National Institute of Standards and Technology における超伝導研究及び生活

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

A low-rate distributed denial of service (DDoS) attack has significant ability of concealing its traffic because it is very much like normal traffic. It has the capacity to elude the current anomaly-based detection schemes. An information metric can quantify the differences of network traffic with various probability distributions. In this paper, we innovatively propose using two new information metrics such as the generalized entropy metric and the information distance metric to detect low-rate DDoS attacks by measuring the difference between legitimate traffic and attack traffic. The proposed generalized entropy metric can detect attacks several hops earlier (three hops earlier while the order α = 10 ) than the traditional Shannon metric. The proposed information distance metric outperforms (six hops earlier while the order α = 10) the popular Kullback-Leibler divergence approach as it can clearly enlarge the adjudication distance and then obtain the optimal detection sensitivity. The experimental results show that the proposed information metrics can effectively detect low-rate DDoS attacks and clearly reduce the false positive rate. Furthermore, the proposed IP traceback algorithm can find all attacks as well as attackers from their own local area networks (LANs) and discard attack traffic.

Low-Rate DDoS Attacks Detection and Traceback by Using New Information Metrics

The rapid developments of the Internet of Things (IoT) and smart mobile devices in recent years have been dramatically incentivizing the advancement of edge computing. On the one hand, edge computing has provided a great assistance for lightweight devices to accomplish complicated tasks in an efficient way; on the other hand, its hasty development leads to the neglection of security threats to a large extent in edge computing platforms and their enabled applications. In this paper, we provide a comprehensive survey on the most influential and basic attacks as well as the corresponding defense mechanisms that have edge computing specific characteristics and can be practically applied to real-world edge computing systems. More specifically, we focus on the following four types of attacks that account for 82% of the edge computing attacks recently reported by Statista: distributed denial of service attacks, side-channel attacks, malware injection attacks, and authentication and authorization attacks. We also analyze the root causes of these attacks, present the status quo and grand challenges in edge computing security, and propose future research directions.

https://ieeexplore.ieee.org/ielaam/5/8789751/8741060-aam.pdf

Edge Computing Security: State of the Art and Challenges

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Service Oriented Architecture Concepts Technology And Design

This book constitutes the refereed proceedings of the International Conference on Future Network Systems and Security, FNSS 2015, held in Paris, France, in June 2015.The 13 full papers presented were carefully reviewed and selected from 34 submissions. The papers focus on the technology, communications, systems and security aspects of relevance to the network of the future.

Future Network Systems and Security: First International Conference, FNSS 2015, Paris, France, June 11-13, 2015, Proceedings

This paper has presented three insiders attacks on Zigbee protocol – a protocol used for wireless communication for the Internet of Thing (IoT) devices. The end- user’s communication in IoT networks are sensor oriented as the user objects in IoT networks are embedded with sensors and actuators. Most of the sensors communicate with wireless medium among which many of them use Zigbee protocol. Security is an important element of IoT objects to protect user’s privacy and counter malicious attacks but difficult to guarantee due to its limited capabilities, wireless communication and unpredicted users’ actions. In this paper, we have evaluated Zigbee protocol stack for security vulnerabilities which revealed security weakness of remote AT commands. By using remote AT commands in an IoT network, we have devised three successful insider attacks to make unauthorized change of the destination address of a packet, change of node ID, and the change of PAN ID. These attacks detail will be very useful for IoT researches and practitioners in the security domain to design appropriate countermeasures for Zigbee IoT networks.

Insider Attacks on Zigbee Based IoT Networks by Exploiting AT Commands

Liquefied Petroleum Gas (LPG) gas is the most commonly used gas for cooking in India and it is considered highly flammable since it is a combination of hydrocarbon gases such as Propane (C3H8), N-butane and Isobutane (C4H10). These elements contribute to its high density and long-distance travelling capabilities. This results in an extensive gas outspread during leakage with multiple avenues for ignition, primarily due to the electric circuitry at home. The primary focus of our project is to simulate a network map of a gas leakage warning system so as to showcase its implementation in an apartment-based setup. The network map can be scaled up for implementation in residential sectors, petroleum and oil fields, sewage lines, etc. based on our proof of concept. In our use case, we would implement LPG Gas Sensors to Microcontroller for providing a logical binary output of fire warning indication.

Gas Leakage Warning System

Security is a major challenge in Opportunistic Networks (OppNets) because of its characteristics, such as open medium, dynamic topology, no centralized management and absent clear lines of defense. A packet dropping attack is one of the major security threats in OppNets since neither source nodes nor destination nodes have the knowledge of where or when the packet will be dropped. In our previous novel attack (Packet Faking Attack [1]) we presented a special type of packet dropping where the malicious node drops one or more packets and then injects new fake packets instead. In this paper, we present an efficient detection mechanism against this type of attack where each node can detect the attack instead of the destination node. Our detection mechanism is very powerful and has very high accuracy. It relies on a very simple yet powerful idea, that is, the packet creation time of each packet. Simulation results show this robust mechanism achieves a very high accuracy, detection rate and good network traffic reduction.

An Efficient Detection Mechanism Against Packet Faking Attack in Opportunistic Networks

Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multidimensional data). Such networks present unique challenges to data dissemination, data storage and in-network query processing (information discovery). In this paper, we investigate efficient strategies for information discovery in large-scale multidimensional WSNs and propose the Adaptive Multi-Dimensional Multi-Resolution Architecture (A-MDMRA) that efficiently combines “push” and “pull” strategies for information discovery and adapts to variations in the frequencies of events and queries in the network to construct optimal routing structures. We present simulation results showing the optimal routing structure depends on the frequency of events and query occurrence in the network. It also balances push and pull operations in large scale networks enabling significant QoS improvements and energy savings.

Robin Doss

Papers

Future Network Systems and Security: First International Conference, FNSS 2015, Paris, France, June 11-13, 2015, Proceedings

Insider Attacks on Zigbee Based IoT Networks by Exploiting AT Commands

Gas Leakage Warning System

An Efficient Detection Mechanism Against Packet Faking Attack in Opportunistic Networks

An adaptive approach to information discovery in multi-dimensional wireless sensor networks