https://minerva-access.unimelb.edu.au/bitstream/handle/11343/197439/1207.0203v1.pdf

Internet of Things (IoT): A vision, architectural elements, and future directions

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

http://www.123seminarsonly.com/Seminar-Reports/015/53603449-zigbee.pdf

Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards

In this paper, we describe LEAP (Localized Encryption and Authentication Protocol), a key management protocol for sensor networks that is designed to support in-network processing, while at the same time restricting the security impact of a node compromise to the immediate network neighborhood of the compromised node. The design of the protocol is motivated by the observation that different types of messages exchanged between sensor nodes have different security requirements, and that a single keying mechanism is not suitable for meeting these different security requirements. LEAP supports the establishment of four types of keys for each sensor node -- an individual key shared with the base station, a pairwise key shared with another sensor node, a cluster key shared with multiple neighboring nodes, and a group key that is shared by all the nodes in the network. The protocol used for establishing and updating these keys is communication- and energy-efficient, and minimizes the involvement of the base station. LEAP also includes an efficient protocol for inter-node traffic authentication based on the use of one-way key chains. A salient feature of the authentication protocol is that it supports source authentication without precluding in-network processing and passive participation. We analyze the performance and the security of our scheme under various attack models and show our schemes are very efficient in defending against many attacks.

LEAP: efficient security mechanisms for large-scale distributed sensor networks

Internet of Things (IoT) is playing a more and more important role after its showing up, it covers from traditional equipment to general household objects such as WSNs and RFID. With the great potential of IoT, there come all kinds of challenges. This paper focuses on the security problems among all other challenges. As IoT is built on the basis of the Internet, security problems of the Internet will also show up in IoT. And as IoT contains three layers: perception layer, transportation layer and application layer, this paper will analyze the security problems of each layer separately and try to find new problems and solutions. This paper also analyzes the cross-layer heterogeneous integration issues and security issues in detail and discusses the security issues of IoT as a whole and tries to find solutions to them. In the end, this paper compares security issues between IoT and traditional network, and discusses opening security issues of IoT.

https://csi.dgist.ac.kr/uploads/Seminar/1407_IoT_SSH.pdf

Security of the Internet of Things: perspectives and challenges

In a large sensor network, in-network data aggregation significantly reduces the amount of communication and energy consumption. Recently, the research community has proposed a robust aggregation framework called synopsis diffusion which combines multipath routing schemes with duplicate-insensitive algorithms to accurately compute aggregates (e.g., predicate Count, Sum) in spite of message losses resulting from node and transmission failures. However, this aggregation framework does not address the problem of false subaggregate values contributed by compromised nodes resulting in large errors in the aggregate computed at the base station, which is the root node in the aggregation hierarchy. This is an important problem since sensor networks are highly vulnerable to node compromises due to the unattended nature of sensor nodes and the lack of tamper-resistant hardware. In this paper, we make the synopsis diffusion approach secure against attacks in which compromised nodes contribute false subaggregate values. In particular, we present a novel lightweight verification algorithm by which the base station can determine if the computed aggregate (predicate Count or Sum) includes any false contribution. Thorough theoretical analysis and extensive simulation study show that our algorithm outperforms other existing approaches. Irrespective of the network size, the per-node communication overhead in our algorithm is O(1).

/pdf/secure-data-aggregation-in-wireless-sensor-networks-4a520aeauc.pdf

Secure Data Aggregation in Wireless Sensor Networks

Most ad hoc networks do not implement any network access control, leaving these networks vulnerable to resource consumption attacks where a malicious node injects packets into the network with the goal of depleting the resources Of the nodes relaying the packets. To thwart or prevent such attacks, it is necessary to employ authentication mechanisms that ensure that only authorized nodes can inject traffic into the network. In this paper we present LHAP a scalable and light-weight authentication protocol for ad hoc networks. LHAP is based on two techniques: (i) hop-by-hop authentication for verifying the authenticity of all the packets transmitted in the network and (ii) one-way key chain and TESLA for packet authentication and for reducing the overhead for establishing trust among nodes. We analyze the security of LHAP and show LHAP is a lightweight security protocol through detailed performance analysis.

