Appearing in 1st IEEE International Workshop on Sensor Net Protocols and Applications (SNPA). Anchorage, Alaska, USA. May 11, 2003. RMST: Reliable Data Transport in Sensor Networks Fred Stann, John Heidemann Abstract – Reliable data transport in wireless sensor networks is a multifaceted problem influenced by the physical, MAC, network, and transport layers. Because sensor networks are subject to strict resource constraints and are deployed by single organizations, they encourage revisiting traditional layering and are less bound by standardized placement of services such as reliability. This paper presents analysis and experiments resulting in specific recommendations for implementing reliable data transport in sensor nets. To explore reliability at the transport layer, we present RMST (Reliable Multi- Segment Transport), a new transport layer for Directed Diffusion. RMST provides guaranteed delivery and fragmentation/reassembly for applications that require them. RMST is a selective NACK-based protocol that can be configured for in-network caching and repair. Second, these energy constraints, plus relatively low wireless bandwidths, make in-network processing both feasible and desirable [3]. Third, because nodes in sensor networks are usually collaborating towards a common task, rather than representing independent users, optimization of the shared network focuses on throughput rather than fairness. Finally, because sensor networks are often deployed by a single organization with inexpensive hardware, there is less need for interoperability with existing standards. For all of these reasons, sensor networks provide an environment that encourages rethinking the structure of traditional communications protocols. The main contribution is an evaluation of the placement of reliability for data transport at different levels of the protocol stack. We consider implementing reliability in the MAC, transport layer, application, and combinations of these. We conclude that reliability is important at the MAC layer and the transport layer. MAC-level reliability is important not just to provide hop-by-hop error recovery for the transport layer, but also because it is needed for route discovery and maintenance. (This conclusion differs from previous studies in reliability for sensor nets that did not simulate routing. [4]) Second, we have developed RMST (Reliable Multi-Segment Transport), a new transport layer, in order to understand the role of in- network processing for reliable data transfer. RMST benefits from diffusion routing, adding minimal additional control traffic. RMST guarantees delivery, even when multiple hops exhibit very high error rates. 1 Introduction Wireless sensor networks provide an economical, fully distributed, sensing and computing solution for environments where conventional networks are impractical. This paper explores the design decisions related to providing reliable data transport in sensor nets. The reliable data transport problem in sensor nets is multi-faceted. The emphasis on energy conservation in sensor nets implies that poor paths should not be artificially bolstered via mechanisms such as MAC layer ARQ during route discovery and path selection [1]. Path maintenance, on the other hand, benefits from well- engineered recovery either at the MAC layer or the transport layer, or both. Recovery should not be costly however, since many applications in sensor nets are impervious to occasional packet loss, relying on the regular delivery of coarse-grained event descriptions. Other applications require loss detection and repair. These aspects of reliable data transport include the provision of guaranteed delivery and fragmentation/ reassembly of data entities larger than the network MTU. Sensor networks have different constraints than traditional wired nets. First, energy constraints are paramount in sensor networks since nodes can often not be recharged, so any wasted energy shortens their useful lifetime [2]. This work was supported by DARPA under grant DABT63-99-1-0011 as part of the SCAADS project, and was also made possible in part due to support from Intel Corporation and Xerox Corporation. Fred Stann and John Heidemann are with USC/Information Sciences Institute, 4676 Admiralty Way, Marina Del Rey, CA, USA E-mail: fstann@usc.edu, johnh@isi.edu. 2 Architectural Choices There are a number of key areas to consider when engineering reliability for sensor nets. Many current sensor networks exhibit high loss rates compared to wired networks (2% to 30% to immediate neighbors)[1,5,6]. While error detection and correction at the physical layer are important, approaches at the MAC layer and higher adapt well to the very wide range of loss rates seen in sensor networks and are the focus of this paper. MAC layer protocols can ameliorate PHY layer unreliability, and transport layers can guarantee delivery. An important question for this paper is the trade off between implementation of reliability at the MAC layer (i.e. hop to hop) vs. the Transport layer, which has traditionally been concerned with end-to-end reliability. Because sensor net applications are distributed, we also considered implementing reliability at the application layer. Our goal is to minimize the cost of repair in terms of transmission.

