Programs for machine learning. Part II

Part I of this paper described the community unit as one of the indirect and implicit means we employ in specifying the behavior of a proposed learning system. It has been pointed out that, for complex problems, the community unit's vision tends to be too narrow and restricted because of its piecemeal manner of attacking problems.This second part of the paper describes a planning mechanism which attempts to overcome this difficulty by taking a larger view of a given task. After surveying the task in general, the planning mechanism subdivides the task into a hierarchy of subtasks each by itself presumably easier to perform than the original task. This hierarchy of subtasks comprises a rough sketch of a possible course of action which guides the community unit.To manage classes of problems and to make efficient use of past experience, an induction mechanism is proposed. The induction mechanism will take a still larger view by considering the system's past experience with various problems and by attempting to apply that experience to related problems which have not previously been encountered

Management and Service-aware Networking Architectures (MANA) for Future Internet Position Paper: System Functions, Capabilities and Requirements

Future Internet (FI) research and development threads have recently been gaining momentum all over the world and as such the international race to create a new generation Internet is in full swing: GENI, Asia Future Internet, Future Internet Forum Korea, European Union Future Internet Assembly (FIA). This is a position paper identifying the research orientation with a time horizon of 10 years, together with the key challenges for the capabilities in the Management and Service-aware Networking Architectures (MANA) part of the Future Internet (FI) allowing for parallel and federated Internet(s)

Inside Dropbox: Understanding Personal Cloud Storage Services

Personal cloud storage services are gaining popularity. With a rush of providers to enter the market and an increasing of- fer of cheap storage space, it is to be expected that cloud storage will soon generate a high amount of Internet traffic. Very little is known about the architecture and the perfor- mance of such systems, and the workload they have to face. This understanding is essential for designing efficient cloud storage systems and predicting their impact on the network. This paper presents a characterization of Dropbox, the leading solution in personal cloud storage in our datasets. By means of passive measurements, we analyze data from four vantage points in Europe, collected during 42 consecu- tive days. Our contributions are threefold: Firstly, we are the first to study Dropbox, which we show to be the most widely-used cloud storage system, already accounting for a volume equivalent to around one third of the YouTube traffic at campus networks on some days. Secondly, we characterize the workload typical users in different environments gener- ate to the system, highlighting how this reflects on network traffic. Lastly, our results show possible performance bot- tlenecks caused by both the current system architecture and the storage protocol. This is exacerbated for users connected far from control and storage data-center

Analyzing FSA Direct Loan Borrower Payback Histories: Predictors of Financial Improvement and Loan Servicing Actions

Classical and count data regression models are estimated to predict improvement in three key financial indicators—net worth, debt-to-asset ratio and current ratio—as well as the number of loan restructurings and delinquencies. Data consist of Farm Service Agency direct loans originated in fiscal years 1994-1996. Models to predict outcomes vary by loan type. Models explaining variation in the financial measures have modest explanatory power but initial levels of debt-to-asset ratio and current ratio are significant in explaining changes in debt-to-asset ratios and current ratios, respectively. Models explaining number of restructurings and delinquencies for operating loans have satisfactory explanatory power. Increasing crop revenues to total farm revenues and increasing farm size lead to increased loan servicing actionsFSA direct loans, financial improvement, loan servicing actions, Agricultural Finance, Farm Management, q14, q12,

MikroTik Devices Landscape, Realistic Honeypots, and Automated Attack Classification

In 2018, several malware campaigns targeted and succeed to infect millions of low-cost routers (malwares e.g., VPN-Filter, Navidade, and SonarDNS). These routers were used, then, for all sort of cybercrimes: from DDoS attacks to ransomware. MikroTik routers are a peculiar example of low-cost routers. These routers are used to provide both last mile access to home users and are used in core network infrastructure. Half of the core routers used in one of the biggest Internet exchanges in the world are MikroTik devices. The problem is that vulnerable firmwares (RouterOS) used in homeusers houses are also used in core networks. In this paper, we are the first to quantify the problem that infecting MikroTik devices would pose to the Internet. Based on more than 4 TB of data, we reveal more than 4 million MikroTik devices in the world. Then, we propose an easy-to-deploy MikroTik honeypot and collect more than 17 millions packets, in 45 days, from sensors deployed in Australia, Brazil, China, India, Netherlands, and the United States. Finally, we use the collected data from our honeypots to automatically classify and assess attacks tailored to MikroTik devices. All our source-codes and analysis are publicly available. We believe that our honeypots and our findings in this paper foster security improvements in MikroTik devices worldwide

The Internet of Names: A DNS Big Dataset - Actively Measuring 50% of the Entire DNS Name Space, Every Day

