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Kishore Angrishi

Publications and source records attributed to Kishore Angrishi.

5 recordsLinked to original sources

Turning Internet of Things(IoT) into Internet of Vulnerabilities (IoV) : IoT Botnets

Internet of Things (IoT) is the next big evolutionary step in the world of internet. The main intention behind the IoT is to enable safer living and risk mitigation on different levels of life. With the advent of IoT botnets, the view towards IoT devices has changed from enabler of enhanced living into Internet of vulnerabilities for cyber criminals. IoT botnets has exposed two different glaring issues, 1) A large number of IoT devices are accessible over public Internet. 2) Security (if considered at all) is often an afterthought in the architecture of many wide spread IoT devices. In this article, we briefly outline the anatomy of the IoT botnets and their basic mode of operations. Some of the major DDoS incidents using IoT botnets in recent times along with the corresponding exploited vulnerabilities will be discussed. We also provide remedies and recommendations to mitigate IoT related cyber risks and briefly illustrate the importance of cyber insurance in the modern connected world.

cs.NI

A Simple Proof of Linear Scaling of End-to-End Probabilistic Bounds using Network Calculus

Statistical network calculus is the probabilistic extension of network calculus, which uses a simple envelope approach to describe arrival traffic and service available for the arrival traffic in a node. One of the key features of network calculus is the possibility to describe the service available in a network using a network service envelope constructed from the service envelopes of the individual nodes constituting the network. It have been shown that the end-to-end worst case performance measures computed using the network service envelope is bounded by $ {\cal O} (H) $, where $H$ is the number of nodes traversed by a flow. There have been many attempts to achieve a similar linear scaling for end-to-end probabilistic performance measures but with limited success. In this paper, we present a simple general proof of computing end-to-end probabilistic performance measures using network calculus that grow linearly in the number of nodes ($H$).

cs.NI

An Approach using Demisubmartingales for the Stochastic Analysis of Networks

Stochastic network calculus is the probabilistic version of the network calculus, which uses envelopes to perform probabilistic analysis of queueing networks. The accuracy of probabilistic end-to-end delay or backlog bounds computed using network calculus has always been a concern. In this paper, we propose novel end-to-end probabilistic bounds based on demisubmartingale inequalities which improve the existing bounds for the tandem networks of GI/GI/1 queues. In particular, we show that reasonably accurate bounds are achieved by comparing the new bounds with the existing results for a network of M/M/1 queues.

cs.NI

An End-to-End Stochastic Network Calculus with Effective Bandwidth and Effective Capacity

Network calculus is an elegant theory which uses envelopes to determine the worst-case performance bounds in a network. Statistical network calculus is the probabilistic version of network calculus, which strives to retain the simplicity of envelope approach from network calculus and use the arguments of statistical multiplexing to determine probabilistic performance bounds in a network. The tightness of the determined probabilistic bounds depends on the efficiency of modelling stochastic properties of the arrival traffic and the service available to the traffic at a network node. The notion of effective bandwidth from large deviations theory is a well known statistical descriptor of arrival traffic. Similarly, the notion of effective capacity summarizes the time varying resource availability to the arrival traffic at a network node. The main contribution of this paper is to establish an end-to-end stochastic network calculus with the notions of effective bandwidth and effective capacity which provides efficient end-to-end delay and backlog bounds that grows linearly in the number of nodes ($H$) traversed by the arrival traffic, under the assumption of independence.

cs.NI

Probabilistic Performance Analysis of Networks using an Improved Network Service Envelope Approach

Stochastic network calculus is an evolving theory which accounts for statistical multiplexing and uses an envelope approach for probabilistic delay and backlog analysis of networks. One of the key ideas of stochastic network calculus is the possibility to describe service offered at network node as a stochastic service envelope, which in turn can be used to describe the stochastic service available in a network of nodes and determine end-to-end probabilistic delay and backlog bounds. This paper introduces a new definition of stochastic service envelopes which yield a simple network service envelope and tighter end-to-end performance bounds. It is shown for ($σ(θ), ρ(θ)$) - constrained traffic model that the end-to-end performance measures computed using the new stochastic network service envelope are tight in comparison to the ones obtained using the existing start-of-the-art definition of statistical network service envelope and are bounded by ${\cal O}(H \log{H})$, where $H$ is the number of nodes traversed by the arrival traffic.

cs.NI