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Decision support to prevent cyber attacks

Recognising the complexity of cyber attacks and the multi-stakeholder nature of tackling cyber security are the key components of a new data-driven cyber security system being developed by experts led by the University of Nottingham. The aim is to support organisations of all sizes in maintaining adequate levels of cyber security through a semi-automatic, regularly updated, organisation-tailored security assessment of their digital infrastructures.

The £1 million project, funded by the Engineering and Physical Sciences Research Council (EPSRC) and the National Cyber Security Centre (formerly CESG), will establish the foundations for a digital ‘Online Cyber Security System’ decision support service (OCYSS) which is designed to rapidly bring together information on system vulnerabilities and alert organisations which may be affected.

The interdisciplinary project brings together academics in different areas of cyber security, information integration and decision making from the University of Nottingham, UK and Carnegie Mellon University, USA. They will be working closely with the UK’s National Cyber Security Centre.

Dr Christian Wagner, from the School of Computer Science at the University of Nottingham, who is currently also a visiting professor at Michigan Technological University, USA, is the lead academic. He said: “While the UK has access to some of the world’s leading experts in cyber security, the scale and variety of systems in UK organisations, both public and private, make it extremely challenging to flag potential system threats in a timely fashion. This international collaborative project targets a novel approach to semi-automatically identify system vulnerabilities, thus greatly increasing the efficiency and capacity to respond to emerging threats.” Also involved as co-investigators are Prof. Garibaldi, who has previously worked with the team at CESG on modelling expert decision making, and Prof. McAuley, who is Director of the Horizon Digital Economy Hub and has specific expertise in security and privacy research.

The UK cyber security sector already has world-leading capabilities and is worth over £6 billion, employing 40,000 people. Cyber attacks are increasing in severity and sophistication and companies are struggling to recruit the expertise needed to defend their organisations.

Cyber security underpinned with scientific expertise

The system will be designed to directly address the acute shortage of availability and access to highly qualified cyber security experts by small-to-large scale organisations — from government to industry.

Dr Wagner notes: “The lack of sufficient access to highly trained and experienced cyber security experts is a key challenge for the UK. It prevents a range of users from establishing and maintaining continuously adequate levels of protection of their assets in a rapidly changing security landscape. We view this challenge as a multi-stakeholder problem because a number of human stakeholders, from users and IT managers, with varying levels of expertise, to cyber security and software providers, need to effectively communicate and work together in order to deliver systems with an appropriate level of cyber security assurance.”

System detects riots far quicker than police reports

An analysis of data taken from the London riots in 2011 showed that computer systems could automatically scan through Twitter and detect serious incidents, such as shops being broken in to and cars being set alight, before they were reported to the Metropolitan Police Service.

The computer system could also discern information about where the riots were rumoured to take place and where groups of youths were gathering.

The study comes just days after the Chief Constable of West Midlands Police claimed that police would face “real challenges” tackling a repeat of the 2011 riots following years of budget cuts.

The new research, published in the peer-review journal ACM Transactions on Internet Technology, showed that on average the computer systems could pick up on disruptive events several minutes before officials and over an hour in some cases.

The researchers believe that their work could enable police officers to better manage and prepare for both large and small scale disruptive events.

Co-author of the study Dr Pete Burnap, from Cardiff University’s School of Computer Science and Informatics, said: “We have previously used machine-learning and natural language processing on Twitter data to better understand online deviance, such as the spread of antagonistic narratives and cyber hate.

“In this research we show that online social media are becoming the go-to place to report observations of everyday occurrences — including social disorder and terrestrial criminal activity. We will never replace traditional policing resource on the ground but we have demonstrated that this research could augment existing intelligence gathering and draw on new technologies to support more established policing methods.”

Scientists are continually looking to the swathes of data produced from Twitter, Facebook and YouTube to help them to detect events in real-time.

Estimates put social media membership at approximately 2.5 billion non-unique users, and the data produced by these users have been used to predict elections, movie revenues and even the epicentre of earthquakes.

n their study the research team analysed 1.6m tweets relating to the 2011 riots in England, which began as an isolated incident in Tottenham on August 6 but quickly spread across London and to other cities in England, giving rise to looting, destruction of property and levels of violence not seen in England for more than 30 years.

Technology video advertising might be linked to less diverse workforce

Consumer tech companies that are serious about attracting more women and people from minority groups into their workforce might want to revisit the video advertisements featured on their websites. Although these ads do not explicitly discourage women and girls, or people of color, from pursuing the fields of computer science, they do little to present technologies as accessible to those who do not fit the dominant white male ideal. This is according to Subriena Persaud of George Mason University in the US, lead author of a study in Springer’s journal Gender Issues that analyzed how gender, race and age are portrayed in the videos of nine major consumer technology companies.

