An Introduction to MultiAgent Systems.

http://wpage.unina.it/valerio.persico/pubs/CloudIoT_FGCS.pdf

Integration of Cloud computing and Internet of Things

In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.

PORs: Proofs of Retrievability for Large Files

IoT security: Review, blockchain solutions, and open challenges

Review: Intrusion detection system: A comprehensive review

IoT is made up of heterogeneous networks which transport a huge volume of data packets over the Internet. Improper utilization of bandwidth or insufficient bandwidth allocation leads to faults such as packet loss, setting up routing path between source and destination, reduction of speed in data communication, etc. One of the vital causes of insufficient bandwidth is nonuniform growth in the number of Internet users in a specific region. In this paper, we propose a framework for efficient distribution of bandwidth over a region based on depth of field analysis and population statistics analysis. We propose to use existing Google Earth Pro APIs over satellite images to estimate possible number of users in a particular area and plan to allocate bandwidth accordingly. The proposed framework is aimed to reduce packet loss and distortion effects due to scattering and refraction.

ZoBe: Zone-Oriented Bandwidth Estimator for Efficient IoT Networks

Abstract In the design of autonomous systems, it is important to consider the preferences of the interested parties to improve the user experience. These preferences are often associated with the contexts in which each system is likely to operate. The operational behavior of a system must also meet various non-functional requirements (NFRs), which can present different levels of conflict depending on the operational context. This work aims to model correlations between the individual contexts and the consequent conflicts between NFRs. The proposed approach is based on analyzing the system event logs, tracing them back to the leaf elements at the specification level and providing a contextual explanation of the system’s behavior. The traced contexts and NFR conflicts are then mined to produce Context-Context and Context-NFR conflict sequential rules. The proposed Contextual Explainability (ConE) framework uses BERT-based pre-trained language models and sequential rule mining libraries for deriving the above correlations. Extensive evaluations are performed to compare the existing state-of-the-art approaches. The best-fit solutions are chosen to integrate within the ConE framework. Based on experiments, an accuracy of 80%, a precision of 90%, a recall of 97%, and an F1-score of 88% are recorded for the ConE framework on the sequential rules that were mined. 

/pdf/correlating-contexts-and-nfr-conflicts-from-event-logs-3cygy0df.pdf

Correlating contexts and NFR conflicts from event logs

Energy efficiency is the main challenge for wireless sensor networks. Power-aware schemes send the same data through multiple paths, which causes data redundancy and a huge amount of energy drainage within the network. Use of a head node for a cluster can be a better solution. The proposed algorithm creates several clusters, selects a cluster head, aggregates the data, and sends that to base station through other cluster heads. Simulation result shows that it helps to increase network longevity.

The Design of Hierarchical Routing Protocol for Wireless Sensor Network

Keystrokes dynamics has been used for quite sometimes in authentication of users. The technique has immense possibilities due to ease of implementation and un-obtrusive nature. Researchers have been working for attaining improved accuracy rate of user identification. Such techniques are validated using standard data-set. As it turns out, the quality of input data is very much important for generating an accurate use pattern vector. In this paper, an application for data collection has been presented. The application, besides creating a user data-set, also generates a signature vector database.

https://hal.inria.fr/hal-01637513/document

Rituparna Chaki

Papers

ZoBe: Zone-Oriented Bandwidth Estimator for Efficient IoT Networks

Correlating contexts and NFR conflicts from event logs

The Design of Hierarchical Routing Protocol for Wireless Sensor Network

Towards Generating a Unique Signature for Remote User by Keystrokes Dynamics

An Efficient Data Distribution Strategy for Distributed Graph Processing System