Subscribing to online services is typically a straightforward process, but cancelling them can be arduous and confusing — causing many to resign and continue paying for services they no longer use. Making the cancellation process intentionally difficult is recognized as a dark pattern called Roach Motel. This paper characterizes the subscription and cancellation flows of popular news websites from four different countries, and discusses them in the context of recent regulatory changes. We study the design features that make it difficult to cancel a subscription and find several cancellation flows that feature intentional barriers, such as forcing users to call a representative or type in a phrase. Further, we find many subscription flows that do not adequately inform users about recurring charges. Our results point to a growing need for effective regulation of designs that trick, coerce, or manipulate users into paying for subscriptions they do not want.

Authentication security advice is given with the goal of guiding users and organisations towards secure actions and practices. In this article, a taxonomy of 270 pieces of authentication advice is created, and a survey is conducted to gather information on the costs associated with following or enforcing the advice. Our findings indicate that security advice can be ambiguous and contradictory, with 41% of the advice collected being contradicted by another source. Additionally, users reported high levels of frustration with the advice and identified high usability costs. The study also found that end-users disagreed with each other 71% of the time about whether a piece of advice was valuable or not. We define a formal approach to identifying security benefits of advice. Our research suggests that cost-benefit analysis is essential in understanding the value of enforcing security policies. Furthermore, we find that organisation investment in security seems to have better payoffs than mechanisms with high costs to users.

Abstract Electricity is a major cost in running a data centre, and servers are responsible for a significant percentage of the power consumption. Given the widespread use of HTTP, both as a service and a component of other services, it is worthwhile reducing the power consumption of web servers. In this paper we consider how reverse proxies, commonly used to improve the performance of web servers, might be used to improve energy efficiency. We suggest that when demand on a server is low, it may be possible to switch off servers. In their absence, an embedded system with a small energy footprint could act as a reverse proxy serving commonly-requested content. When new content is required, the reverse proxy can power on the servers to meet this new load. Our results indicate that even with a modest server, we can get a 25% power saving while maintaining acceptable performance.

Leaks from password datasets are a regular occur-rence. An organization may defend a leak with reassurances that just a small subset of passwords were taken. In this paper we show that the leak of a relatively small number of text-based passwords from an organizations' stored dataset can lead to a further large collection of users being compromised. Taking a sample of passwords from a given dataset of passwords we exploit the knowledge we gain of the distribution to guess other samples from the same dataset. We show theoretically and empirically that the distribution of passwords in the sample follows the same distribution as the passwords in the whole dataset. We propose a function that measures the ability of one distribution to estimate another. Leveraging this we show that a sample of passwords leaked from a given dataset, will compromise the remaining passwords in that dataset better than a sample leaked from another source.

In this work we show that random-access protocols, which are used in a range of networks (e.g. WiFi, power line communications and Internet of Things), may experience a high-throughput, extremely long (of the order of hours) transitory phase. This behaviour is not highlighted by common analysis techniques and experimental evaluations, which can lead to incorrect prediction of network performance. We identify factors that led to this transitory behaviour being overlooked in previous work. Via numerical analysis and experimental evaluation, we establish under which conditions this transitory phase occurs. Additionally, we give insight into the duration of this transitory period and its statistical properties.

As Small Medium Enterprises (SMEs) adopt Cloud technologies to provide high value customer offerings, uptime is considered important. Cloud outages represent a challenge to SMEs and micro teams to maintain a services platform. If a Cloud platform suffers from downtime this can have a negative effect on business revenue. Additionally, outages can divert resources from product development/delivery tasks to reactive remediation. These challenges are immediate for SMEs or micro teams with a small levels of resources. In this paper we present a framework that can model the arrival of Cloud outage events . This framework can be used by DevOps teams to manage their scarce pool of resources to resolve outages, thereby minimising impact to service delivery. We analysed over 300 Cloud outage events from an enterprise data set. We modelled the inter-arrival and service times of each outage event and found a Pareto and a lognormal distribution to be a suitable fit. We used this result to produce a special case of the G/G/1 queue system to predict busy times of DevOps personnel. We also investigated dependence between overlapping outage events. Our predictive queuing model compared favourably with observed data , 72% precision was achieved using one million simulations.