Six videos advertising products and services (54 videos in total) were obtained from the websites of well-known tech companies. Persaud and her research associates team noted the gender and race of each character featured, and looked at the videos as a whole to see how the characters fit into the story lines and how gender roles are portrayed.

Women, the elderly, racial/ethnic minorities, and even children (who are otherwise commonly used in advertising) were all found to be under-represented in the portrayals. According to the researchers, the emotionality and passivity of women in most of the advertisements analyzed perpetuates the idea that women are not in control of the creation and usage of technology.

“Instead, technology itself is portrayed in masculinist terms — powerful, fast, strong, active — thereby reinforcing this association,” explains Persaud, who says that males are shown to be more in control, enfolding others, taking and using products in the presence of others, and also being the provider of these products and services. “This is interesting in light of the fact that the devices advertised are inherently fragile and breakable, which could logically be deemed more appropriate to the culturally perceived delicateness and gentleness of feminine hands. However, the fragility of the technology has been converted into requiring not a delicate touch, but a competent, skillful hand.”

This leaves the impression that marketers aim their technology products and services at adult, white men and that these images serve to reinforce the association between masculinity and technology. Persons of color, women, girls, and boys do appear in these advertisements but their presence is less obvious and central than middle-aged or young-adult white men.

“These images reinforce hegemonic ideals and reinforce the association between technology and masculinity, as well as whiteness and youth,” says Persaud.

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Privacy in electronic healthcare systems

All over the world, digital tools are increasingly being used to improve and streamline healthcare services. This does not only lead to positive results, but also creates opportunities for new types of threats regarding information security and privacy.

Information security and protection of privacy are some of the most important factors in the development of high-quality tools in the healthcare sector. If no attention is paid to these aspects, there is substantial risk that individuals may come to harm in healthcare situations. Leonardo Iwaya, PhD student in computer science at Karlstad University, explores ways of securing information and protecting privacy when using mobile applications in healthcare (mHealth).

“Mobile apps are for example used in developing countries to increase the coverage and the access to public healthcare,” says Leonardo Iwaya. “But many projects fail because issues related to data security and privacy cannot be successfully integrated in the systems.”

For instance, in Brazil, mHealth tools have been used by community health workers to improve patients’ treatment in poor and rural areas, strengthening the link between the society and the public health system. These patients often have limited possibilities to visit healthcare clinics and the project instead involved healthcare workers visiting patients at home. Smartphones are, for example, used to streamline the handling of journals. Information gathered during a visit is also used to analyse the impact of the conditions in the specific areas on people’s health, so that more prevention work can be done.

Wires of polymers chains

As conventional silicon-integrated circuits reach their lower size limit, new concepts are required such as molecular electronics — the use of electronic components comprised of molecular building blocks. Shuo-Wang Yang at A*STAR Institute of High Performance Computing together with his colleagues and collaborators, are using computer modeling to design electric wires made of polymer chains.

“It has been a long-standing goal to make conductive molecular wires on traditional semiconductor or insulator substrates to satisfy the ongoing demand miniaturization in electronic devices,” explains Yang.

Progress has been delayed in identifying molecules that both conduct electricity and bind to substrates. “Structures with functional groups that facilitate strong surface adsorption typically exhibit poor electrical conductivity, because charge carriers tend to localize at these groups,” he adds.

Yang’s team applied density functional theory to a two-step approach for synthesizing linear polymer chains on a silicon surface. “This theory is the best simulation method for uncovering the mechanism behind chemical reactions at atomic and electronic levels. It can be used to predict the reaction pathways to guide researchers,” says Yang.

The first step is the self-assembled growth of single monomers on to the silicon surface. Yang’s team studied several potential monomers including, most recently, a thiophene substituted alkene and a symmetrical benzene ring with three alkynes attached. The second step is the polymerization of the tethered monomers by adding a radical to the system.

According to the calculations, these tethered polymers are semiconductors in their natural state. “We introduced some holes, such as atomic defects, to the wires to shift the Fermi levels and make them conductive,” Yang explains.

The team then studied the electron band structures of each component before and after tethering and polymerization; finding little charge transfer between the molecular wires and the silicon surfaces. “The surface-grafted polymers and underlying substrates seem independent of each other, which is an ideal model of a conductive molecular wire on a traditional semiconductor substrate,” says Yang.

“Our finding provides a theoretical guide to fabricating ideal molecular wires on traditional semiconducting surfaces,” he adds. The team is plans to extend their work to study 2D analogs of these 1D polymer chains that could work as a metallic layer in molecular electronic devices.

