International Journal of Engineering Trends and Technology (IJETT) – Volume 4 Issue 9- Sep 2013
Key Recovery Based Preventing Method for
Blocking Attacks
M.Kavitha1, A.V.D.N.Murthy2, P. Suresh Babu3
1
1,2,3
Final M.Tech Student , 2Assistant Professor, 3Associate Professor
Department Of Computer Science & Engineering, Kaushik College of Engineering,
Visakhapatnam, Andhra Pradesh.
Abstract: Data transferring/exchanging is more
happening process in present days, well as the network
problems also there in present communications. Such as
protocol, collisions of packets when transferring, Daniel
of Service etc. From these problems we have to achieve
more security over the network to exchange data. There
are so many methods to secure data from these
problems. These methodologies are different types such
as based on network layer, transport layer etc. Under
theses methodologies the data is converted to un format
using some cryptographic and key exchanging methods.
We introduced a methodology that contains key
recovery, this is secure process that the key which is
used to covert data is not exchanged between the users
but reveals by the users. Most of the data is captured by
attacking on keys in the network. That’s why we
introduced this technique, adding to this symmetric
cryptographic algorithm is used to send data more
secure.
I.INTRODUCTION
In computing, a denial-of-service attack (Daniel of Service
attack) or distributed denial-of-service attack (Daniel of
Service attack) is an attempt to make a machine or network
resource unavailable to its respective users. And also that
means to carry out and motives for and targets of a Daniel
of Service attack may vary and it is generally consists of
efforts to temporarily or indefinitely interrupt or suspend
services of a host connected to the Internet[1][13].
A denial-of-service attack is characterized by an
explicit attempt by attackers to prevent legitimate users of a
service from using the service. There are two types forms
of Daniel of Service attacks: those that crash services and
those that flood services. A Daniel of Service attack can be
perpetrated in so many ways. There are five types of attack
are:
1. Consumption of computational resources are
bandwidth and disk space or processor time.
2. Disruption of configuration information is routing
information.
3. Disruption of state information is unsolicited
resetting of TCP sessions.
4. Disruption of physical network components.
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5.
Obstructing the communication media between
the intended users and the victim so that they can
no longer communicate adequately.
A Daniel of Service attack may include execution of
malware intended to
 Max out the processor's usage of preventing any
work from occurring.
 It finds errors in the microcode of the machine.
 It finds errors in the sequencing of instructions
and to force the computer into an unstable state or
lock-up.
 Exploit errors in the operating system that cause
resource starvation and/or thrashing that is to use
up all available facilities so no real work can be
accomplished or it can crash the system itself
 Crash the operating system itself.
In most cases Daniel of Service attacks involve forging
of IP sender addresses (IP address spoofing) so that the
location of the attacking machines cannot easily be
identified and to prevent filtering of the packets based on
the source address. Anyone with a transceiver can
eavesdrop on wireless transmissions that inject spurious
messages or jam legitimate ones. While eavesdropping and
message injection can be prevented using cryptographic
methods and jamming attacks are much harder to counter.
Since RF (radio frequency) is essentially an open
medium is jamming can be a huge problem. Jamming is
one of many exploits used compromise the wireless
environment and it is by denying service to authorized
users as legitimate traffic is jammed by the overwhelming
frequencies of illegitimate traffic. A very technical
knowledge attacker with the right tools can easily jam
frequency in a way and that reduces the signal to a level
where the wireless network cans no longer function. The
processing time of jamming is the fact that it may not be
caused on demand as other forms of wireless technology
are relying on the frequency. Some widely used consumer
products include cordless phones and Bluetooth-enabled
devices and baby monitors are all capable of disrupting the
signal of a wireless network and faltering traffic. Jamming
mostly relates to older wireless local area networks as they
are not fully equipped to make the adaptation to more types
of interference and those networks reglarly call for an
administrator to manually adjust each access point through
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trial and error. To avoid this daunting task and best practice
is to invest into a new wireless local network system. These
environments offer real-time management features capable
of identifying and adapting to unintentional interference.
If an attacker truly wanted to compromise your LAN
and wireless security and most effective approach would be
to send random unauthenticated packets to every wireless
station in the network. It is easily achieved by purchasing
hardware off the shelf from an electronics retailer and
downloading free software from the internet. In some cases
and simply impossible to defend against jamming as an
experienced attacker may have the ability to flood all
available network frequencies. There is a case If the major
concern relates to malicious jamming as an intrusion
prevention and detection system may be your best option.
