Forwarding Behavior Research Articles

Information-Centric Networking Security

The selected articles cover topics including security mechanisms overview for named data networking (NDN), security for an edge named function environment, secure NDN with attribute- based cryptography and software-defined networking (SDN), content protection for NDN, and the design of a security monitoring plane in NDN. Over the last few decades, the sum of all forms of video data has grown explosively and is expected to reach 90 percent of all Internet traffic in the near future. Meanwhile, new applications, such as the Internet of Things (IoT), augmented reality, and automatic driving, are emerging as the major trends for the next evolution of the digital society, resulting in the generation and sharing of vast amounts of data. The existing Internet-based technologies, such as peer-to-peer networks, content distribution networks, and cloud computing, will be unable to handle such large amounts of data and provide the necessary quality of service (QoS) to the applications. In this context, information-centric networking (ICN), characterized by name-based data retrieval and in-network data caching, has emerged as a promising candidate for future networks. It provides access to named data as first-order network service, providing a built-in mechanism for data provenance and greater potential for optimizing forwarding behavior compared to the traditional host-centric communication systems — the Internet today.

Impact of Content Popularity on Information Coverage in Online Social Networks

Online Social Networks (OSNs) have become an efficient media to disseminate content like news and advertisements. In this paper, we are interested in investigating the open problem of how does the content popularity influence the information coverage exactly. Specifically, we assume that each user has $q$ friends and forwards the received content to each of his friends with the forwarding probability $p$ , where $p$ is only determined by the content popularity. Based on a geography-aware social model leveraging the forwarding behavior of OSNs users, we explore the exact relationship between the content popularity and the information coverage by the method of network partitions. Then, we mainly have the following observations: 1) The information coverage is only related to $p$ and $q$ ; 2) In order to disseminate the content to a constant portion of all users within the network, the forwarding probability $p$ should be no less than $\Theta \left(\frac{1}{q}\right)$ . Extensive evaluations on both the generated data and the real OSN topology validate our observations.

Temperature dependence of electrical properties in Cu0.5Ag0.5InSe2/Si heterostructure

The polycrystalline Cu0.5Ag0.5InSe2 thin film was deposited on mono-crystalline n-Si wafer by sequential thermal evaporation of elemental sources. p-Cu0.5Ag0.5InSe2/n-Si heterojunction diode was fabricated and the current–voltage characteristics of the diode at various temperatures were investigated to determine the main diode parameters and dark current transport mechanism. The studied diode structure showed a rectifying behavior with a barrier height of 0.63 eV at room temperature. Series and shunt resistance values were calculated by parasitic resistance relations in high bias regions. Considering the ideality factor values between 1.7 and 2.8, dominant transport characteristics were detailed for forward and reverse voltages. The analysis of the forward current–voltage behavior reveals field emission can be the possible current conduction mechanism. At the reverse bias region, around 101 number of tunneling step and about 105 density of traps were found to act a role in the process in leakage current flow.

Evaluation of the Schottky Contact Degradation on the Temperature Transient Measurements in GaN HEMTs

The temperature dependence of the Schottky voltage under a forward constant current was used as a means to measure the transient temperature characteristics of gallium nitride (GaN) high-electron-mobility transistors (HEMTs). However, the degradation of the Schottky diode leads to error in the calculated temperature measurement results, especially at a high forward Schottky current. In this paper, we characterized the degradation of GaN HEMT Schottky diodes under forward bias using pulsed current–voltage measurements. The forward Schottky voltage behavior at constant currents of 0.2, 0.35, 0.5, 1, 1.5, and 2 mA was monitored. In particular, the vertical temperature distribution was corrected experimentally based on the transient voltage measurements. The success of this correction indicates that the said artifacts can be removed using the transient voltage measurements. This method increases the accuracy of temperature measurements when the temperature dependence of the Schottky voltage is used to characterize the behavior of GaN HEMTs.

