Definition and Development of a Topology-Based Cryptographic Scheme for Wireless Sensor Networks

Marchesani, Stefano; Pomante, Luigi; Pugliese, Marco; Santucci, F.

doi:10.1007/978-3-319-04166-7_4

Cited by 14 publications

(15 citation statements)

References 9 publications

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“…Our method for sure is slower and less precise (since it is an approximation) than the Marsaglia's method, anyway it is a valid alternative for the cases where m varies over time, giving a good trade-off between precision computing speed. A possible application filed of the proposed algorithm is the filed of embedded systems and Wireless Sensor Networks (WSN) [20]- [21], where the aspect just mentioned has its importance.…”

Section: Discussionmentioning

confidence: 99%

“…It is possible to notice that the approximations obtained by the WH approach (20) and (21) are better than the Stirling formula (22). In particular, the higher-order WH approximation (21) is characterized by a relative error decreasing as α −2 , similarly to the approximation obtained including the first two terms of the Stirling series (23).…”

Section: Considerations On Wh-type Approximations For the Gamma Randomentioning

confidence: 96%

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Wilson-Hilferty-type approximation for Poisson Random Variable

Giammatteo¹,

Mascio²

2020

Adv. sci. technol. eng. syst. j.

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The possibility to apply non-linear transformation of the Wilson-Hilferty type to the Poisson random variable is investigated using an analytic approach, in order to improve the convergence towards the large-parameter Gaussian limit. Considering the already existing non-linear transformation for the Gamma distribution, the original Wilson-Hilferty and a higher-order transformations are showed and approximations for the Gamma function are illustrated. From this, an approximate algorithm which exploits standard Gaussian random numbers is established, in order to generate Poisson random numbers of any parameter m. The algorithm performance is also assessed. The convenience of this approximate approach it resides in the fact that simulations often could be computationally demanding so that optimized algorithms have to be adopted for the efficient extraction of Poisson random numbers with variable parameter m.

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Section: Discussionmentioning

confidence: 99%

Section: Considerations On Wh-type Approximations For the Gamma Randomentioning

confidence: 96%

Wilson-Hilferty-type approximation for Poisson Random Variable

Giammatteo¹,

Mascio²

2020

Adv. sci. technol. eng. syst. j.

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“…The paper shows how k‐means clustering and LLM may be coupled for the detection of DNS tunneling. Future work includes the evaluation of other cyber attacks, such as Denial of Service and malware in different contexts (eg, sensor networks). Preliminary results on the Kddcup data set show promising performance to overcome the high dimensionality of the space of features.…”

Section: Discussionmentioning

confidence: 99%

Unsupervised learning and rule extraction for Domain Name Server tunneling detection

Aiello

Mongelli

Muselli

et al. 2018

Internet Technology Letters

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The paper deals with k-means clustering and logic learning machine (LLM) for the detection of Domain Name Server (DNS) tunneling. As the LLM shows more versatility in rule generation and classification precision with respect to traditional decision trees, the approach reveals to be robust to a large set of system conditions. The detection algorithm is designed to be applied over streaming data, without accurate tuning of algorithms' parameters. An extensive performance evaluation is provided with respect to different tunneling tools and applications; silent intruders are considered. Results show robustness on a test set that exhibits a different behavior from training. KEYWORDS covert channel, rule extraction, unsupervised learning 1 Internet Technology Letters. 2019;2:e85.wileyonlinelibrary.com/journal/itl2

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“…Other schemes can be found in [5]. In [25], [29] and [30], we have proposed a family of novel schemes called TAKS (Topology Authenticated Key Scheme) to generate topology authenticated keys for handling cryptographic aspects in resource constrained deployments of WSN. TAKS cryptographic scheme allows to authenticate each message exchanged in the network referring to a certified topology of the network.…”

Section: Security In Ieee 802154 Networkmentioning

confidence: 99%

“…TAKS cryptographic scheme allows to authenticate each message exchanged in the network referring to a certified topology of the network. Since TAKS provides good results from both performance and security points of view [25], its usage in IEEE 802.15.4 networks is very encouraged. The complexity and distributed nature of a WSN makes cryptography not sufficient to ensure network security.…”

Section: Security In Ieee 802154 Networkmentioning

confidence: 99%

A Middleware Approach for IEEE 802.15.4 Wireless Sensor Networks Security

Marchesani¹,

Pomante²,

Pugliese³

et al. 2015

ICST Transactions on Ubiquitous Environments

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Recent years have seen the growth of interest for middleware (MW) approaches in resource-constrained systems like Wireless Sensor Networks (WSNs). In this context, available MW platforms usually provide an Application Layer with different basic services, but do not provide security services such as secure links management or intrusion detection. Nevertheless, since WSN applications normally require the collection of reliable data from the sensing units, secure communications should be guaranteed even in the presence of resource constraints. So, this paper present a novel MW approach directly tailored to an IEEE 802.15.4-based WSN. The security-related components of the proposed MW include a light yet powerful cryptographic scheme (TAKS) and an Intrusion Detection System (WIDS). According to the performance and overhead assessment, we may argue that the proposed architecture has potentials to be exploited in realistic application scenarios that rely on the IEEE 802.15.4.

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Definition and Development of a Topology-Based Cryptographic Scheme for Wireless Sensor Networks

Cited by 14 publications

References 9 publications

Wilson-Hilferty-type approximation for Poisson Random Variable

Wilson-Hilferty-type approximation for Poisson Random Variable

Unsupervised learning and rule extraction for Domain Name Server tunneling detection

A Middleware Approach for IEEE 802.15.4 Wireless Sensor Networks Security

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