Wading through the noise, or how to make sense of scattered e-mail addresses

‘Making sense of email addresses on drives’  by Neil C. Rowe, Riqui Schwamm, Michael R. McCarrin (U.S. Naval Postgraduade School, Computer Science Department), and Ralucca Gera (Applied Mathematics Department)
Best Paper Award at ICDF2C 2016, 8th EAI International Conference on Digital Forensics & Cyber Crime

Investigators of cyber crime rely on different kinds of physical and digital evidence, and hard drives fall into the category of the most useful. Drives often contain information in the form of email addresses, which can be used to build a picture of the social networks in which the drive owner participated. Information gathered this way is usually more reliable than what we can infer from publicly available data on the actual online social networks, if only because every user has the ability choose what is and what isn’t publicly available. But hard drives and large and there is plenty of noise to wade through if you’re looking for a specific type of information. Thus, the demand for new methods that can filter data based on interestingness is huge.
Thus far, little attention has been paid to mining email addresses from drives, their classification, or their connection to social networks. Work has been done on the classification of email messages from their message headers, but headers provide significantly richer contextual information than lists of email addresses scattered over a drive. What authors of this paper set out to do essentially equates to searching for needles in haystacks, but these needs could hold valuable information.
They have done their work with 2401 drives from 36 countries that represent a range of business, government, and home users, running the Bulk Extractor tool to extract all email addresses, effectively bypassing the file system and searching the raw drive bytes for patterns appearing to be email addreses. This totaled to respectable numbers – 292,347,920 addresses having an average of 28.4 characters per address, of which there were 17,544,550 addresses.
What followed was serious data-crunching. To learn more about the method, test setup, elimination of uninteresting addresses, and visualization of email networks and drive similarities, we recommend getting the full paper here.


Teaching kids Computational Thinking is much easier with tangible objects

‘A Human-Centred Tangible approach to learning Computational Thinking’ by Tommaso Turchi and Alessio Malizia (Human Centred Design Institute, Brunel University London)
EUDL‘s Most Downloaded Paper for the month of August 2016, appears in Issue #9 of EAI Endorsed Transactions on Ambient Systems

Some argue – and they may be very right – that the amount of technology around us, and our understanding of that technology are hugely disproportionate. Computer-like devices are completely ubiquitous and most of us carry at least one with us at all times. However – and this may be credited to very skilled UI designers who have all but removed barriers to entry – as a global user and consumer base, we are losing a grasp on what makes our smartphones and computers tick. With that, we are not only potentially opening ourselves to abuse, but we are starting to lose cognitive skills that created those computers in the first place.
Authors of this paper go so far as to dismiss Computational Thinking as a skill, but instead argue that it is an essential component of literacy in the 21. century. And by Computational Thinking, they do not strictly mean programming skills. Instead, they define it as a range of mental tools reflecting the fundamental principles and concepts of Computer Science, including abstracting and decomposing a problem, recognizing similar ones and being able to generalize their solutions. To reach this new level of literacy, Turchi & Malizia are adamant about teaching these skills derived from Computer Science right from kindergarten, focusing on the K-12 age group.
But having a young child sit down at a computer and start tapping away lines of code simply isn’t a thing that happens. A new set of teaching methods needs to be utilized, one that embraces the principles of Computational Thinking. This is where Visual Programming Environments usually come into play, but a crucial pedagogical step has been skipped by the time childs sits in front of the screen. Unplugged, off-screen activities are used to inspire students and enhance subject knowledge, and can be implemented without the use of computers, making abstract concepts both tangible and visible and improving upon their problem solving skills.
To see how the proposed Tangible Programmable Augmented Surface corresponds to a child’s unique learning reaction to a tangible object, while teaching the much revered Computational Thinking, we recommend getting the full paper for free from EUDL.