Personal care robots about human poses

Expectations for care robots are growing against the backdrop of declining birthrates, an aging population, and a lack of care staff. As an example, for care at nursing homes and other such facilities, it is anticipated that robots will check the condition of the residents while patrolling the facility. When evaluating a person’s condition, while an initial estimation of the pose (standing, sitting, fallen, etc.) is useful, most methods to date have utilized images. These methods face challenges such as privacy issues, and difficulties concerning application within darkly lit spaces. As such, the research group (Kaichiro Nishi, a 2016 master’s program graduate, and Professor Miura) has developed a method of pose recognition using depth data alone.

For poses such as upright positions and sitting positions, where body parts are able to be recognized relatively easily, methods and instruments which can estimate poses with high precision are available. In the case of care, however, it is necessary to recognize various poses, such as a recumbent position (the state of lying down) and a crouching position, which has posed a challenge up until now. Along with the recent progress of deep learning (a technique using a multistage neural network), the development of a method to estimate complex poses using images is advancing. Although deep learning requires preparation of a large amount of training data, in the case of image data, it is relatively easy for a person to see each part in an image and identify it, with some datasets also having been made open to the public. In the case of depth data, however, it is difficult to see the boundaries of parts, making it difficult to generate training data.

As such, this research has established a method to generate a large amount of training data by combining computer graphics (CG) technology and motion capture technology. This method first creates CG data of various body shapes. Next, it adds to the data information of each part (11 parts including a head part, a torso part, and a right upper arm part), and skeleton information including each joint position. This makes it possible to make CG models take arbitrary poses simply by giving the joint angles using a motion capture system.

Three dimensional chip combines computing and data storage

As embedded intelligence is finding its way into ever more areas of our lives, fields ranging from autonomous driving to personalized medicine are generating huge amounts of data. But just as the flood of data is reaching massive proportions, the ability of computer chips to process it into useful information is stalling.

Now, researchers at Stanford University and MIT have built a new chip to overcome this hurdle. The results are published in the journal Nature, by lead author Max Shulaker, an assistant professor of electrical engineering and computer science at MIT. Shulaker began the work as a PhD student alongside H.-S. Philip Wong and his advisor Subhasish Mitra, professors of electrical engineering and computer science at Stanford. The team also included professors Roger Howe and Krishna Saraswat, also from Stanford.

Computers today comprise different chips cobbled together. There is a chip for computing and a separate chip for data storage, and the connections between the two are limited. As applications analyze increasingly massive volumes of data, the limited rate at which data can be moved between different chips is creating a critical communication “bottleneck.” And with limited real estate on the chip, there is not enough room to place them side-by-side, even as they have been miniaturized (a phenomenon known as Moore’s Law).

To make matters worse, the underlying devices, transistors made from silicon, are no longer improving at the historic rate that they have for decades.

The new prototype chip is a radical change from today’s chips. It uses multiple nanotechnologies, together with a new computer architecture, to reverse both of these trends.

Instead of relying on silicon-based devices, the chip uses carbon nanotubes, which are sheets of 2-D graphene formed into nanocylinders, and resistive random-access memory (RRAM) cells, a type of nonvolatile memory that operates by changing the resistance of a solid dielectric material. The researchers integrated over 1 million RRAM cells and 2 million carbon nanotube field-effect transistors, making the most complex nanoelectronic system ever made with emerging nanotechnologies.

The RRAM and carbon nanotubes are built vertically over one another, making a new, dense 3-D computer architecture with interleaving layers of logic and memory. By inserting ultradense wires between these layers, this 3-D architecture promises to address the communication bottleneck.

However, such an architecture is not possible with existing silicon-based technology, according to the paper’s lead author, Max Shulaker, who is a core member of MIT’s Microsystems Technology Laboratories. “Circuits today are 2-D, since building conventional silicon transistors involves extremely high temperatures of over 1,000 degrees Celsius,” says Shulaker. “If you then build a second layer of silicon circuits on top, that high temperature will damage the bottom layer of circuits.”

The key in this work is that carbon nanotube circuits and RRAM memory can be fabricated at much lower temperatures, below 200 C. “This means they can be built up in layers without harming the circuits beneath,” Shulaker says.

This provides several simultaneous benefits for future computing systems. “The devices are better: Logic made from carbon nanotubes can be an order of magnitude more energy-efficient compared to today’s logic made from silicon, and similarly, RRAM can be denser, faster, and more energy-efficient compared to DRAM,” Wong says, referring to a conventional memory known as dynamic random-access memory.

Global study of physical activity

The large-scale study of daily step data from anonymous smartphone users dials in on how countries, genders, and community types fare in terms of physical activity and what results may mean for intervention efforts around physical activity and obesity. The study was published July 10, 2017, in the advance online edition of Nature.

“Big data is not just about big numbers, but also the patterns that can explain important health trends,” said Grace Peng, Ph.D., director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) program in Computational Modeling, Simulation and Analysis.