This type of system should be able to detect the presence of
an RPA (Rogue Access Point) or any authorized client
device in your wireless network. Very efficient systems can
prevent unauthorized clients from accessing the system and
then alter configurations to maintain network performance
in the presence of an attack that the blacklist certain threats
and pinpoint the physical location of a rogue device to
enable faster containment. It doesn't what type of
interference you're experiencing; the network must have
the ability to detect it and that reacts and quickly make
adjustments.
To minimize the impact of an unintentional disruption,
and it is important to identify its presence. It makes itself
known at the physical layer of the network, more
commonly known as Media Access Control layer and
increased noise floor results in a faltered noise-to-signal
ratio and which will be indicated at the client. It is
measurable from the access point where network
management features should able to effectively report noise
floor levels that exceed a predetermined threshold. There is
an access points must be dynamically reconfigured to
transmit channel in reaction to the disruption as identified
by changes at the physical layer. Consider that if the attack
occurred on an RF corresponding to channel 1 and the
access point should switch to channel 6 or 11 in order to
avoid the attack. Selecting a different channel does not
always eliminate the issue of interference. A very
intelligent attacker will often use all available channels in
the attack. When this happens that’s your only option may
be to physically hunt down the attacker and confront them
face to face.
II. RELATED WORK
Although several studies have targeted jammingstyle attacks, the definition of this type of attack remains
un- clear. A common assumption is that a jammer
continuously emits RF signals to fill a wireless channel and
so that strict traffic will be completely blocked. We believe
that a broader range of behaviours can be adopted by a
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jammer. Consider an example and that a jammer may
remain quiet when there is no activity on the channel, and
start interference as soon as it detects a transmission. The
common characteristic for all jamming attacks is that their
communications are not compliant with MAC protocols.[1]
Therefore, we define a jammer to be an entity who is
purposefully trying to interfere with the physical
transmission and reception of wireless communications.
The objective of a jammer is to interfere with
legitimate wireless communications. A jammer fulfil
his/her goal by either preventing a real traffic source from
sending out a packet or by preventing the reception of
legitimate packets. Let us assume that A and B denote two
legitimate wireless participants, and let us denote X to be
the jammer. A legitimate participant may be unable to send
out packets for many reasons. To name just a couple, X can
continuously emit a signal on the channel so that A will
never sense the channel as idle, or X can keep sending out
regular data packets and force A to receive junk packets all
the time. On the other hand, however, even if A
successfully sends out packets to B, it is possible for X to
blast a radio transmission to corrupt the message that B
receives. We thus define the following two metrics to
measure the effectiveness of a jammer:
 Packet Send Ratio (PSR): The ratio of packets that are
successfully sent out by a legitimate traffic source
compared to the number of packets it intends to send out at
the MAC layer. Suppose A has a packet to send. There are
so more wireless networks employ some form of carriersensing multiple access control before transmission may be
performed. For example, in the MAC pro- tocol employed
by Mica2, the channel must be sensed as being in an idle
state for at least some random amount of time before A can
send out a packet. Further, different MAC protocols have
different definitions on an idle channel. Some simply
compare the signal strength measured with a fixed
threshold, while others may adapt the threshold based on
the noise level on the channel. A radio interference attack
may cause the channel to be sensed as busy, causing A's
transmission to be delayed. If too many packets are
buffered in the MAC layer, the newly arrived packets will
be dropped. It is also possible that a packet stays in the
MAC layer for too long, resulting in a timeout and packets
being discarded. If A intends to send out n messages, but
only m of them go through, the PSR is m n . The PSR can
be easily measured by a wireless device by keeping track of
the number of packets it intends to send and the number of
packets that are successfully sent out.
 Packet Delivery Ratio (PDR): The ratio of packets that
are successfully delivered to a destination compared to the
number of packets that have been sent out by the sender.
Even after the packet is sent out by A, B may not be able to
decode it correctly, due to the interference introduced by X.