Wise-PRoPHET: A Watchdog supervised PRoPHET for reliable dissemination of post disaster situational information over smartphone based DTN

Delay tolerant network (DTN) has been successfully proposed for setting up emergency post disaster communication networks when normal communication infrastructure is typically incapacitated. These networks work on the basis of cooperation from participating nodes, which is cost-intensive in terms of battery life, computation, etc. Therefore, nodes can refuse to cooperate to save resources, giving rise to selfish nodes that hinder the transmission of sensitive post disaster situational messages. Another issue is the presence of malicious nodes that collude to either spoil the reputation of honest nodes or boost the reputation of selfish nodes. The existing DTN routing protocols, like PRoPHET, do not address these issues. In this paper, a trust based Watchdog technique is seamlessly integrated with PRoPHET so that situational messages are successfully delivered even in the presence of selfish and malicious nodes. The Watchdog monitors its neighbouring nodes to generate a local perception about their forwarding behaviour. This information is then disseminated in the network to build a global perception of forwarding behaviour for detection of selfish nodes. The local perception is further used to identify malicious nodes in the network. The proposed technique rationalizes self-trusting, a property of trust based data forwarding in opportunistic networks which reduces and delays message transfers, to further improve delivery ratio and delay. Results of extensive simulation, using ONE simulator, substantiate the efficiency of the proposed Watchdog enabled PRoPHET over state-of-the-art competing schemes, in terms of detection ratios, attraction ratio, etc. while not compromising standard network performance. Finally, it is claimed that the proposed technique, tolerates a reasonable percentage of selfish and malicious nodes to achieve a desirable level of network performance, in a post disaster communication scenario.

Algebraic Methods for the Construction of Algebraic-Difference Equations With Desired Behavior

For a given system of algebraic and difference equations, written as an Auto-Regressive (AR) representation $A(\sigma)\beta(k)=0$, where $\sigma $ denotes the shift forward operator and $A\left( \sigma \right) $ a regular polynomial matrix, the forward-backward behavior of this system can be constructed by using the finite and infinite elementary divisor structure of $A\left( \sigma \right) $. This work studies the inverse problem: Given a specific forward-backward behavior, find a family of regular or non-regular polynomial matrices $A\left( \sigma \right) $, such that the constructed system $A\left( \sigma \right) \beta \left( k\right) =0$ has exactly the prescribed behavior. It is proved that this problem can be reduced either to a linear system of equations problem or to an interpolation problem and an algorithm is proposed for constructing a system satisfying a given forward and/or backward behavior.

An Efficient Trust-Based Scheme for Secure and Quality of Service Routing in MANETs

Due to the dynamism of topology, sharing of bandwidth and constraint of resources in wireless nodes, the provision of quality of service (QoS) for routing in mobile ad hoc networks (MANETs) presents a great challenge. Security is another crucial aspect of providing QoS since the existence of malicious nodes present all kinds of threats to MANETs. Although a number of mechanisms have been proposed for protecting MANETs, most of the solutions are only effective for a particular kind of attacks or provide security at the cost of sacrificing QoS. In this paper, we propose a trust-based secure QoS routing scheme by combining social and QoS trust. The primary approach of the proposed scheme relies on mitigating nodes that exhibit various packet forwarding misbehavior and on discovering the path that ensures reliable communication through the trust mechanism. The scheme would select the best forwarding node based on packet forwarding behavior as well as capability in terms of QoS parameters, such as residual energy, channel quality, link quality, etc. We will present an adversary model for packet dropping attack against which we evaluate the proposed scheme. Simulation experiment using Network Simulator-2 (NS2) and under various network conditions show that mixing social and QoS trust parameters can greatly improve security and quality of service routing in terms of overhead, packet delivery ratio and energy consumption.