While Western societies are becoming increasingly connected, many developing regions lack basic Internet connectivity, primarily due to the high costs associated with infrastructure deployment and maintenance. Potential exists for the TV white-space (TVWS) wireless technology to bridge this digital divide, though efficient channel access mechanisms suited to multi-hop networks that operate in sub-gigahertz bands are yet to be developed. Using a small test bed, we demonstrate a prototype implementation of a medium access protocol that learns appropriate transmission opportunities in such settings, achieving pseudo-scheduled behaviour ex tempore and providing substantial gains over the de facto IEEE 802.11af protocol.

Due to the directionality of transmissions in millimeter wave (mm-wave) networks, wireless stations are usually unable to overhear when other stations access the channel. This makes it hard to design efficient distributed beam coordination and scheduling mechanisms. At the same time, centralized schemes only perform well in relatively simple, static scenarios. In practical settings where links have different channel qualities and in the context of relaying or in-band backhauling, centrally coordinating all stations becomes difficult. In this paper, we propose a low complexity, decentralized, learning-based scheduling algorithm for mm-wave networks that handles heterogeneous link rates and packet sizes efficiently. Compared to state-of-the-art slotted channel access for mm-wave networks, the proposed mechanism achieves throughput gains of up to a factor of 8 in single-hop scenarios and end-to-end throughput improvements of up to a factor of 1.6 in multi-hop topologies.

The rise of the cloud and distributed data-intensive (big data) applications puts pressure on data center networks due to the movement of massive volumes of data. Reducing the volume of communication is pivotal for embracing greener data exchange by efficient utilization of network resources. This paper proposes the use of mixing technique, spate coding, working in tandem with software-defined network control as a means of dynamically-controlled reduction in volume of communication. We introduce motivating real-world use-cases, and present a novel spate coding algorithm for the data center networks. We also analyze the computational complexity of the general problem of minimizing the volume of communication in a distributed data center application without degrading the rate of information exchange, and provide theoretical limits of such schemes. Moreover, we proceed to bridge the gap between theory and practice by performing a proof-of-concept implementation of the proposed system in a real world data center. We use Hadoop MapReduce, the most widely used big data processing framework, as our target. The experimental results employing two of industry standard benchmarks show the advantage of our proposed system compared to a vanilla Hadoop implementation, an in-network combiner, and Combine-N-Code. The proposed coding-based scheme shows performance improvement in terms of volume of communication (up to 62%), goodput (up to 76%), disk utilization (up to 38%), and the number of bits that can be transmitted per Joule of energy (up to 200%).

In recent decades, power line communication (PLC) has attracted considerable attention from the research community and industry, as well as from regulatory and standardization bodies. In this paper, we provide an overview of both narrowband and broadband systems, covering potential applications, regulatory and standardization efforts, and recent research advancements in channel characterization, physical layer performance, medium access, and higher layer specifications and evaluations. We also identify the areas of current and further study that will enable the continued success of PLC technology.

Welcome to the IEEE JSAC special issue on Power Line Communications and its Integration with the Networking Ecosystem. This special issue was motivated by the growth in maturity of power line communications (PLC) over the last ten years since the last JSAC special issue focusing on PLC in 2006. For this special issue, we hoped to receive papers showing the growth of PLC technology itself, and works showing applications and integration with the technology ecosystem.

With the increasing availability of flexible wireless 802.11 devices, the potential exists for users to selfishly manipulate their channel access parameters and gain a performance advantage. Such practices can have a severe negative impact on compliant stations. To enable access points to counteract these selfish behaviours and preserve fairness in wireless networks, in this paper we propose a policing mechanism that drives misbehaving users into compliant operation without requiring any cooperation from clients. This approach is demonstrably effective against a broad class of misbehaviours, soundly-based, i.e., provably hard to circumvent and amenable to practical implementation on existing commodity hardware.

