An Intelligent Technique to Detect Jamming Attack in Wireless Sensor Networks (WSNs)

Sasikala, E.; Rengarajan, N.

doi:10.1007/s40815-015-0009-4

Cited by 36 publications

(13 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Effective design and implementation of bct algorithms can provide suitable outcomes for problems with conflicting objectives, while involving light computational loads. bcts gained popularity in networking due to their ease of implementation and effectiveness to solve multi-objective and often intractable optimization problems, including manet topology control [50], routing [13,20], node collaboration [36] and cybersecurity [25].…”

Section: Bio-inspired Computation For Swarms and Uavsmentioning

confidence: 99%

“…These desirable characteristics of manets at the same time bring new challenges for providing autonomous flight control of uavs operating as a swarm, including an increased level of topology control and cyber security. 1 Bio-inspired computation techniques are excellent candidates to bring effective solutions for manet topology control [50], routing [20], node collaboration [36] and cybersecurity mechanisms [25]. These techniques can find desired optimum or near optimum solutions to satisfy conflicting objectives in prohibitively large domains.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Artificial intelligence and game theory controlled autonomous UAV swarms

Kusyk

Samoylov

et al. 2020

Evol. Intel.

View full text Add to dashboard Cite

Autonomous unmanned aerial vehicles (uavs) operating as a swarm can be deployed in austere environments, where cyber electromagnetic activities often require speedy and dynamic adjustments to swarm operations. Use of central controllers, uav synchronization mechanisms or pre-planned set of actions to control a swarm in such deployments would hinder its ability to deliver expected services. We introduce artificial intelligence and game theory based flight control algorithms to be run by each autonomous uav to determine its actions in near real-time, while relying only on local spatial, temporal and electromagnetic (em) information. Each uav using our flight control algorithms positions itself such that the swarm maintains mobile ad-hoc network (manet) connectivity and uniform asset distribution over an area of interest. Typical tasks for swarms using our algorithms include detection, localization and tracking of mobile em transmitters. We present a formal analysis showing that our algorithms can guide a swarm to maintain a connected manet, promote a uniform network spreading, while avoiding overcrowding with other swarm members. We also prove that they maintain manet connectivity and, at the same time, they can lead a swarm of autonomous uavs to follow or avoid an em transmitter. Simulation experiments in opnet modeler verify the results of formal analysis that our algorithms are capable of providing an adequate area coverage over a mobile em source and maintain manet connectivity. These algorithms are good candidates for civilian and military applications that require agile responses to the changes in dynamic environments for tasks such as detection, localization and tracking mobile em transmitters.

show abstract

Section: Bio-inspired Computation For Swarms and Uavsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Artificial intelligence and game theory controlled autonomous UAV swarms

Kusyk

Samoylov

et al. 2020

Evol. Intel.

View full text Add to dashboard Cite

show abstract

“…The authors of [25,26] considered the increase of the Euclidean distance (proportional to hop counts) between a source node and a destination node to detect the jamming attack. Before the detection of jamming attack, a source node has discovered multiple paths to the same destination node and obtained the shortest path for data packet transmission by computing and comparing the distance of these discovered paths.…”

Section: Detection Mechanisms Against Jamming Attackmentioning

confidence: 99%

Data collection for attack detection and security measurement in Mobile Ad Hoc Networks: A survey

Liu

Yan

Pedrycz

2018

Journal of Network and Computer Applications

View full text Add to dashboard Cite

Mobile Ad Hoc Network (MANET) is becoming one type of major next generation wireless networks. Nevertheless, it easily suffers from various attacks due to its specific characteristics. In order to evaluate and measure the security of MANET in real time and make this network react accordingly, a promising alternative is to integrate detection mechanisms that play a role of the second line of defense to detect attacks in MANETs. We note that in most attack detection mechanisms, it is essential and crucial to collect the data related to security for further analysis. If security-related data collection is untrustworthy, attack detection and security measurement might be impacted and disabled. Unfortunately, few existing studies concern security-related data collection in attack detection for the purpose of trustworthy security measurement. The literature lacks a thorough survey on security-related data collection for attack detection and security measurement in MANETs. In this paper, we propose a number of requirements for trustworthy security-related data collection, and then review detection mechanisms in MANETs that were published in recent 20 years. In particular, we employ the proposed requirements as a set of criteria to evaluate the existing work about security-related data collection. Based on the survey and evaluation, we identify a number of open issues and point out future research directions.

show abstract

“…Although it is not within the scope of this article, it is worth mentioning that the sensors in WSNs due to their wireless communication capabilities are also vulnerable to disruptions of the radio channel. For instance, a DoS jamming attack can be easily executed by an adversary with a low-cost hardware, and ad hoc solutions, such as those presented in [11,12] or [13], are needed for its detection.…”

Section: Introductionmentioning

confidence: 99%

ECG-RNG: A Random Number Generator Based on ECG Signals and Suitable for Securing Wireless Sensor Networks

Cámara

Peris-López

Martín

et al. 2018

Sensors

View full text Add to dashboard Cite

Wireless Sensor Networks (WSNs) are a promising technology with applications in many areas such as environment monitoring, agriculture, the military field or health-care, to name but a few. Unfortunately, the wireless connectivity of the sensors opens doors to many security threats, and therefore, cryptographic solutions must be included on-board these devices and preferably in their design phase. In this vein, Random Number Generators (RNGs) play a critical role in security solutions such as authentication protocols or key-generation algorithms. In this article is proposed an avant-garde proposal based on the cardiac signal generator we carry with us (our heart), which can be recorded with medical or even low-cost sensors with wireless connectivity. In particular, for the extraction of random bits, a multi-level decomposition has been performed by wavelet analysis. The proposal has been tested with one of the largest and most publicly available datasets of electrocardiogram signals (202 subjects and 24 h of recording time). Regarding the assessment, the proposed True Random Number Generator (TRNG) has been tested with the most demanding batteries of statistical tests (ENT, DIEHARDERand NIST), and this has been completed with a bias, distinctiveness and performance analysis. From the analysis conducted, it can be concluded that the output stream of our proposed TRNG behaves as a random variable and is suitable for securing WSNs.

show abstract

An Intelligent Technique to Detect Jamming Attack in Wireless Sensor Networks (WSNs)

Cited by 36 publications

References 13 publications

Artificial intelligence and game theory controlled autonomous UAV swarms

Artificial intelligence and game theory controlled autonomous UAV swarms

Data collection for attack detection and security measurement in Mobile Ad Hoc Networks: A survey

ECG-RNG: A Random Number Generator Based on ECG Signals and Suitable for Securing Wireless Sensor Networks

Contact Info

Product

Resources

About