Factors influencing the forwarding behaviour of mobile phone users in the context of mobile advertising in Europe

The importance of word of mouth (WOM) as a source of information for consumers to draw from when making a purchase decision has been acknowledged by scholars and practitioners alike. With the technological development on a global scale, a new type of WOM has emerged, namely the mobile word of mouth (mWOM). Mobile phones have become an essential means of communication for consumers, and the mWOM has a great potential to influence individuals at any stage of the decision-making process. The current research seeks to find an answer to the question of what factors influence an individual's decision to participate in mWOM using an empirical study. It was found that value perceptions have an impact on mobile users' desire to participate in WOM. Contrary to hypothesised, the desire to participate in WOM does not lead to a higher intention to speak positively about the mobile advertising campaign.

Factors influencing the forwarding behaviour of mobile phone users in the context of mobile advertising in Europe

Factors influencing the forwarding behaviour of mobile phone users in the context of mobile advertising in Europe

APD-JFAD: Accurate Prevention and Detection of Jelly Fish Attack in MANET

Mobile ad hoc networks (MANETs) are surrounded by tons of different attacks, each with different behavior and aftermaths. One of the serious attacks that affect the normal working of MANETs is DoS attack. A sort of DoS attack is Jellyfish attack, which is quite hard because of its foraging behavior. The Jellyfish attack is regarded as one of the most difficult attack to detect and degrades the overall network performance. In order to combat Jellyfish attack in MANETs, this paper proposes a novel technique called accurate prevention and detection of jelly fish attack detection (APD-JFAD). It is a fusion of authenticated routing-based framework for detecting attacks and support vector machine (SVM). SVM is utilized for learning packet forwarding behavior. The proposed technique chooses trusted nodes in the network for performing routing of packets on the basis of hierarchical trust evaluation property of nodes. The technique is tested using NS-2 simulator against other existing techniques, i.e., ABC, MABC, and AR-AIDF-GFRS algorithms by various parameters such as throughput, PDR, dropped packet ratio, and delay. The results prove that APD-JFAD is highly efficient in Jellyfish attack detection and also performs well as compared to other algorithms.

Viral Promotional Advergames: How Intrinsic Playfulness and the Extrinsic Value of Prizes Elicit Behavioral Responses

When designing a viral promotional advergame (VPA) (which combines a promotional game and an advergame in a viral marketing campaign), marketers focus on game schemes and prizes to trigger players' intrinsic and extrinsic motivations and elicit certain behavioral responses, such as sharing personal data and forwarding the game. A field study examines factors that lead to behavioral responses in VPAs. The results show that players who perceive more playfulness tend to increase their game forwarding and personal data sharing behaviors. The perceived value of prizes also relates positively to game forwarding but not to personal data sharing. Finally, the results show that prior brand attitudes moderate the effect of the perceived value of prizes on game forwarding behavior.

Fast packet classification algorithm for network-wide forwarding behaviors

Packet classification has been a key technology to quickly identify an action to be taken on a packet at a switch. Several advanced applications, most of which have been introduced recently with the advent of software-defined networking, commonly require the identification of a combination of switch actions, i.e., the network-wide forwarding behavior of a packet. Conventional classification methods, however, fail to well support network-wide behaviors, since the search space is partitioned in convoluted manner due to the complexity posed by the combinations possible.This paper proposes a novel packet classification method that supports the fast determination of network-wide forwarding behaviors. To avoid the inefficiencies of existing methods, which are revealed for the first time by our research, we base our method on a compressed data structure named the multi-valued decision diagram. On the solid foundation of decision diagrams, several algorithms are introduced with thorough theoretical analyses, and the construction process and the classification performance are highly optimized for the new classification problem. Experiments on real network datasets show that our method identifies the network-wide forwarding behaviors at the line basic rate, e.g., 10 Mpps, on a single CPU core with only tens of MB of memory.

Leveraging SDN to Improve the Performance of Multicast-Enabled IPTV Distribution Systems

Distribution of live multimedia streams to a high number of end users through an ISP network may be efficiently implemented through IP multicasting. Multicast traffic engineering with traditional decentralized approaches, however, is still a challenging problem for network operators. In this article we present a centralized approach to management of source-specific multicast traffic flows relying on software defined networking. Our approach is suitable for hybrid IP/SDN networks, where network nodes behave as traditional IP routers by default, but whose packet forwarding behavior may be customized for specific flows thanks to an OpenFlow-enabled control plane. We also describe a traffic management system that we implemented as a proof of concept, which can be used by an ISP to compute multicast distribution trees for a given set of channels to be distributed to their customers.