Power Line Communication (PLC) devices are increasingly used and available. However, research carried out at the Medium Access Control (MAC) layer is limited. This article addresses Quality of Service (QoS) mechanisms defined in the widely implemented Homeplug and IEEE 1901 standards. By means of a testbed constructed from off-the-shelf components we identify a number of issues with a potentially significant impact on user satisfaction: i) a pronounced starvation and variability of lower-priority traffic when different access categories are combined and ii) an oscillatory behaviour in higher-priority and high-traffic configurations. We also determine the underlying causes of such findings and propose possible solutions. Our contributions are of relevance to both the research community and manufacturers, as we identify crucial aspects to be revisited in order to guarantee successful advancement and further adoption of the technology.

A many-to-one communication pattern is present both in Data Acquisition (DAQ) and datacenter networks. The problem arising from this pattern is widely known in the literature as incast and can be observed as TCP throughput collapse. It is a result of overloading the switch buffers, when a specific node in a network requests data from multiple sources. This paper provides two contributions. First, we confirm that there are strong analogies between the TCP behavior in DAQ and datacenter networks. Second, we evaluate different proposals from the datacenter environment for application in DAQ to improve performance and reduce buffer requirements.

The recent trends in software-defined networking (SDN) and network function virtualization (NFV) are boosting the advance of software-based packet processing and forwarding on commodity servers. Although performance has traditionally been the challenge of this approach, this situation changes with modern server platforms. High performance load balancers, proxies, virtual switches and other network functions can be now implemented in software and not limited to specialized commercial hardware, thus reducing cost and increasing the flexibility. In this paper we design a lossless software-based switch for high bandwidth data acquisition (DAQ) networks, using the ATLAS experiment at CERN as a case study. We prove that it can effectively solve the incast pathology arising from the many-to-one communication pattern present in DAQ networks by providing extremely high buffering capabilities. We evaluate this on a commodity server equipped with twelve 10 Gbps Ethernet interfaces providing a total bandwidth of 120 Gbps.

WLANs are constantly undergoing extensive research and development, and scientists keep coming up with new methods to improve existing protocols and amend standards. Experimental assessment has been an important part of 802.11 research, however measuring the detailed behaviour of the medium and hardware has been challenging. In this paper we design a diagnostic tool, WiFo, for IEEE 802.11-based WLANs. This tool helps developers and researchers monitor and analyze the wireless signals and details such as backoff distribution in a user-friendly environment. Our solution is much cheaper and easier to use than existing tools, and provides more flexibility by allowing users to add functionality. We then use WiFo to study several aspects of some off-the-shelf hardware and their corresponding software drivers, and show some interesting results regarding how they apply standard specifications.

This paper presents findings of an empirical study into how delays and inactivity gaps affect end user perception in the system implementation phase - and subsequently - during the actual usage phase. The authors' methods of research included interviews and online surveys with employees within an accounts team of a company named DFS. The findings indicate that inactivity gaps (short delays) have a negative impact on end user perception in the implementation phase, however on the other hand, long delays pose a minor effect on end user perception in the implementation phase. The data reveals end users view longer delays more positively than shorter delays with both types of delays having no bearing on satisfaction levels during system usage.

Packet loss is one of the most important factors in degrading Voice over IP (VoIP) perceived call quality. Forward Error Correction (FEC) is a powerful technique for transmitting audio streams over the IP network to decrease the effect of packet loss. Although these method reduces the effect of packet loss, it increases the bandwidth and delay in order to recover from the lost packets. In this paper, we propose a new adaptive FEC mechanism for voice calls based on the generated codewords from a Reed-Solomon (RS) encoder. This mechanism chooses the optimum RS code from a family of codes to improve the conversational call quality. Our proposed mechanism is able to switch between different codes during the call to account for the variation of the network conditions including packet loss and delay. We have deduced the proposed algorithm by performing subjective mean opinion score (MOS) testing based on an interactive assessment tests. We show that our adaptive algorithm outperforms fixed RS codes under highly varying network conditions.

