network protocols. By exploiting this knowledge, the adversary launches selective jamming attacks in which it targets specific packets of “high” importance. For example, jamming of TCP acknowledgments (ACKs) can severely degrade the throughput of a TCP connection due to the congestion control mechanism of the TCP protocol [3]. Compared to continuous jamming, the adversary is active for a short period of time, thus expending orders of magnitude less energy. To perform selective jamming, the adversary must be capable of classifying transmitted packets in real time, and corrupting them before the end of their transmission. Packet classification can be performed by receiving just a few bytes of a packet, for example, by decoding the frame control field of a MAC-layer frame. We are interested in developing resource efficient methods for preventing real-time packet classification and hence, mitigating selective jamming. Our contributions are summarized below.
A. Our Contributions
We investigate the feasibility of real-time packet classification for launching selective jamming attacks. We consider a sophisticated adversary who exploits his knowledge on network protocols along with secrets extracted from compromised nodes to maximize the impact of his attack. To mitigate selective jamming, we combine cryptographic mechanisms such as commitment schemes [6], cryptographic puzzles [7], and all in- one transformations [13], with physical-layer parameters.
We further study the impact of various selective jamming strategies on the performance of the TCP protocol. The remainder of the paper is organized as follows. Section II, presents related work. In Section III, we describe the problem addressed, and state the system and adversarial model assumptions. In Section IV, we
Jamming Attacks Prevention in Wireless Networks Using Packet Hiding Methods
www.iosrjournals.org 14 | P a g e
illustrate the feasibility of selective jamming attacks. In Section V, we develop methods for preventing selective jamming. Section VI, illustrates the impact of selective jamming on the performance of TCP. In Section VII, we conclude.
RELATED WORK
Continuous jamming has been used as a denial-of-service (DoS) attack against voice communication since the 1940s [15]. Re cently, several alternative jamming strategies have been demonstrated [11], [12], [19], [20]. Xu et. al. Categorized jammers into four models, (a) a constant jammer that continuously emits noise, (b) a deceptive jammer that continuously broadcasts fabricated messages or replays old ones, © a random jammer that alternates between periods of continuous jamming and inactivity, and (d) a reactive jammer who jams only when transmission activity is detected. Intelligent attacks which target the transmission of specific packets were presented in [8], [18]. Thuente considered an attacker who infers eminent packet transmissions based on timing information at the MAC layer. Law et. al. considered(a) (b)
PROPOSED WORK
Here the contribution towards jamming attacks is reduced by using the two algorithms 1. Symmetric encryption algorithm 2. Brute force attacks against block encryption algorithms The proposed algorithm keeps these two in mind as they are essential in reducing the jamming attacks by using the packet hiding mechanism.
Problem Statement And Assumptions
Problem Statement
Consider the scenario depicted in Fig. 1(a). Nodes A and B communicate via a wireless link. Within the communication range of both A and B there is a jamming node J. When A transmits a packet m to B, node J classifies m by receiving only the first few bytes of m. J then corrupts m beyond recovery by interfering with its reception at B. We address the problem of preventing the jamming node from classifying m in real time, thus mitigating J’s ability to perform selective jamming. Our goal is to transform a selective jammer to a random
Jamming Attacks Prevention in Wireless Networks Using Packet Hiding Methods
one. Note that in the present work, we do not address packet classification methods based on protocol semantics, as described in [1], [4], [11], [33].
Implementation
The implementation environment has software such as JDK 1.6 running in Windows XP operating system. The system uses Java technology such as RMI (Remote Method Invocation). Java’s SWING API is used to build user interface. The RMI technology lets nodes to communicate remotely. The simulation has three kinds of nodes namely centralized server, server and client. The purpose of source is to send the data to the destination. There sender will be consisting of the Channel Encoder, Interleaver and the Modulator. For simulation of communication in WSN, the server node is able to send messages to client nodes based on the port number and the communication is routed through one of the centralized servers. Here user is able to select a file by clicking browse button. The Send button is to be initiated by user in order to send messages to client based on port number. The message or file selected is broken into packets with length 48 bytes.