RMST: Reliable Data Transport in Sensor Networks

https://hal.archives-ouvertes.fr/hal-01780365/document

Internet of things security: A top-down survey

LSB: A Lightweight Scalable Blockchain for IoT security and anonymity

Marc Dacier's topic is: intrusion detection vs. detection of errors caused by intentionally malicious faults. Although research on intrusion detection has been carried out for more than two decades, it has recently received increased attention due to the success of the Internet. A recent survey conducted by the IBM Global Security Laboratory indicates that more than 20 intrusion-detection products are now available on the market, whereas two years ago there were only three. Despite this growth of product offerings, intrusion-detection solutions are still in their infancy. Not only is there a lack of understanding of what an intrusion really is, but also how it should be handled. Moreover, from a technical point of view, many critical issues remain unsolved.In this talk, Marc presents what has been done in the intrusion domain in the past, and highlights new research directions that need to be addressed. He will highlight the relationship between intrusion detection and fault tolerance, drawing on the body of knowledge that has been developed within the traditional dependability community, and noting the opportunities for these two communities to work together to solve this important problem.Sami Saydjari's topic is: the detection of novel, previously unseen attacks. Although intrusion detection is a field still in its infancy, two broad approaches have evolved: pattern-based detection and anomaly-based detection. Pattern-based detection, sometimes called misuse-based detection, relies on matching known patterns of attacks already suffered. Anomaly-based detection, on the other hand, relies on detecting behaviors that are abnormal with respect to some normal standard. An example is that of a masquerader trying to hide behind someone else's login; unless the masquerader is clever indeed, his activities will stand out as anomalous against a victim's profile of normal behavior. Anomaly-based detection techniques appear to hold the best hope of detecting new variants of attacks.Sami emphasizes that although there exist some low-level sensors that can detect known attacks, the research community must move quickly in learning how to detect novel attacks at much higher detection rates (state of the art is around 80%) while keeping the false positive rates very low (0.1% or better). Detecting novel attacks will require better anomaly detection algorithms. Achieving a 99.9% detection rate will require gaining a firm understanding of the "sweet spots" of various detection algorithms, as well as an understanding of how to fuse the results of the best of the best. There is also a need to better represent knowledge of attack patterns in a canonical form, to be able to share that knowledge across multiple detection tools, and to be able to judge tools on the basis of how effectively they use knowledge, as opposed to which tool can include the largest corpus of precompiled (pattern-based) knowledge into its on-line database.The session concludes with an open discussion of how research communities can work together to reduce undependability caused by intentionally malicious faults.

Intrusion Detection

There are many emerging areas in which highly constrained devices are interconnected and communicated to accomplish some tasks Nowadays, Internet of Things (IoT) enables many low resources and constrained devices to communicate, compute process and make decision in the communication network In the heterogeneous environments for IoT, there are many challenges and issues like power consumption of devices, limited battery, memory space, performance cost, and security in the Information Communication Technology (ICT) network In this paper, we discuss a state-of-art of lightweight cryptographic primitives which include lightweight block ciphers, hash function, stream ciphers, high performance system, and low resources device for IoT environment in details We analyze many lightweight cryptographic algorithms based on their key size, block size, number of rounds, and structures In addition, we discuss the security architecture in IoT for constrained device environment, and focus on research challenges, issues and solutions Finally, a proposed security scheme with a service scenario for an improvement of resource constrained IoT environment and open issues are discussed

https://link.springer.com/content/pdf/10.1007%2Fs12652-017-0494-4.pdf

Advanced lightweight encryption algorithms for IoT devices: survey, challenges and solutions

The emergence of new data handling technologies and analytics enabled the organization of big data in processes as an innovative aspect in wireless sensor networks (WSNs). Big data paradigm, combined with WSN technology, involves new challenges that are necessary to resolve in parallel. Data aggregation is a rapidly emerging research area. It represents one of the processing challenges of big sensor networks. This paper introduces the big data paradigm, its main dimensions that represent one of the most challenging concepts, and its principle analytic tools which are more and more introduced in the WSNs technology. The paper also presents the big data challenges that must be overcome to efficiently manipulate the voluminous data, and proposes a new classification of these challenges based on the necessities and the challenges of WSNs. As the big data aggregation challenge represents the center of our interest, this paper surveys its proposed strategies in WSNs.

Big Data Challenges and Data Aggregation Strategies in Wireless Sensor Networks

EDAK: An Efficient Dynamic Authentication and Key Management Mechanism for heterogeneous WSNs

Wireless Sensor Networks have emerged as a new information-gathering system based on the collaborative efforts of large number of tiny sensors with limited resource. Energy constraints distinguish sensors networks from other wireless communication networks. Energy efficiency and network lifetime have been the focus of many research works on sensor networks, such as energy aware routing. This paper suggests a new routing protocol called HEEP which combines two algorithms: LEACH and PEGASIS. HEEP advise a new network self-organisation approach, that join clusters-based and the chain-based approaches. This new approach is called chains clustering approach. Organising the network nodes in chains clusters avoids the bad energy dissipation in LEACH protocol and reduces the routing delay generated by PEGASIS protocol. The experimental results show that HEEP outperforms LEACH and LEACH-C with more 110% of network lifetime, and reduces the routing delay introduced in PEGASIS by 50%.

HEEP (Hybrid Energy Efficiency Protocol) based on chain clustering

Efficient HIP-based approach to ensure lightweight end-to-end security in the internet of things

The wireless sensor networks (WSN) are particularly vulnerable to various attacks at different layers of the protocol stack. Many intrusion detection system (IDS) have been proposed to secure WSNs. But all these systems operate in a single layer of the OSI model, or do not consider the interaction and collaboration between these layers. Consequently these systems are mostly inefficient and would drain out the WSN. In this paper we propose a new intrusion detection system based on cross layer interaction between the network, Mac and physical layers. Indeed we have addressed the problem of intrusion detection in a different way in which the concept of cross layer is widely used leading to the birth of a new type of IDS. We have experimentally evaluated our system using the NS simulator to demonstrate its effectiveness in detecting different types of attacks at multiple layers of the OSI model.

/pdf/cross-layer-intrusion-detection-system-for-wireless-sensor-23zt7i0vap.pdf

Azeddine Bilami

Papers

Big Data Challenges and Data Aggregation Strategies in Wireless Sensor Networks

EDAK: An Efficient Dynamic Authentication and Key Management Mechanism for heterogeneous WSNs

HEEP (Hybrid Energy Efficiency Protocol) based on chain clustering

Efficient HIP-based approach to ensure lightweight end-to-end security in the internet of things

Cross layer intrusion detection system for wireless sensor network