Femtocells are small cellular telecommunication base stations that provide improved cellular coverage. These devices provide important improvements in coverage, battery life and throughput, they also present security challenges. We identify a problem which has not been identified in previous studies of femtocell security: rogue owners of femtocells can secretly monitor third-party mobile devices by using the femtocell's access control features. We present traffic analysis of real femtocell traces and demonstrate the ability to monitor mobile devices through classification of the femtocell's encrypted backhaul traffic. We also consider the femtocell's power usage and status LEDs as other side channels that provide information on the femtocell's operation. We conclude by presenting suitable solutions to overcome this problem.

The standardized Medium Access Control (MAC) protocols for Power Line Communication (PLC) networks (Homeplug and IEEE 1901) are based on the Distributed Coordination Function (DCF) defined for IEEE 802.11. However, the backoff procedure is modified with the goal of decreasing the collision probability. In this work, the backoff procedure of PLC MAC protocols is compared to DCF in different traffic conditions and scenarios, including scenarios with all nodes in coverage range as well as topologies with hidden and exposed terminal problems. The goal is to demonstrate and quantify the pros and cons of each approach in each particular case. Results show that the modified backoff procedure of the Homeplug MAC reduces the collision probability when there is high contention. However, the performance is not always improved compared to DCF. Moreover, when Homeplug provides better performance than the vanilla DCF, we show that the DCF can be easily tuned to achieve similar gains.

The two main drawbacks of receiver-initiated Medium Access Control (MAC) protocols for Wireless Sensor Networks (WSNs) are that i) they require all nodes to send a beacon each time they wake up, and that ii) broadcast traffic is not efficiently supported. In this work, we propose addressing these limitations by extending receiver-initiated MAC protocols with scheduling, i.e, coordinating sensor nodes to wake up at nearly the same instant. Following this approach, only one sensor node in the neighborhood sends a beacon per wake-up period and, as all nodes are awake at the same time, broadcast transmissions are naturally supported. A distributed learning technique is used to establish the order of beacon transmissions. We present the protocol description and the time to convergence when a fully connected network is considered.

As open-source WiFi device drivers are increasingly available, wireless equipment can be configured to disobey the 802.11 specification, with the goal of achieving performance gains, to the detriment of fair users.We demonstrate a practical implementation of a node policing scheme that combats such selfish behaviour, using commercial off-the-shelf hardware and a modified firmware. With a small testbed, we show that access points running our scheme can detect misbehaving stations, inflict punishment upon them and effectively restore fairness in the network.

Rate control methodologies that are currently available in IEEE 802.11 network cards seriously underutilize network resources and, in addition, per-second throughputs suffer from high variability. In this paper, we introduce an algorithm, H-RCA, that overcomes these shortcomings, giving substantially higher, and less variable, throughput. The approach solely uses information already available at the driver-level to function and can be implemented on 802.11e commodity hardware. H-RCA's design objective is to minimize the average time each packet spends on the medium (including retries) in order to maximize total network throughput. It uses a development of a recently proposed estimation scheme to distinguish transmission failures due to collisions from those caused by channel noise. It employs an estimate of the packet loss ratio due to noise in assessing whether it is appropriate to change rate. We demonstrate experimentally that packet loss ratio is not necessarily a monotonic increasing function of rate; this is accounted for in H-RCA's design. As H-RCA statistically separates noise losses from those caused by collisions, ns-2 simulations show that it is robust to changing environments. H-RCA does not require specific hardware support nor any change to the IEEE 802.11 protocol. This point is substantiated with results from an experimental implementation.

Hash functions are often used to consistently assign objects to particular resources, for example to load balancing in networks. These functions can be randomly selected from a family, to prevent attackers generating many colliding objects, which usually results in poor performance. We describe a number of attacks allowing us to identify which hash function from a family is being used by observing a relatively small number of collisions. This knowledge can then be used to generate a large number of colliding inputs. In particular we detail attacks against small families of hashes, Pearson-like hash functions and linear hashes, such as the Toeplitz hash used in Microsoft's Receive Side Scaling.