LHAP: a lightweight hop-by-hop authentication protocol for ad-hoc networks

Wireless sensor nodes lack hardware support for tamper- resistance and are often deployed in unattended environments, thus leaving them vulnerable to capture and compromise by an adversary. In a node replication attack, an adversary uses the credentials of a compromised node to surreptitiously introduce replicas of that node into the network. These replicas are then used to launch a variety of attacks that subvert the goal of the sensor application, and the operation of the underlying protocols. We present a novel distributed approach called Localized Multicast for detecting node replication attacks. We evaluate the performance and security of our approach both theoretically and via simulation. Our results show that Localized Multicast is more efficient than previous distributed approaches in terms of communication and memory costs. Further, in our approach, the probability of detecting node replicas is much higher than that achieved in previous distributed protocols.

/pdf/efficient-distributed-detection-of-node-replication-attacks-4dcgrjgsw1.pdf

Efficient Distributed Detection of Node Replication Attacks in Sensor Networks

In this paper, we examine the availability and utility of idle memory in workstation clusters. We attempt to answer the following questions. First, how much of the total memory in a workstation cluster can be expected to be idle? This provides an estimate of the opportunity for hosting guest data. Second, how much memory can be expected to be idle on individual workstations? This helps determine the recruitment policy – how much memory should be recruited on individual hosts? Third, what is the distribution of memory idle-times? This indicates how long guest data can be expected to survive; applications that access their data-sets frequently within the expected life-time of guest data are more likely to benefit from exploiting idle memory. Fourth, how much performance improvement can be achieved for off-the-shelf clusters without customizing the operating system and/or the processor firmware? Finally, how long and how frequently might a user have to wait to reclaim her machine if she volunteers to host guest pages on her machine? This helps answer the question of social acceptability. To answer the questions relating to the availability of idle memory, we have analyzed two-week long traces from two workstation pools with different sizes, locations, and patterns of use. To evaluate the expected benefits and costs, we have simulated five data-intensive applications (0.5 GB-5 GB) on these workstation pools.

/pdf/availability-and-utility-of-idle-memory-in-workstation-5ezvg3rblb.pdf

Availability and utility of idle memory in workstation clusters

Wireless sensor networks (WSNs) are increasingly used in many applications, such as volcano and fire monitoring, urban sensing, and perimeter surveillance. In a large WSN, in-network data aggregation (i.e., combining partial results at intermediate nodes during message routing) significantly reduces the amount of communication overhead and energy consumption. The research community proposed a loss-resilient aggregation framework called synopsis diffusion, which uses duplicate-insensitive algorithms on top of multipath routing schemes to accurately compute aggregates (e.g., predicate count or sum). However, this aggregation framework does not address the problem of false subaggregate values contributed by compromised nodes. This attack may cause large errors in the aggregate computed at the base station, which is the root node in the aggregation hierarchy. In this paper, we make the synopsis diffusion approach secure against the above attack launched by compromised nodes. In particular, we present an algorithm to enable the base station to securely compute predicate count or sum even in the presence of such an attack. Our attack-resilient computation algorithm computes the true aggregate by filtering out the contributions of compromised nodes in the aggregation hierarchy. Extensive analysis and simulation study show that our algorithm outperforms other existing approaches.

Sanjeev Setia

Papers

Secure Data Aggregation in Wireless Sensor Networks

LHAP: a lightweight hop-by-hop authentication protocol for ad-hoc networks

Efficient Distributed Detection of Node Replication Attacks in Sensor Networks

Availability and utility of idle memory in workstation clusters

Secure Data Aggregation in Wireless Sensor Networks: Filtering out the Attacker's Impact