45,690 research outputs found
Intelligent intrusion detection in low power IoTs
Security and privacy of data are one of the prime concerns in today’s Internet of Things (IoT). Conventional security techniques like signature-based detection of malware and regular updates of a signature database are not feasible solutions as they cannot secure such systems effectively, having limited resources. Programming languages permitting immediate memory accesses through pointers often result in applications having memory-related errors, which may lead to unpredictable failures and security vulnerabilities. Furthermore, energy efficient IoT devices running on batteries cannot afford the implementation of cryptography algorithms as such techniques have significant impact on the system power consumption. Therefore, in order to operate IoT in a secure manner, the system must be able to detect and prevent any kind of intrusions before the network (i.e., sensor nodes and base station) is destabilised by the attackers. In this article, we have presented an intrusion detection and prevention mechanism by implementing an intelligent security architecture using random neural networks (RNNs). The application’s source code is also instrumented at compile time in order to detect out-of-bound memory accesses. It is based on creating tags, to be coupled with each memory allocation and then placing additional tag checking instructions for each access made to the memory. To validate the feasibility of the proposed security solution, it is implemented for an existing IoT system and its functionality is practically demonstrated by successfully detecting the presence of any suspicious sensor node within the system operating range and anomalous activity in the base station with an accuracy of 97.23%. Overall, the proposed security solution has presented a minimal performance overhead.</jats:p
Information Cost Tradeoffs for Augmented Index and Streaming Language Recognition
This paper makes three main contributions to the theory of communication
complexity and stream computation. First, we present new bounds on the
information complexity of AUGMENTED-INDEX. In contrast to analogous results for
INDEX by Jain, Radhakrishnan and Sen [J. ACM, 2009], we have to overcome the
significant technical challenge that protocols for AUGMENTED-INDEX may violate
the "rectangle property" due to the inherent input sharing. Second, we use
these bounds to resolve an open problem of Magniez, Mathieu and Nayak [STOC,
2010] that asked about the multi-pass complexity of recognizing Dyck languages.
This results in a natural separation between the standard multi-pass model and
the multi-pass model that permits reverse passes. Third, we present the first
passive memory checkers that verify the interaction transcripts of priority
queues, stacks, and double-ended queues. We obtain tight upper and lower bounds
for these problems, thereby addressing an important sub-class of the memory
checking framework of Blum et al. [Algorithmica, 1994]
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures
We introduce BriskStream, an in-memory data stream processing system (DSPSs)
specifically designed for modern shared-memory multicore architectures.
BriskStream's key contribution is an execution plan optimization paradigm,
namely RLAS, which takes relative-location (i.e., NUMA distance) of each pair
of producer-consumer operators into consideration. We propose a branch and
bound based approach with three heuristics to resolve the resulting nontrivial
optimization problem. The experimental evaluations demonstrate that BriskStream
yields much higher throughput and better scalability than existing DSPSs on
multi-core architectures when processing different types of workloads.Comment: To appear in SIGMOD'1
Effective Monte Carlo simulation on System-V massively parallel associative string processing architecture
We show that the latest version of massively parallel processing associative
string processing architecture (System-V) is applicable for fast Monte Carlo
simulation if an effective on-processor random number generator is implemented.
Our lagged Fibonacci generator can produce random numbers on a processor
string of 12K PE-s. The time dependent Monte Carlo algorithm of the
one-dimensional non-equilibrium kinetic Ising model performs 80 faster than the
corresponding serial algorithm on a 300 MHz UltraSparc.Comment: 8 pages, 9 color ps figures embedde
Application Protocols enabling Internet of Remote Things via Random Access Satellite Channels
Nowadays, Machine-to-Machine (M2M) and Internet of Things (IoT) traffic rate
is increasing at a fast pace. The use of satellites is expected to play a large
role in delivering such a traffic. In this work, we investigate the use of two
of the most common M2M/IoT protocols stacks on a satellite Random Access (RA)
channel, based on DVB-RCS2 standard. The metric under consideration is the
completion time, in order to identify the protocol stack that can provide the
best performance level
A cross-layer approach to enhance QoS for multimedia applications over satellite
The need for on-demand QoS support for communications over satellite is of primary importance for distributed multimedia applications. This is particularly true for the return link which is often a bottleneck due to the large set of end-users accessing a very limited uplink resource. Facing this need, Demand Assignment Multiple Access (DAMA) is a classical technique that allows satellite operators to offer various types of services, while managing the resources of the satellite system efficiently. Tackling the quality degradation and delay accumulation issues that can result from the use of these techniques, this paper proposes an instantiation of the Application Layer Framing (ALF) approach, using a cross-layer interpreter(xQoS-Interpreter). The information provided by this interpreter is used to manage the resource provided to a terminal by the satellite system in order to improve the quality of multimedia presentations from the end users point of view. Several experiments are carried out for different loads on the return link. Their impact on QoS is measured through different application as well as network level metrics
Performance Comparison of Dual Connectivity and Hard Handover for LTE-5G Tight Integration in mmWave Cellular Networks
MmWave communications are expected to play a major role in the Fifth
generation of mobile networks. They offer a potential multi-gigabit throughput
and an ultra-low radio latency, but at the same time suffer from high isotropic
pathloss, and a coverage area much smaller than the one of LTE macrocells. In
order to address these issues, highly directional beamforming and a very
high-density deployment of mmWave base stations were proposed. This Thesis aims
to improve the reliability and performance of the 5G network by studying its
tight and seamless integration with the current LTE cellular network. In
particular, the LTE base stations can provide a coverage layer for 5G mobile
terminals, because they operate on microWave frequencies, which are less
sensitive to blockage and have a lower pathloss. This document is a copy of the
Master's Thesis carried out by Mr. Michele Polese under the supervision of Dr.
Marco Mezzavilla and Prof. Michele Zorzi. It will propose an LTE-5G tight
integration architecture, based on mobile terminals' dual connectivity to LTE
and 5G radio access networks, and will evaluate which are the new network
procedures that will be needed to support it. Moreover, this new architecture
will be implemented in the ns-3 simulator, and a thorough simulation campaign
will be conducted in order to evaluate its performance, with respect to the
baseline of handover between LTE and 5G.Comment: Master's Thesis carried out by Mr. Michele Polese under the
supervision of Dr. Marco Mezzavilla and Prof. Michele Zorz
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