Understanding cognitive biases through virtual role-playing

‘Do Warriors, Villagers and Scientists Decide Differently? The Impact of Role on Message Framing’ by J. Siebelink, P. van der Putten (Media Technology, Leiden University), and M. C. Kaptein (Tilburg University)
Best Paper Award at Intetain 2016, 8th International Conference on Intelligent Technologies for Interactive Entertainment

The ‘framing effect’, one of the more well-researched cognitive biases, is one of the central phenomena in the fields of decision-making and behavioral economics. It assumes that choices between logically equivalent alternatives can be influenced by framing the problem in different ways, and it is often used as evidence for irrational or impulsive decision-making.

There are two treatments for a hypothetical outbreak of an Asian disease that infected 600 patients. Treatment A will save 200 patients, while with treatment B, there is a 1/3 probability that everyone will be saved, and a 2/3 chance that nobody will be saved. Alternatively, you can describe, or ‘frame’, the same problem as follows – with treatment A, 400 people will die, while with treatment B, there is a 1/3 probability that nobody will die, and a 2/3 chance that everyone will die.

The ‘Asian Disease Problem’ is a classic example of the risky-choice framing effect. Science tells us that most people will be influenced by whether the problem is described to them as a gain (positive frame – 200 patients will be saved), or a loss (negative frame – 400 patients will die), even if it is the same thing logically.
Although we have a decent understanding of how the framing effect works in everyday life, there are still avenues to be explored when it comes role-playing a virtual character. Authors of this paper set out to investigate how the framing effect changes when a person plays a distinct role with characteristics different from themselves. In a wider perspective, it is an investigation of changes in cognitive processes and decision-making when put into the shoes of a digital persona, the research question being “Does playing an analytic or impulsive character, respectively, influence the susceptibility to the framing effect?” It is an exercise in not only advancing our understanding of cognitive processes, but also exploring new methods of  learning about behavioral psychology.
Researchers had three groups of people play Skyrim – a well-known roleplaying video game, with modifications made to it to create experimental conditions. 86 participants have played as ‘warriors‘, ‘scientists‘, or ‘neutrals‘ (effectively a control group), progressing through a set of tasks in a positive or a negative framing with multiple solutions. Each group had a set of abilities that allowed them to manipulate the world in a certain way, and an expectation was set that the warriors would be more more susceptible to the framing effect and therefore more likely to react impulsively, while the scientists would approach problems analytically, and would therefore be less susceptible to the framing effect.
A fascinating method, certainly. If you would like to learn more and see the results of the study, you can download the full paper for free here.


Minimizing the energy dissipated by wireless sensor nodes

‘Weighted Route Selection in Cluster-Based Protocol for Wireless Sensor Networks’ by Rivo S.A. Randriatsiferana, Herimpitia T.C. Antilahy, Frederic Alicalapa and Richard Lorion
EUDL‘s Most Downloaded Paper for the month of July (2016), appears in Issue #8 of EAI Endorsed Transactions on Future Internet