Such a scenario is an unsuccessful delivery. The PDR may
be measured at the receiver B by calculating the ratio of the
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number of packets that pass the CRC check with respect to
the number of packets (or preambles) received. PDR may
also be calculated at the sender A by having B send back an
acknowledge packet. In either case, if no packets are
received PDR is defined to be 0.
A) Types of jamming
A. Physical Jamming (Physical Layer)
Physical or Radio jamming in a wireless medium
is a simple but disruptive form of Daniel of Service attack.
These attacks are launched by either continuous emission
of radio signals or by sending random bits onto the
channel. The jammers causing these attacks can deny
complete access to the channel by monopolizing the
wireless medium. The no destroying to communicate has
an unusually large carrier sensing time waiting for the
channel to become idle. This has an adverse propagating
effect as the nodes enter into large exponential back-off
periods.
B. Virtual Jamming (MAC Layer)
In IEEE 802.11 based MAC protocols and the
virtual carrier sensing is used at the MAC layer to
determine the availability of the wireless medium. The
process Jamming can be launched at the MAC layer
through attacks on the RTS/CTS frames or DATA frames.
A significant advantage of MAC layer jamming is that the
adversary node consumes less power in targeting these
attacks as compared to the physical radio jamming. Here,
we focus on Daniel of Service attacks at the MAC layer
resulting in collision of RTS/CTS control frames or the
DATA frames [4][9]
C. Synchronization Signal Jamming (SSJ)
When a UE wants to connect to an Node, it has to
first go through a series of synchronization steps. Initially it
detects the Primary Synchronization Signal which allows
the UE to synchronize to each slot and gives it the cell ID.
Next, it detects the Secondary Synchronization Signal
(SSS) which tells the UE the cell ID group which method
of duplexing is used and the cyclic prefix length. The SSS
also allows the UE to detect when each radio frame starts.
After synchronizing with the PSS and SSS, the UE receives
more information about the cell by decoding the Master
Information Block (MIB). The MIB contains information
essential for initial access to a cell. It consists of 14 bits
that contain the downlink system bandwidth and Physical
Control Format Indicator Channel (PHICH) size, and
information allowing frame synchronization and mapped to
the central 72 subcarriers that appear in slot 1 of each
frame. There are three signals and they are not present in
all ten sub-frames, but they are always mapped to the same
subcarriers.
The Synchronization Signal Jamming (SSJ) attack
is designed to deny the UE access to the PSS, SSS, and
MIB. The jamming waveform used for the SSJ attack is
noise that spans the centre 73 subcarriers. For the usage of
complexity the DC sub carriers are included and even
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though it does not contain information. The
Synchronization Signal Jamming attack does not involve
jamming specific symbols and so that the jammer does not
have to be synchronized to the Node. The SSJ attack is
simply a brute force method of denying the UE three
different mechanisms that it needs to access a cell. The act
of only jamming some of subcarriers that allows the SSJ
attack to have roughly a 3 dB gain over traditional barrage
jamming and the which can be thought of as an increase in
jamming radius for a jammer that is power constrained.
D. Primary Synchronization Signal Jamming
Detecting the PSS is the first step a UE takes in
accessing a cell. It uses a sequence length of 63 and centre
element is null because the downlink DC subcarrier is
never used for transmission. There are three PSS sequences
used in LTE, and each one corresponds to one of the three
sectors. The UE must detect the PSS without any
knowledge of the channel therefore it finds the timing
offset that corresponds to the maximum cross correlation
for each of the three sequences, and uses it to synchronize
in the time domain. For FDD, the PSS only occurs in slots
0 and 10 (there are 20 total slots per frame). The SSJ attack
discussed previously injects noise into the subcarriers that
contain the PSS. An attack that only targets the PSS can be
realized by only jamming the symbols that contain the PSS.
Jammer would have to cause a fairly high jammer-to-signal
ratio, because the PSS is designed to be detected at high
interference levels and so that the UE can also detect
neighbouring cells. A more effective method of causing a
PSS attack would be to simply transmit one of the three
PSS sequences thus create a corruted PSS. If the jammers
received power at the UE is greater than the Node's, then
the UE is most likely going to synchronize to the bogus
PSS.