The Domain Name System (DNS) is part of the core infrastructure of the Internet. Tracking changes in the DNS over time provides valuable information about the evolution of the Internet’s infrastructure. Until now, only one large-scale approach to perform these kinds of measurements existed, passive DNS (pDNS). While pDNS is useful for applications like tracing security incidents, it does not provide sufficient information to reliably track DNS changes over time. We use a complementary approach based on active measurements, which provides a unique, comprehensive dataset on the evolution of DNS over time. Our high-performance infrastructure performs Internet-scale active measurements, currently querying over 50% of the DNS name space on a daily basis. Our infrastructure is designed from the ground up to enable big data analysis approaches on, e.g., a Hadoop cluster. With this novel approach we aim for a quantum leap in DNS-based measurement and analysis of the Internet

Role of Social Capital on Uptake of Sustainable Agricultural Intensification Practices’ Combinations

Smallholder farmers in sub-Saharan Africa are faced with many challenges in the production of maize and legumes. Some of the challenges include soil mining, drought, soil erosion, input acquisition among others. These challenges cannot be alleviated with the adoption of a single agricultural practice but a bundle of combination. There was need, therefore, to evaluate if social capital among other factors influences adoption of the different combination of the six Sustainable Agricultural Intensification Practices among smallholder maize-legume systems in Kenya. The study used secondary data from Adoption Pathway project panel dataset collected from Bungoma, Siaya, Meru, Tharaka Nithi and Embu counties, in three waves:  covering 613 households in the baseline, 535 in the midline and 495 in the end line was used in the analysis. Eighteen possible combinations adopted by smallholder farmers, a Principal Component Analysis was used to reduces data dimensionality, such that Seven possible clusters were formed that were homogeneous within. An index of the different combinations in the cluster was then formed for each household. Using STATA software, a Seemingly Unrelated Regression model was used in the analysis of the seven equations against a set of dependent variables, among them social capital. The findings of the study showered that social capital is not significant in explaining adoption of different combinations of SAIPs that a household adopted except for cognitive social capital and participation level in group institutions where the household was a member. Other factors that influenced adoption of combination of SAIPs included age of the household head, received information about SAIP and input markets, amount of money that a household got as income and that which they saved. Additionally, the spatial distance of the farming plot measured as the number of walking minutes from the household homestead and the number of years one has been living in the village practicing maize-legume production also significantly influenced the combinations of the SAIPs that a household adopted. Policy interventions should encourage and promote better access to information and encourage participation in group institutions. Keywords: Principal Component Analysis, Clusters, Seemingly Unrelated Regressio

Characterising attacks targeting low-cost routers: a MikroTik case study (Extended)

Attacks targeting network infrastructure devices pose a threat to the security of the internet. An attack targeting such devices can affect an entire autonomous system. In recent years, malware such as VPNFilter, Navidade, and SonarDNS has been used to compromise low-cost routers and commit all sorts of cybercrimes from DDoS attacks to ransomware deployments. Routers of the type concerned are used both to provide last-mile access for home users and to manage interdomain routing (BGP). MikroTik is a particular brand of low-cost router. In our previous research, we found more than 4 million MikroTik routers available on the internet. We have shown that these devices are also popular in Internet Exchange infrastructures. Despite their popularity, these devices are known to have numerous vulnerabilities. In this paper, we extend our previous analysis by presenting a long-term investigation of MikroTik-targeted attacks. By using a highly interactive honeypot that we developed, we collected more than 44 million packets over 120 days, from sensors deployed in Australia, Brazil, China, India, the Netherlands, and the United States. The incoming traffic was classified on the basis of Common Vulnerabilities and Exposures to detect attacks targeting MikroTik devices. That enabled us to identify a wide range of activities on the system, such as cryptocurrency mining, DNS server redirection, and more than 3,000 successfully established tunnels used for eavesdropping. Although this research focuses on Mikrotik devices, both the methodology and the publicly available scripts can be easily applied to any other type of network device

Aquatic Exercise for Better Living on Land: Impact of Shallow-Water Exercise on Older Japanese Women for Performance of Activities of Daily Living (ADL)

Twenty-six Japanese women (70.5 yr) self-selected water exercise (WEX) (n=13), or control (CON) (n=13) for 12 weeks. WEX was performed 60-minutes/day, 3 days/week with warm-up, cool-down stretch, ADL exercises, and cardiovascular/muscular endurance in 30°C water at a xiphoid level depth. CON continued their current activity/nutrition patterns. Compared to CON, WEX improved (p\u3c.05) functional fitness and balance measures including arm curl (22%), chair stand (21%), 8-feet up & go (13%), chair sit/reach (50%), and 12-min walk (15%). No significant changes in sway velocity (SV) or limits of stability (LOS) were seen for either group. This shallow water exercise improved land-based ADL for older women but not balance. ADL tasks associated with balance did improve which may have indicated enhanced motor control