Technological advancements have come a long way over the decades. Mutual communication between various devices and appliances that we use is nothing unheard of. In fact, humanity has already entered an era of technological convergence, where objects of our every-day life communicate through a network of heterogeneous networks. The basic premise for such evolution is the development of wireless network sensors (WSN). These sensors consist of a set of nodes which communicate with each other over wireless links. For them to function properly, it is essential to mitigate several constraints such as energy consumption and data communication. Since the nodes are small components with limited resources, the most crucial challenge remains to control the energy consumption in order to maximize a network lifetime. Authors of this paper have proposed various protocols to tackle this issue. Among them, the Weighted Route Selection in Cluster-Based Protocol or WeRoS in short, came up as the most efficient protocol, both in terms of energy consumption and extension of the network lifetime.
Generally, WSNs are required to work without human intervention and supervision. This means organizing network into a connected hierarchy — load balancing, thus increasing the network lifetime. To ensure an effective load balance between nodes,  some of them are sometimes elected as leader, which are usually called cluster-heads (CHs). The selection of CHs plays a major role in what is known as clustering process. This process is divided into two main phases:  the cluster construction phase and the data communication phase. There are two possibilities that can be used for the data communication process: one-hop and multi-hop communications.
WeRoS, as proposed by the authors, combined the CH selection rotation and a multi-hop communication for data forwarding and balancing the energy consumption between nodes. The CH selection depends on the remaining energy of the nodes and its coefficient of variation. These parameters are introduced to elect CHs by maximizing the remaining energy as well as minimizing its variance. Furthermore, multi-hop communications generally route data using fixed paths, overusing the nodes closest to Base Station (BS), thus making the signal diminish quickly which results in the existence of energy holes. WeRoS tackled this issue with an algorithm named  “Binary Greedy Forwarding”. It consists of designing an adjacency table between CHs in order to establish communication between CHs and BS which allows for CHs to become self-organized during the data transmission phase. The data is then routed to the BS via an unique path, effectively addressing the energy hole problem.
The authors have demonstrated the superiority of WeRoS via a series of simulation experiments. They compared it with other protocols such as LEACH, LEACH-C, e-LEACH and HEED. These simulations show, that WeRoS exhibits satisfactory comparative performances on energy consumption reduction, nodes synchronous death, and increases the overall network lifetime.
In order to read about the study in greater detail, you can download the full paper on EUDL.


Quantifying gang activity in an urban environment

‘Guns of Brixton: which London neighborhoods host gang activity?’  by Alessandro Venerandi, Giovanni Quattrone, and Licia Capra
Best Paper Award at Urb-IoT 2016, 2nd EAI International Conference on IoT in Urban Space

Street crime and gang activity is a complicated subject that is related to a wide range of economic and social issues, only one of which is the level of education. It has proven to be very difficult to reach widely applicable conclusions as these conditions may vary wildly from neighborhood to neighborhood, not to mention from country to country. But there are ways of framing this subject within rigid, quantifiable data. Authors of this paper have successfully quantified the relationship between urban form (density and connectivity of built environment, and house typologies) and crime activity by using Open data as input and by taking the metropolitan area of London as case study.
As the they elaborate: “We identify a set of descriptors which are able to capture multiple aspects of the built environment such as build period, type and fiscal band of dwellings, place accessibility, and street network connectivity. We extract measures to describe the built environment from Ordnance Survey (OS) VectorMap District and the London Datastore (i.e., the official web portal for statistical information on Greater London). We derive the areas where gangs currently operate from a geodataset made publicly available on an online article by the Independent. The information contained in that dataset was gathered through an interview which saw the involvement of an ex-sergeant of the London Metropolitan Police. Having computed the measures and assigned presence or absence of gang activity to the different areas of London, we perform step-wise logistic regression to obtain a parsimonious set of descriptors of the urban environment which are significantly associated with the activity of criminal groups.”
This brings us closer to understanding how crime develops in neighborhoods, indirectly pointing us towards ways of lowering compatibility with crime by design. If you would like to learn more, you can find the full paper for free here.


On a quest to protect industrial control systems from cyber attacks

‘Attribution of Cyber Attacks on Industrial Control Systems’ by Allan Cook, Andrew Nicholson, Helge Janicke, Leandros Maglaras, and Richard Smith
EUDL‘s Most Downloaded Paper for the month of June (2016), appears in Issue #7 of EAI Endorsed Transactions on Industrial Networks and Intelligent Systems

