Cryptographic Puzzles Based Data Transmission and Detecting

Jamming Attacks in Wireless Networks

M. Dharani and S. Narmadha

Department of Computer Science, Karpagam Academy of Higher Education, Coimbatore, India

Keywords: Wireless Network, Puzzle Gaming Technique, Data Hiding Mechanism, Cryptographic Techniques.

Abstract: When nodes in wireless networks compete for access to a single wireless medium, collisions frequently occur.

Having the destination node combine inter-nodes for data transfer when using cooperative wireless

communications increases immunity to interference. One of the primary methods used to compromise the

wireless environment is jamming. By blocking off providers to authorized customers, while true visitors are

slowed down by means of the giant quantities of unlawful traffic, it operates. By randomly delivering

unauthenticated packets to each network wireless station, the attacker can quickly compromise the network.

Because wireless networks rely on shared media, it is simple for adversaries to conduct denial-of-service and

jamming assaults. Using the following approaches, the jamming and denial-of-service attacks in our proposed

work can be easily detected, and network performance can be enhanced. We provide a data-hiding mechanism

and puzzle-gaming technique that aid in determining whether inter-nodes are jammed or not. In network

transactions, cryptographic methods and data concealment are strengthened to ensure the transaction's

security. The methodology can improve network throughput and server processing overhead while ensuring

secure transactions.

1 INTRODUCTION

To connect participating nodes, wireless networks

rely on the wireless medium's continuous availability.

However, this medium is susceptible to various

security threats because of its open nature.

vulnerabilities. Wireless signals can be intercepted,

fraudulent messages injected, and legitimate

messages jammed by anybody possessing a

transceiver. While cryptographic measures can

prevent message injection and eavesdropping,

jamming attacks are far more difficult to prevent.

They have been shown to be capable of carrying out

major Attacks on wireless networks that cause a

denial of service (Alejandro and Loukas 2022). In the

most basic jamming technique, the attacker sends a

continuous jamming signal or a series of brief

jamming pulses to disrupt message reception.

Jamming attacks are frequently examined using a

jammer is not a part of the network in an external

threat model. jamming techniques, according to this

paradigm, consist of transmitting high-power

interference signals constantly or at random.

Adopting a "always-on" technique, on the other hand,

Assistant Professor

offers a number of disadvantages. The adversary must

first spend a lot of energy jamming the appropriate

frequency ranges. Second, because of the persistent

existence of extremely high interference magnitudes

(Alejandro and Loukas, 2022) this kind of assault is

easy to detect. Ad hoc networks are expected to

considerably improve military, industrial, and utility

communications that are essential to their missions.

To stop part or all victim communication, an

adversary may try to target a victim's ad hoc network.

In ad hoc wireless networks, Multiple degrees of

research have been done on such denial-of-service

(DoS) attacks (Brown 2006). DoS attacks where the

attackers are users of the target ad hoc network have

been studied by several researchers. Ad hoc networks

are especially vulnerable to peer-based assaults since

they rely on peer node cooperation to function. We

examine encrypted victim networks in this study,

where the attacker cannot directly affect any victim

communication because headers and payload of the

entire packet included—is encrypted. In this

circumstance, the offender must deploy jamming, a

type of external physical layer-based DoS (Brown,

2006).

216

Dharani, M. and Narmadha, S.

Cryptographic Puzzles Based Data Transmission and Detecting Jamming Attacks in Wireless Networks.

DOI: 10.5220/0012611400003739

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Artiﬁcial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics (AI4IoT 2023), pages 216-220

ISBN: 978-989-758-661-3

Figure 1: System Architecture.

2 RELATED WORK

2.1 Encrypted Wireless Ad Hoc

Network Jamming and Sensing

The challenge of an attacker jamming a wi-fi ad hoc

community of an encrypted sufferer is examined in

this paper. When dissecting jamming into its

component parts, this article focuses on the layer of

the transport/network (Brown 2006). A layer that is

clogged, which takes advantage of the When AODV

and TCP can identify the victim packet types, they

have been demonstrated to be quite effective in both

simulated and real networks. However, it is

anticipated that encryption will hide the complete

header and package content, leaving the attacker with

only the capacity to detect packet size, timing, and

sequence. The development and testing of a sensor

using real-time data. The designation has been proven

to be quite dependable for a variety of unusual packet

types. The implications for improving community

safety are investigated in conjunction with the

proportionate contributions of size, time, and

sequencing.