Power line communication (PLC) technology is at a tipping point and may become ubiquitous as a home networking technology. However, there are concerns regarding RF interference between PLC networks and other radio operators. It is imperative that the interference dynamics of PLC systems be fully understood in advance of any large-scale roll-out. In this work, we experiment with two interference scenarios: notch-infilling due to non-linear mixing and mitigation of radiated emissions using RF chokes. In our controlled test bed environment, we measure RF emissions from the power line devices in the 1 MHz to 30 MHz range. Through the results and simulation, we demonstrate that the effect of non-linear devices may be less of a concern than initially thought, and that simple methods can be employed to control local RF interference.

In practical WLAN deployments, the capture effect has been shown to enhance the performance of stations residing close to the AP, while putting at disadvantage the distant nodes. In this paper, we introduce an analytical model to characterise the performance of 802.11 devices with heterogeneous capture probabilities and different network loads, and explore the interaction between the MAC operation and PHY capture. Unlike previous studies, we reveal that the throughput of stations experiencing low capture probabilities can also benefit from the capture effect when the stations retaining high capture probabilities are not saturated. Following these findings, we design a power-hopping scheme for 802.11 MAC that exploits the benefits of the capture effect to improve performance in dense deployments where nodes experience similar channel conditions. We investigate the potential gains of this mechanism by implementing a practical approximation using commercial off-the-shelf hardware and open-source drivers and, by conducting experiments in a real testbed, we show that our scheme can significantly outperform the standard 802.11 protocol in terms of throughput.

The distribution of passwords chosen by users has implications for site security, password-handling algorithms and even how users are permitted to select passwords. Using password lists from four different web sites, we investigate if Zipf's law is a good description of the frequency with which passwords are chosen. We use a number of standard statistics, which measure the security of password distributions, to see if modelling the data using a simple distribution is effective. We then consider how much the password distributions from each site have in common, using password cracking as a metric. This shows that these distributions have enough high-frequency passwords in common to provide effective speed-ups for cracking passwords. Finally, as an alternative to a deterministic banned list, we will show how to stochastically shape the distribution of passwords, by occasionally asking users to choose a different password.

We consider the sizing of network buffers in IEEE 802.11-based networks. Wireless networks face a number of fundamental issues that do not arise in wired networks. We demonstrate that the use of fixed-size buffers in 802.11 networks inevitably leads to either undesirable channel underutilization or unnecessary high delays. We present two novel dynamic buffer-sizing algorithms that achieve high throughput while maintaining low delay across a wide range of network conditions. Experimental measurements demonstrate the utility of the proposed algorithms in a production WLAN and a lab test bed.

The robustness to noise of the 802.11b/g 5.5 Mb/s and 11 Mb/s rates must be investigated experimentally as they cannot be predicted theoretically. In this paper we report on detailed outdoor and indoor measurements that lead us to the surprising conclusion that the 11 Mb/s 802.11g rate experiences fewer packet losses than the 6 Mb/s 802.11g rate at any given (symbol) SNR. This occurs due to the combination of modulation and physical layer coding schemes used by these rates and has serious implications for rate control algorithms. The practical implications of this, factoring in the interaction between packet loss and 802.11 MAC retries, is that 6 Mb/s is effectively redundant as a packet transmission rate if the 11 Mb/s rate is available.

We propose a powerful MAC/PHY cross-layer approach to measuring IEEE 802.11 transmission opportunities in WLAN networks on a per-link basis. Our estimator can operate at a single station and it is able to: 1) classify losses caused by noise, collisions, and hidden nodes; and 2) distinguish between these losses and the unfairness caused by both exposed nodes and channel capture. Our estimator provides quantitative measures of the different causes of lost transmission opportunities, requiring only local measures at the 802.11 transmitter and no modification to the 802.11 protocol or in other stations. Our approach is suited to implementation on commodity hardware, and we demonstrate our prototype implementation via experimental assessments. We finally show how our estimator can help the WLAN station to improve its local performance.