This is because a cross-correlation process is used
to detect the PSS non-coherently. A jammer using this
method would not need receiving capability but it would
simply start the bogus PSS transmission at a random time
and the leading to uniformly distributed timing relative to
the correct PSS signal. If the UE synchronized to the
corrupted PSS, then is not synchronized in time to the
Node, and it will not know when each OFDM symbol
starts, and hence will not be able to detect the SSS or
decode the MIB. This attack appears to work, until
considering the cell re-selection procedure. If a cell does
not provide a certain level of quality, after that UE begins
the cell reselection procedure, where it tries to access the
cell with the next strongest signal. Jammer can transmitting
three bogus PSSs only has to transmit six symbols in every
frame, on 62 subcarriers. A downside to PSS jamming is
that it will not immediately cause Denial of Service
(DANIEL OF SERVICE). It will prevent new UEs from
accessing the cell(s), and cause UEs in idle mode to
reselect a corrupted cell. Therefore PSS jamming is not
effective for an attack intended on causing immediate
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DANIEL OF SERVICE. However, it is sufficient for an
attack that will last a long period of time. The jammer
barely has to transmit anything, the PSS jamming attack
offers roughly 20 dB of gain relative to the barrage
jamming attack. This results in an extremely efficient
jammer. This type of attack can be prevented by employing
a cell reselection implementation that is able to blacklist
corrupted synchronization signals by keeping track of the
time-delay in the cross correlation.
A)Basic Statistics to detect jamming attacks
Detecting jamming attacks is important because it
is the first step towards building a secure and dependable
wire- less network. It is challenging because jammers can
employ different models and often difficult to differentiate
a jamming scenario from legitimate scenarios. Specifically,
we need to differentiate a jamming scenario from various
network conditions: congestions that occur when the
aggregated traffic load exceeds the network capacity so that
the packet send ratio and delivery ratio are affected; the
interrupt of the communication due to failures at the sender
side, etc[8][5].
Signal Strength
One seemingly natural measurement that can be employed
to detect jamming is signal strength, or ambient energy.
The rationale behind using this measurement is that the
signal strength distribution may be affected by the presence
of a jammer. In practice, since most commodity radio
devices do not provide signal strength or noise level
measurements that are calibrated (even across devices from
the same manufacturer), it is necessary for each device to
employ its own empirically gathered statistics in order to
make its decisions. Each device should sample the noise
levels many times during a given time interval. By
gathering enough noise level measurements during a time
period prior to jamming, network devices can build a
statistical model describing normal energy levels in the
network. We now explore two basic strategies that employ
signal strength measurements for detecting a jamming
attack. The first approach uses either the average signal
value or the total signal energy over a window of N signal
strength measurements. This is a simple approach that
extracts a single statistic for basing a hypothesis test upon.
Since a single statistic loses most of the shape
characteristics of the time series, a second strategy would
seek to capture the shape of the time series by representing
its spectral behaviour. The second strategy that we discuss
uses N samples to extract spectral characteristics of the
signal strength for the basis of discrimination. In the
discussion below, we assume that we have measured the
channel's received energy levels s(t) at different times and
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collected N of these samples to form a window of samples
fs(k); s(k ¡ 1); s(k ¡ N + 1)g.
Basic Average and Energy Detection
We can extract two basic statistics from signal strength
readings, namely, the average signal strength and the
energy for detection. In both cases, the statistical
hypothesis testing problem is binary and essentially
involves deciding between signal absent and signal present
hypotheses. The use of the signal average arises naturally
when the jammer emits a constant amplitude signal. In this
case, the detection statistic is T(k) = ( Pk j=k¡N+1 s(j))=N.
The use of the signal energy arises when the jammer emits
a powerful noise-like signal, such as a white Gaussian
process. Here, the detection statistic is T(k) = ( Pk j=k¡N+1
s(j)2)=N. In either case, the detection decision is made by
comparing T(k) to a threshold ° that is suitably chosen by
considering tradeoffs between probability of detection and
false alarm, such as through application of NeymanPearson theorem.
In the existing approaches the methods based on
the cryptographic approaches[7] and applied on the layers,
for example application and network layer. In the previous
techniques symmetric cryptographic techniques are used.
In the next section we presented more securable techniques
for jamming attacks.
III. PACKET HIDING TECHNIQUES
In this first we present packet hiding technique
for jamming, we used key recovery technique for revealing
the secret key. Because random key is embedded in the
puzzle, if any attack on packet the random key will reveal,
leads to leakage of message. For any random seed
generation sender and receiver requests for service provider
only. Service provider is an authenticated server that
always monitors and helps secure communication between
the users.