2.2 Methods for Hiding Packets to

Prevent

The Wi-Fi medium's openness makes it inclined to

deliberate interference attacks, occasionally

acknowledged as jamming. This deliberate disruption

of Wi-Fi communications can be exploited as a

springboard for Denial-of-Service assaults in

opposition to Wi-Fi networks. Jamming has

frequently been dealt with the usage of an exterior

hazard model. Nevertheless, attackers that are privy

to network and protocol specifications can carry out

low-effort jamming attacks that are challenging to

find and defend against. That is research (Alejandro

and Loukas 2022) we investigate the topic of

concentrated attacks on WiFi networks that jam

traffic. In these assaults, the enemy selectively targets

high-value messages while being active for a brief

period of time. We demonstrate the advantages of

selective jamming in terms of community

performance degradation and adversary effort by

offering two case studies, one on TCP and one on

routing (Alejandro and Loukas 2022). We show that

physical layer classification of packets in real-time

enables the launch of targeted jamming assaults. To

address We create three methods that combine

physical-layer cryptography with cryptographic

primitives to defend against these assaults.

characteristics. We test the computational and verbal

exchange price of our techniques and monitor their

security (Alejandro and Loukas 2022).

Cryptographic Puzzles Based Data Transmission and Detecting Jamming Attacks in Wireless Networks

217

Figure 2: Destination Node.

Figure 3: Solves the challenge and transmits information to the target.

2.3 Attacks on Control-Channel

Jamming in Multi-Channel Ad Hoc

Networks Mitigation

In multi-channel ad hoc networks, the issue of

control-channel jamming assaults is covered. As

opposed to the conventional viewpoint, which

considers We think of jammer assaults as a physical-

layer weakness and a modern adversary who takes

use of their understanding of protocol mechanics as

well as cryptographic portions extrapolated from

infected nodes in order to increase the impact of his

attack on higher-layer features (Liu et al 2007, Merkle

1978). We suggest fresh security metrics that gauge

an adversary's capacity to prevent entrance to the

manipulated channel as well as the total amount of

time required to re-establish the manipulated channel.

Additionally, we suggest a distributed, randomised

device that permits frequency hopping by nodes to

create extra control channels (Liu et al 2007). Our

strategy minimizes the outcomes of node compromise

due to the fact no two nodes use the identical hopping

AI4IoT 2023 - First International Conference on Artiﬁcial Intelligence for Internet of things (AI4IOT): Accelerating Innovation in Industry

and Consumer Electronics

218

Figure 4: Server- An example of a server sending a packet across an inter node.

Figure 5: Average route discovery time (non-congested network).

sequence, making it a traditional type of frequency

hopping. A compromised node is additionally

recognized in my opinion through its hop sequence,

which isolates it from any upcoming know-how about

the manipulate channel's frequency role (Liu et al

2007).

3 PROBLEM DEFINITION

To connect participating nodes, wireless networks

rely on the wireless medium's continuous availability.

However, this medium is susceptible to various

security threats because of its open nature.

vulnerabilities. Wireless signals can be intercepted,

fraudulent messages injected, and legitimate

messages jammed by anybody possessing a

transceiver. Cryptographic techniques can be

employed to prevent message injection and

eavesdropping, but jamming attacks are much more

difficult to prevent (Alejandro and Loukas 2022).

They have been shown to be capable of carrying out

major Attacks on wireless networks that cause a

denial of service. The adversary sends a continuous

jamming signal or a series of brief jamming pulses to

obstruct message reception in the most basic

jamming. Jamming assaults are regularly analyzed

the usage of an exterior chance mannequin the place

the jammer is no longer a element of the network.

This mannequin consists of the transmission of high-

power interference indicators always or at random as

one of the jamming techniques. Adopting a "always-

on" strategy, however, has a number of drawbacks.

The enemy must first use a large energy required to

jam the appropriate frequency ranges. Second, this

kind of attack is simple to spot due to the persistent

presence of exceptionally high interference levels.