Practical Network-Wide Packet Behavior Identification by AP Classifier

Identifying the network-wide forwarding behaviors of a packet is essential for many network management applications, including rule verification, policy enforcement, attack detection, traffic engineering, and fault localization. Current tools that can perform packet behavior identification either incur large time and memory costs or do not support real-time updates. In this paper, we present AP Classifier, a control plane tool for packet behavior identification. AP Classifier is developed based on the concept of atomic predicates, which can be used to characterize the forwarding behaviors of packets. Experiments using the data plane network state of two real networks show that the processing speed of AP Classifier is faster than existing tools by at least an order of magnitude. Furthermore, AP Classifier uses very small memory and is able to support real-time updates.

Analytical Model for SDN Signaling Traffic and Flow Table Occupancy and Its Application for Various Types of Traffic

Software defined networking (SDN) has emerged as a promising networking paradigm overcoming various drawbacks of current communication networks.The control and data plane of switching devices is decoupled and control functions are centralized at the network controller. In SDN, each new flow introduces additional signaling traffic between the switch and the controller. Based on this traffic, rules are created in the flow table of the switch, which specify the forwarding behavior. To avoid table overflows, unused entries are removed after a predefined time-out period. Given a specific traffic mix, the choice of this time-out period affects the tradeoff between signaling rate and table occupancy . As a result, network operators have to adjust this parameter to enable a smooth and efficient network operation. Due to the complexity of this problem caused by the various traffic flows in a network, a suitable abstraction is necessary in order to derive valid parameter values in time. The contribution of this paper is threefold. First, we formulate a simple analytical model that allows optimizing the network performance with respect to the table occupancy and the signaling rate. Second, we validate the model by means of simulation. Third, we illustrate the impact of the time-out period on the signaling traffic and the flow table occupancy for different data-plane traffic mixes and characteristics. This includes scenarios with single application instances, as well as multiple application instances of different application types in an SDN-enabled network.

RuleScope: Inspecting Forwarding Faults for Software-Defined Networking

Software-defined networking (SDN) promises unprecedentedly flexible network management but it is susceptible to forwarding faults. Such faults originate from data-plane rules with missing faults and priority faults. Yet existing fault detection ignores priority faults, because they are not discovered on commercial switches until recently. In this paper, we present RuleScope, a more comprehensive solution for inspecting SDN forwarding. RuleScope offers a series of accurate and efficient algorithms for detecting and troubleshooting rule faults. They inspect forwarding behavior using customized probe packets to exercise data-plane rules. The detection algorithm exposes not only missing faults but also priority faults and the troubleshooting algorithm uncover actual forwarding states of data-plane flow tables. Both of them help track real-time forwarding status and benefit reliable network monitoring. Furthermore, toward fast inspection of dynamic networks, we propose incremental algorithms for rapidly evolving network policies to amortize detection and troubleshooting overhead without sacrificing accuracy. Experiments with our prototype on the Ryu SDN controller and Pica8 P-3297 switch show that the RuleScope achieves accurate fault detection on 320-entry flow tables with a cost of 1500+ probe packets within 16 s.

Communication and Data Trust for Wireless Sensor Networks Using D–S Theory

Wireless sensor networks (WSNs) are usually deployed in insecure remote and open environments. Nodes could be attacked and compromised. The attacker can use compromised sensor nodes to disrupt communications or inject misleading sensor values. Misleading data can corrupt the entire decision making process, which depends upon WSN data. We propose a trust mechanism, which evaluates communication trust and data trust for WSNs. Communication trust is computed from direct and indirect observations of the neighbour's forwarding behavior. Direct trust is derived from the consistency of forwarding behavior. Indirect trust is derived from the neighbour's observations translated into recommendations. We use weighted Dempster-Shaffer (D-S) theory to compute indirect trust. Data trust is computed by using median of sensor data. We present arguments and simulation results to show the effectiveness of the proposed algorithm against packet forwarding/modification attacks, bad mouthing attacks, collusion attacks, and on-off attacks. Our proposed trust model helps data in WSNs to be more secure.