We identify common hypotheses on which a large number of distinct mathematical models of WLANs employing IEEE 802.11 are founded. Using data from an experimental test bed and packet-level ns-2 simulations, we investigate the veracity of these hypotheses. We demonstrate that several of these assumptions are inaccurate and/or inappropriate. We consider hypotheses used in the modeling of saturated and unsaturated 802.11 infrastructure mode networks, saturated 802.11e networks, and saturated and unsaturated 802.11s mesh networks. In infrastructure mode networks, we find that even for small numbers of stations, common hypotheses hold true for saturated stations and also for unsaturated stations with small buffers. However, despite their widespread adoption, common assumptions used to incorporate station buffers are erroneous. This raises questions about the predictive power of all models based on these hypotheses. For saturated 802.11e models that treat differences in arbitration interframe space (AIFS), we find that the two fundamental hypotheses are reasonable. For 802.11s mesh networks, we find that assumptions are appropriate only if stations are lightly loaded and are highly inappropriate if they are saturated. In identifying these flawed suppositions, this work identifies areas where mathematical models need to be revisited and revised if they are to be used with confidence by protocol designers and WLAN network planners.

As WLANs employing IEEE 802.11 have become pervasive, many analytic models for predicting their performance have been developed in recent years. Due to the complicated nature of the 802.11 MAC operation, approximations must be made to enable tractable mathematical models. In this article, through simulation we investigate the veracity of the approximations shared by many models that have been developed starting with the fundamental hypotheses in Bianchipsilas (1998 and 2000) seminal papers. We find that even for small numbers of station these assumptions that hold true for saturated stations (those that always have a packet to send) and for unsaturated stations with small buffers. However, despite their widespread adoption, we find that the commonly adopted assumptions that are used to incorporate station buffers are not appropriate. This raises questions about the predictive power of models based on these hypotheses.

This paper introduces a finite load multi-class 802.11e EDCF model that is simple enough to be explicitly solvable. The model is nevertheless flexible enough to model the impact of 802.11e parameters on the prioritization of realistic traffic. We emphasize that a modeling framework which allows nonsaturated sources is essential in the study of realistic traffic. We apply the model to a situation of practical interest: competing TCP flows in an infrastructure network. The model allows us to make a principled selection of 802.11e parameters to resolve problems highlighted in this scenario. Model predictions and parameter selections are validated against simulation and experiment. The model is shown to be accurate and the parameters effective.

We consider the medium access control (MAC) layer for very high-speed wireless LANs, which is designed to support rich multimedia applications such as high-definition television. In such networks, the physical (PHY) layer data rate is proposed to exceed 216 Mbps. The legacy MAC layer, however, greatly restricts the performance improvement due to its overhead. It has been shown that MAC utilizes less than 20% of the transportation ability provided by the PHY layer. To mitigate this inefficiency, we propose an aggregation with fragment retransmission (AFR) scheme, which supports transmissions of very large frames and partial retransmissions in the case of errors. Aggregation allows for increased performance despite per-transmission overhead while partial retransmission alleviates the risk of losing the entire frame. Extensive simulations show that AFR fundamentally outperforms the legacy MAC protocol. It is particularly effective for applications with high data rates and large packet sizes such as HDTV and high-rate UDP traffic. For applications with very low data rates and small packet sizes such as voice over IP, AFR performs slightly better.

We consider the possibility of having a (recursive) name server act as a slave to the root zone, rather than caching information after it is requested. Tests, described here, indicate that this technique seems to be comparable to the traditional hints mechanism for moderately busy name servers and may offer other benefits such as reducing the number of bogus requests going to the root servers. With further refinement the technique may be operationally useful, but the impact on root servers would have to be fully assessed.

We derive the moments of the guesswork , the number of attempts required to correctly guess the output of a random source, for a source determined by a Markov chain via a large deviations type estimate. These moments are related to the Perron-Frobenius eigenvalue of the matrix formed by element-wise powers of the Markov chain's transition matrix.