4 PROPOSED MODEL

In this study, the issue of jamming is addressed using

the internal threat model. We take into account a

educated opponent who is conscious of community

Cryptographic Puzzles Based Data Transmission and Detecting Jamming Attacks in Wireless Networks

219

secrets and techniques and the specifics of how

community protocols are applied at any layer in the

community stack. In order to launch selective

jamming assaults that target only particular

communications of "high value," the enemy uses his

insider information. A jammer may, for example,

target TCP acknowledgments to severely limit an

end-to-end flow's throughput or Routing layer route-

request/route-reply messages to thwart route

discovery. The enemy must be able to deploy specific

jamming attacks in order to able to execute a

"classify-then-jam" technique prior to the end of an

electronic gearbox. Such a technique can put into

practice by decoding packets as they are sent or by

utilizing protocol semantics to categories transmitted

packets. Selective jamming necessitates a thorough

understanding both the specifics of the physical

(PHY) layer and those of higher levels. We created

three strategies that, by obstructing real-time packet

classification, turn an intentional jammer becomes an

accidental one. Our structures combine physical-layer

houses with cryptographic primitives like dedication

schemes, cryptographic riddles, and transformations

that are all-or-nothing (Alejandro and Loukas 2022).

In the first series of experiments, we used a

multihop route to connect a client and a server for a

single file transfer. The client asked the server for a

5KB file. We measured the actual throughput of the

TCP connection in the following situations to

investigate the impacts of packet concealment: There

is no message encryption or packet concealment

(N.H. (M.E.), transmission time (T.T.), and file

transfer (F.T.). Because there is no cross-traffic, the

relatively little communication justifies the overhead

of each concealing technique as well as the minimal

queuing delay at intermediate routers. Cryptographic

challenges are sometimes exploited in hiding

methods. Figure.2 shows a destination node that

receives the file via inter-node communication from

the server and that node that solves the puzzle

5 CONCLUSIONS

In wireless networks, the issue of targeted jamming

assaults has been solved. Because the jammer is a

member of the community being attacked, it is

informed of the protocol requirements and shared

community secrets and practices. This is a paradigm

of internal opponents. We proved the jammer's

capability categorize sent real-time packets by

deciphering the initial scant signs of a continuous

transmission. We investigated how targeted Jamming

attacks had an impact on routing and TCP, among

other network protocols. (Alejandro and Loukas

2022). Our research demonstrates that a specific

jammer can have a significant detrimental impact on

performance with little effort. We devised three ways

for converting a targeted jammer into an arbitrary one

by impeding instant packet categorization. Physical-

layer features are mixed with cryptographic

fundamentals like all-or-nothing transformations,

cryptographic riddles, and commitment schemes in

our systems. We assessed the safety of our techniques

and calculated the overhead for computation and

communication.

REFERENCES

T. X. Brown, J. E. James, and A. Sethi, “Jamming and

Sensing of Encrypted Wireless Ad Hoc Networks,”

Proc. ACM Int’l Symp. Mobile Ad Hoc Networking

and Computing (MobiHoc), pp. 120-130, 2006.

Alejandro Proan˜o and Loukas Lazos “Packet-Hiding

Methods for Preventing Selective Jamming Attacks”

IEEE transactions on dependable and secure

computing, vol. 9, no. 1, january/february 2022.

L. Lazos, S. Liu, and M. Krunz, “Mitigating Control-

Channel Jamming Attacks in Multi-Channel Ad Hoc

Networks,” Proc. Second ACM Conf. Wireless

Network Security, pp. 169-180, 2009.

X. Liu, G. Noubir, and R. Sundaram, “Spread: Foiling

Smart Jammers Using Multi-Layer Agility,” Proc.

IEEE INFOCOM, pp. 2536-2540, 2007.

Y. Liu, P. Ning, H. Dai, and A. Liu, “Randomized

Differential DSSS: Jamming-Resistant Wireless

Broadcast Communication,” Proc. IEEE INFOCOM,

2010.

R. C. Merkle, “Secure Communications over Insecure

Channels,” Comm. ACM, vol. 21, no. 4, pp. 294-299,

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and Consumer Electronics

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