Construction of Algebraic and Difference Equations with a Prescribed Solution Space

AbstractThis paper studies the solution space of systems of algebraic and difference equations, given as auto-regressive (AR) representationsA(σ)β(k) = 0, whereσdenotes the shift forward operator andA(σ) is a regular polynomial matrix. The solution space of such systems consists of forward and backward propagating solutions, over a finite time horizon. This solution space can be constructed from knowledge of the finite and infinite elementary divisor structure ofA(σ). This work deals with the inverse problem of constructing a family of polynomial matricesA(σ) such that the systemA(σ)β(k) = 0 satisfies some given forward and backward behavior. Initially, the connection between the backward behavior of an AR representation and the forward behavior of its dual system is showcased. This result is used to construct a system satisfying a certain backward behavior. By combining this result with the method provided by Gohberget al. (2009) for constructing a system with a forward behavior, an algorithm is proposed for computing a system satisfying the prescribed forward and backward behavior.

Discovering hidden suspicious accounts in online social networks

Hidden suspicious accounts are sparsely connected in social graphs; however, certain suspicious messages are usually forwarded in bulk to extend their overall propagation scope. Existing anti-attack methods only detect single messages or accounts. Because most algorithms rely on the connection relations among the accounts in social graphs, they may repeatedly detect the same account. Furthermore, these hidden suspicious accounts cannot be identified and eliminated completely. Therefore, messages forwarded by hidden suspicious accounts should be merged, and the accounts should be eliminated simultaneously rather than individually. This paper introduces the forwarding message tree, which combines accounts based on the relations among their forwarded messages. Our approach clearly exposes the inner relations among hidden suspicious accounts and conveniently deletes those accounts. First, we present the forwarding message tree and identify six effective features: the forwarding layer relation, propagation depth, propagation breadth, repeated forwarding behavior, propagation speed, and average tree weight. Next, to illustrate the effectiveness of these features, we incorporate them into machine learning algorithms. The detection accuracy and false-positive rates for a real dataset collected from an online social network are 95.32% and 0.5%, respectively. Most of the proposed features rate at the top of a gain ranking. We conclude that the forwarding message tree can indeed detect and delete hidden suspicious accounts.

Incentive-Compatible Packet Forwarding in Mobile Social Networks via Evolutionary Game Theory

In the absence of end-to-end paths and without the knowledge of the whole network, packet forwarding, including forwarding decision (i.e., forwarding or dropping the packet) and relaying selection, is crucial to be made by the individual of the node based on the packet-forwarding protocol in autonomous mobile social networks (MSNs). In this paper, we investigate the adaptive packet forwarding in MSNs afflicted with potential selfish nodes. When considering the various selfish behaviors of network nodes in multi-hop MSNs, an incentive compatible multiple-copy packet forwarding (ICMPF) protocol is proposed to maintain a satisfied packet delivery probability while reducing the delivery overhead. Considering the fact that the node's forwarding decision in the ICMPF protocol is affected by its available resources (i.e., bandwidth and location privacy) and network environment (i.e., other nodes' actions and social ties), an evolutionary game framework is exploited for modeling the complicated interactions among nodes to guide their forwarding behaviors. Meanwhile, we portray the forwarding behavior dynamics and develop the evolutionary stable strategy (ESS) for this game-theoretic framework. Then, we prove that the strategy dynamics converge to the ESS and further develop a distributed learning algorithm for nodes to approach to the ESS. Simulation results show that our system converges to the ESS and also is robust to the learning error induced by the communication noise.