Industrial Control Systems (ICS) are a big deal. They provide essential services for critical national or organizational infrastructure, and to compromise them means to compromise the continued security of these countries. They are responsible for the management of processes that, if not executed correctly, pose a significant risk to the health and safety of human lives, serious damage to the environment, as well as serious financial issues such as production losses that may have a negative impact on a nation’s economy. As such, they are increasingly becoming the subject of computer network attacks, which could have devastating consequences.
The authors of this paper have put together a survey of technical attribution techniques specifically related to ICS in order to create a single self-containing attribution resource that is useful for new researchers to the field. The survey is first of its kind, as previous attack taxonomies used for contemporary attribution do not accommodate methods to integrate data from cyber-physical systems such as ICS, and the existing information is very scattered.
Attribution of cyber attacks is a crucial component of prosecution, as it defines the type of attack, so that international law enforcement agencies or national governments can decide on appropriate recourse. Attribution also serves to act as a deterrent to future attacks, can provide the basis for interrupting attacks in progress and can support overall improvements to defensive techniques.
If you wish to learn more, you can download the full paper for free on EUDL.


Video: Laurent Ros and Fabrice Belveze – Best Paper Award at CROWNCOM 2016

‘Performance of Fractional Delay Estimation in Joint Estimation Algorithm Dedicated to Digital Tx Leakage Compensation in FDD Transceivers’  by Robin Gerzaguet, Laurent Ros, Fabrice Belveze, and Jean-Marc Brossier
Best Paper Award at CROWNCOM 2016, 11th EAI International Conference on Cognitive Radio Oriented Wireless Networks

Abstract: This paper deals with the performance of the fractional delay estimator in the joint complex amplitude/delay estimation algorithm dedicated to digital Tx leakage compensation in FDD transceivers. Such transceivers are affected from transmitter-receiver signal leakage. Combined with non-linearity of components in the received path, it leads to a pollution in the baseband signal. The baseband polluting term depends on the equivalent Tx leakage channel, modeling leakages and the received path. We have proposed a joint estimation of the complex gain and the fractional delay and derived asymptotic performance of the complex gain estimator, that showed the necessity of the fractional delay estimation. In this paper, we propose a comprehensive study of the fractional delay estimation algorithm and its analytic performance. The study is based on the analysis of the S-curve and loop noise variance of the timing error detector, from which an approximation of the asymptotic performance of the joint estimation algorithm is derived.
If you want to learn more, the full paper is available to download via EUDL.


Developing a resource management scheme to keep the Cloud afloat

‘Dynamic Virtual Machine Consolidation for Energy Efficient Cloud Data Centers’  by Dong-Ki Kang, Fawaz Alhazemi, Seong-Hwan Kim, and Chan-Hyun Youn (School of Electrical Engineering, KAIST, Daejeon, Korea)
Best Paper Award at CLOUDCOMP 2015, 6th EAI International Conference on Cloud Computing

It doesn’t need saying that globally, we do a lot of computing every single day. What does need saying is that data centers and server infrastructures consume crazy amounts of energy. And the trend isn’t showing signs of stopping. On the contrary, cloud computing has officially stepped into the mainstream and global bandwidth demands increase steadily. Sustainability and evironmental aspects aside, energy consumption makes a severe dent in the budget of any operation. As stated in the paper, some reports estimate that the “cost of power and cooling has increased 400% over 10 years, and 59% of data centers identify them as key factors limiting server deployments.” Authors of this paper have set out to tackle this spreading issue by consolidating resource allocation dynamically with a Virtual Machine (VM).
Firstly though, let’s introduce the most popular method for achieving highest possible energy efficiency in data centers – Dynamic Right Sizing (DRS). DRS essentialy turns off idle servers, but there is more to it than that. To maximize the efficiency via DRS, one of primary adaptive resource management strategies is a Virtual Machine consolidation, in which running VM instances can be dynamically integrated into the minimal number of cloud servers in accordance with their resource utilization collected by hypervisor monitoring module. That is, running VM instances on under-utilized servers which are supposed to be turned off could be migrated to power-sustainable servers.
However, cloud users are many, and and their resource demands differ. Reckless switching of servers in high volume could lead to undesirable performance degradation. To achieve the demanded Quality of Service, authors of this paper have devised a careful resource management scheme which considers switching overheads. They propose a management system called Self Adjusting Workload Prediction to increase the prediction accuracy of users’ future demands even under irregular workload patterns. The method adaptively scales the history window size up or down according to extracted workload’s autocorrelations and sample entropies which measure periodicity and burstiness of workloads.
To learn more about how the system works and to see how the tests went, we recommend getting the full paper on EUDL.
CLOUDCOMP 2016 is still accepting papers! Learn more on the conference website.