In our method we use key exchanging protocol
and any key agreement method. For key exchanging
protocol we use diffie Hellman key exchanging algorithm.
In this first phase sender and receiver consider one random
challenge that is say ‘g’, and they consider another random
integer n, then sender generates one secret key then
generates public key. Receiver also follows same procedure
then the public keys exchange each other. Then using the
received public keys sender and receiver generates one
common key that is session key.
Initial step of this process is both Alice and Bob agree
upon a prime number and another number that has no
factor in common. Consider a prime number as p and the
other number as g and also g is also known as the
generator and p is known as prime modulus.
Then since eve is sitting in between and listening to this
communication so eve also gets to know p and g.
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1
Processing Time
After that modulus arithmetic says that r = (g x)
mod p. So r will always produce an integer between 0
and p.
The first trick here is that given x (with g and p known) ,
it is very easy to find r. But given r(with g and p known) it
is difficult to deduce x.
This is not that much of difficult work to crack but what
if the value of p is a very huge prime number? Well, if this
is the case then deducing x (if r is given) becomes almost
next to impossible as it would take thousands of years to
crack this even with supercomputers.
Coming back to the communication all the users such as
Bob, Alice and eve now know g and p.
Now, Alice selects a random private number xa and
calculates (g to the power xa) mod p =ra. This
resultant ra is sent to Bob through the communication
channel. Intercepting in between, eve also comes to
know ra.
Similarly Bob selects random private number xb,
calculates (g to the power xb) mod p = rb and sends
this rb to Alice through the same communication channel
and generally eve also comes to know about rb.
So
eve
came
to
know
the
information
about g, p, ra and rb.
Now comes the heart of this algorithm. Alice calculates
(rb to the power xa) mod p = Final key which is equivalent
to (g to the power (xa*xb) ) mod p .
Similarly Bob calculates (ra xb) mod p = Final key which
is again equivalent to (g to the power(xb * xa)) mod p.
Then Alice and Bob were able to calculate a
common Final key without sharing each other private
random number and eve sitting in between will not be able
to determine the Final key as the private numbers were
never transferred.
Following this key exchanging process sender encrypts and
generates signature using RSA and sends to receiver. Then
receiver decrypts the encrypted message then sends
acknowledgement to sender.
The generation process is not by individual , in
between them there is a mediator called service provider.
All the random challenges are done by authenticated
service provider only.
A) Key Recovery based hiding
In proposed system we introduced key recovery
process we are using exchanging and key agreement
protocol to exchange the message.
The processing time for existing methods is very
high for the large packets. We studied the previous
methods and as concerned with them the plotted the graph
and shown below:
Strong Hiding
0.5
Puzzle Hiding
Proposed
0
Packet Hiding Methods
IV.CONCLUSION
Our proposed work prevents jamming attacks efficiently
.The issue of detecting the presence of jamming attacks,
and examined the ability of different measurement statistics
to classify the presence of a jammer. We showed that by
using signal strength, carrier sensing time, or the packet
delivery ratio individually and it is one is not able to
definitively conclude the presence of a jammer. Most of the
attacks are mainly focus on the content and the keys used
to hide the data. So our process has no problem for loss of
keys. The content also very secure when transferring the
network.
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Sri. P.Suresh Babu, completed his
B.Tech,M.E. He is working as a Associate
Professor in Department Of Computer
Science & Engineering in Kaushik College
of Engineering, Visakhapatnam, Andhra
Pradesh. His Teaching Experience: 14 Years
Industrial Experience: 4 Years
[22] Alejandro Proan˜o and Loukas Lazos Packet-Hiding
Methods for Preventing Selective Jamming Attacks,2012.
BIOGRAPHIES
M.Kavitha completed her MCA, she
pursuing MTech in kaushik college of
engineering.Her Interested area of research is
network security.
Mr. A.V.D.N.Murthy completed M.C.A,
M.Tech. He is working as a Assistant
Professor in Department Of Computer
Science & Engineering in Kaushik College
of Engineering,Visakhapatnam, Andhra
Pradesh. His Teaching Experience: 6 Years
and Industrial Experience: 1.2 Years
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