“Data science and modeling can be immensely powerful tools. They can aid in harnessing and analyzing all the personalized data that we get from our phones and wearable devices.”

Almost three quarters of adults in developed countries and half of adults in developing economies carry a smartphone. The devices are equipped with tiny accelerometers, computer chip that maintains the orientation of the screen, and can also automatically record stepping motions. The users whose data contributed to this study subscribed to the Azumio Argus app, a free application for tracking physical activity and other health behaviors.

In their study, Scott L. Delp, Ph.D., James H. Clark Professor of Bioengineering and director of the Mobilize Center at Stanford University, and colleagues analyzed 68 million days of minute-by-minute step recordings from 717,527 anonymous users of the smartphone app. Participation spanned 111 countries, but the researchers focused their study on 46 countries, each with at least 1,000 users. Of those, 90 percent of users were from 32 high income countries and 10 percent were from 14 middle income countries. The Stanford Mobilize Center is an NIH Big Data 2 Knowledge Center of Excellence.

“The study is 1,000 times larger than any previous study on human movement,” said Delp. “There have been wonderful health surveys done, but our new study provides data from more countries, many more subjects, and tracks people’s activity on an ongoing basis in their free-living environments versus a survey in which you rely on people to self-report their activity. This opens the door to new ways of doing science at a much larger scale than we have been able to do before.”

In addition to the step records, the researchers accessed age, gender, and height and weight status of users who registered the smartphone app. They used the same calculation that economists use for income inequality — called the Gini index — to calculate activity inequality by country.

“These results reveal how much of a population is activity-rich, and how much of a population is activity-poor,” Delp said. “In regions with high activity inequality there are many people who are activity poor, and activity inequality is a strong predictor of health outcomes.”

Globally, the average user recorded about 5,000 steps per day. The smartphone data reflected the degree of difference, or inequality, for activity among people within a given country. By comparing countries with more uniform activity patterns and those with unequal activity, certain patterns and health dynamics emerged. For instance, countries with the greatest activity inequality are also the countries with the greatest obesity problem. Individuals in the five countries with the greatest activity inequality are nearly 200 percent more likely to be obese than individuals from the five countries with the lowest activity inequality.

The average activity — measured in steps counted by smartphone accelerometers — is equivalent for people in the United States and Mexico, for example. But individuals in the United States reflect a wider range of activity levels than those in Mexico. This wider gap between active and sedentary people corresponds with higher prevalence of obesity in the United States overall.

The authors suggest that this inequality is an important target for obesity intervention. Using a computer simulation, they showed that targeted interventions could result in up to a four times greater reduction in obesity than non-targeted approaches.

Decision making rules least susceptible to manipulation

HSE researchers have used computer modelling to demonstrate the varying manipulability of decision-making procedures and to identify those least susceptible to manipulation. Their findings are published in the paper ‘Manipulability of Majority Relation-based Collective Decision Rules’.

In selecting one of several possible options, people can use a range of different rules (procedures) for collective decision-making. While there are about 30 such rules in total, important elections, such as voting for presidents, members of government, heads of corporations and banks, etc., normally use majority voting systems in which the winner is chosen by a majority vote.

The relative majority voting rule is the most well-known one, but there are also absolute and qualified majority voting systems. Under the relative majority system, a candidate needs to receive more votes than any of their opponents, but not necessarily more than half of all votes. This system is currently used in the UK and Japan, in Congressional elections in the US, and in voting for State Duma seats in single-member constituencies in Russia.

The relative majority voting rule leaves plenty of room for manipulation. For example, a voter may prefer option A, but understands that by voting for A, they may increase C’s likelihood of winning, C being the least preferable option for them; so instead they modify their ballot by selecting B, which is not their option of choice but better than C. By voting strategically, they hope to defend their opinion better.

“We assume here that the voter initiates such manipulation and shall leave aside the question as to how they arrive at this decision and whether they have been advised by someone else to vote tactically. We are only interested in the possibility of someone seeing the benefit in making an insincere choice,” comments Daniel Karabekyan, one of the authors of the paper.

A real-life example of large-scale manipulation was the 1993 parliamentary election in Russia, where the LDPR received 24% of seats. Although most experts had predicted with confidence — and publicised it everywhere — that Gaidar’s party would win by a wide margin, many people voted tactically for the LDPR — not necessarily because it was their party of choice, but in order to have opposition politicians represented in parliament.

In fact, political practice and research both reveal that the majority voting rule is not the only one which is manipulable. In the early 1970s, two American authors, Allan Gibbard and Mark Satterthwaite, independently published mathematical proof that any voting rule must be manipulable, as voters can always modify their ballot to defend their opinion better.