Sleep and fall detection in a single device will aid tomorrow's elderly

‘Elderly Monitoring System with Sleep and Fall Detector’  by Abdulakeem OdunmbakuAmir-Mohammad RahmaniPasi Liljeberg, and Hannu Tenhunen
Best paper at HealthyIoT 2015, 2nd EAI International Conference on IoT Technologies for Health Care 

Western population is growing old. While we don’t usually describe the aging prognosis as a ‘demographic crisis’, our current trajectory certainly has a lot of people worried.  The population of the 60 and over age group is expected to reach 1.2 billion by the year 2025, and 2 billion by 2050, and regardless of how accurate these prognoses are, the trend is an undisputable fact. And it is about to put extreme pressure on our health care infrastructure. As the authors point out (and tackle the issue directly with a system design), IoT-powered technology will need to be one of the pillars that takes a load off of human resources – if the elderly are to be taken care of.
Two main activities in the elderly population have been put forward in previous research as activites that are relatively easy to track, but have significant value for diagnosis and crisis detection. Sleep monitoring and fall detection are two aspects which have been a focal point of many applications in the past already. Since low quality of sleep can lead to extensive health problems (such as high blood pressure), it can be a telling ambient indicator. Furthermore, a simple fall can result in a permanent handicap for an elderly person, especially when not treated immediately. Efficient fall detection can thus be a crucial element in preventing critical conditions for the elderly.
While assistive technologies have focused on either one or the other in the past, the authors of this paper set out to combine the two into a single device – one that is non-obtrusive, autonomous, and accessible.
The authors have chosen accelerometer to be the central component of their system – with very intuitive reasoning in terms of fall detection – and under the principle that the brain activity during sleep is equal to the motion produced by the body during sleep. The device’s requirements for both of these cases is simple – it needs to be attached to the body. An internet-connected smart watch was used for the prototype of this design, which also keeps the cost of the device relatively low – not having to develop a custom device from scratch.
If you wish to take a closer look at the back-end architecture of the system, the method of testing, and the results, you can get the full paper on ResearchGate.
This year’s edition of the conference, HealthyIoT 2016, is accepting submission until July 10th!


Context-awareness improved with novel method of clustering objective interestingness

‘Clustering the objective interestingness measures based on tendency of variation in statistical implications’ by Ngia Quoc Phan, Vinh Cong Phan, Hung Huu Huynh, Hiep Xuan Huynh

Second most downloaded paper from EUDL for May 2016, from Issue 9 of EAI Endorsed Transactions on Context-Aware Systems and Applications

You can read about the most downloaded paper for January and May 2016 here.

Objective interestingness is a crucial factor in all context-aware systems as is self-evident from its name. The success of recognizing important and relevant environmental cues hinges on the system’s ability to evaluate that relevance. This is especially important in the post-processing stage of data mining. The list of methods to measure objective interestingness is long and keeps growing, and plus, different methods work better in different situations. This paper proposes a method of clustering measures of objective interestingness based on tendency of variation in statistical implications.

This new approach uses a hierarchical structure of similarity tree to cluster the objective interestingness measures with agreed assymetrical properties. The results of tendency variation in statistical implications are based on partial derivatives of the calculated function of measures on each parameter to build a distance matrix of the measures. As a result, each cluster is a group of measures that have proximity or similarity to each other. This enables users to better choose appropriate measure for their application.

Want to know the details? Get the full paper for free on EUDL.