Performance evaluation of cyber-physical intrusion detection on a robotic vehicle

Intrusion detection systems designed for con- ventional computer systems and networks are not necessarily suitable for mobile cyber-physical systems, such as robots, drones and automobiles. They tend to be geared towards attacks of different nature and do not take into account mobility, energy consumption and other physical aspects that are vital to a mobile cyber-physical system. We have developed a decision tree-based method for detecting cyber attacks on a small-scale robotic vehicle using both cyber and physical features that can be measured by its on-board systems and processes. We evaluate it experimentally against a variety of scenarios involving denial of service, command injection and two types of malware attacks. We observe that the addition of physical features noticeably improves the detection accuracy for two of the four attack types and reduces the detection latency for all four

Decision tree-based detection of denial of service and command injection attacks on robotic vehicles

Mobile cyber-physical systems, such as automobiles, drones and robotic vehicles, are gradually becoming attractive targets for cyber attacks. This is a challenge because intrusion detection systems built for conventional computer systems tend to be unsuitable. They can be too demanding for resource-restricted cyber-physical systems or too inaccurate due to the lack of real- world data on actual attack behaviours. Here, we focus on the security of a small remote-controlled robotic vehicle. Having observed that certain types of cyber attacks against it exhibit physical impact, we have developed an intrusion detection system that takes into account not only cyber input features, such as network traffic and disk data, but also physical input features, such as speed, physical jittering and power consumption. As the system is resource-restricted, we have opted for a decision tree-based approach for generating simple detection rules, which we evaluate against denial of service and command injection attacks. We observe that the addition of physical input features can markedly reduce the false positive rate and increase the overall accuracy of the detection

Simulation for Neutron Transport in PWR Reactor Moderator and Evaluation for Proper Thickness of Light Water Reflector

Monte Carlo calculation method can be used for resolving particle transport in matter, and particularly the transport of neutrons in environment of reactor core. The method has become more efficiently because of high accuracy of updated nuclear data and fast development of advanced super-computing system. In this work, we would like to present calculations for kinematical characteristics of neutron transport in a typical configuration of the pressurized water reactor (PWR) fuel assembly based on the Monte-Carlo simulation method. We concentrate in two main results: (1) neutron energy spectrum at fuel rod and (2) optimal thickness of light water reflector

Prospects for Food Fermentation in South-East Asia, Topics From the Tropical Fermentation and Biotechnology Network at the End of the AsiFood Erasmus+Project

Fermentation has been used for centuries to produce food in South-East Asia and some foods of this region are famous in the whole world. However, in the twenty first century, issues like food safety and quality must be addressed in a world changing from local business to globalization. In Western countries, the answer to these questions has been made through hygienisation, generalization of the use of starters, specialization of agriculture and use of long-distance transportation. This may have resulted in a loss in the taste and typicity of the products, in an extensive use of antibiotics and other chemicals and eventually, in a loss in the confidence of consumers to the products. The challenges awaiting fermentation in South-East Asia are thus to improve safety and quality in a sustainable system producing tasty and typical fermented products and valorising by-products. At the end of the “AsiFood Erasmus+ project” (www.asifood.org), the goal of this paper is to present and discuss these challenges as addressed by the Tropical Fermentation Network, a group of researchers from universities, research centers and companies in Asia and Europe. This paper presents current actions and prospects on hygienic, environmental, sensorial and nutritional qualities of traditional fermented food including screening of functional bacteria and starters, food safety strategies, research for new antimicrobial compounds, development of more sustainable fermentations and valorisation of by-products. A specificity of this network is also the multidisciplinary approach dealing with microbiology, food, chemical, sensorial, and genetic analyses, biotechnology, food supply chain, consumers and ethnology

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Cyber-physical intrusion detection for robotic vehicles

Intrusion detection systems (IDS) designed for conventional computer systems and networks are not necessarily suitable for mobile cyber-physical systems (CPS), such as robots, drones and automobiles. They tend to be geared towards attacks of different nature and do not take into account mobility, energy consumption and other physical aspects that are vital to a mobile cyber-physical system. This work provides two different approaches for addressing the problem of detecting attacks against vehicles, using a small-scale robotic vehicle as a testbed. The first approach is based on decision trees and the second on deep learning. Both use a combination of cyber and physical features that can be measured by its onboard systems and processes. Experimental evaluation on a variety of scenarios involving denial of service, command injection and two different types of malware infections demonstrated the feasibility of the approaches. Decision tree algorithm is one of the most lightweight machine learning techniques, yet sufficiently powerful in many areas of applications, because it can naturally account for non-linearities in the data. Decision trees produce sets of simple rules, which can be easily checked onboard even the most resource-constrained of robotic vehicles. In the case of our vehicle, this approach was able to achieve high accuracy rate for denial of service attacks, but less so for the other attacks tested. Due to their processing resource constraints, cyber-physical systems, such as robotic vehicles, tend to be limited to lightweight mechanisms, such as decision trees and other statistical machine learning techniques. We show that considerably higher accuracy rates can be achieved if one utilises techniques from the field of deep learning. In particular, we use a recurrent neural network architecture, benefiting from a long short-term memory layer, which is highly appropriate for real-time data. To address the processing limitations, we turn to computational offloading, which is a technique particularly common for mobile devices, for largely the same reasons: to save energy and to have access to greater processing resources. We show both experimentally and mathematically in which cases offloading the periodic task of deep learning based intrusion detection to a remote server can be practical, especially in relation to the time the whole process takes

A targeted malicious email (TME) attack tool

Spam email is a big problem on the Internet, with 89% of all email consisting of spam. The aim of this work was to investigate the technologies required to send spam email and then to develop an automated tool. The tool would need to perform three steps, which were email harvesting, applying social engineering to the content and finally sending out the spam emails. This work clearly demonstrated how emails could still be harvested to produce spam emails, even when the Web Administrator had attempted to obfuscate them. Two common techniques to protect email addresses included replacing the text of address with an image or using JavaScript to safeguard email address in the code used to write the web page. Both of these techniques are aimed at discouraging harvesting activities. In order to bypass the anti-spam system, spammers need to harvest large numbers of valid email addresses and therefore this process needed to be automated. Having identified how the email addresses were stored, these then had to be extracted for use in the tool. This was done using regular expressions. Having obtained a large number of valid emails, the next step was to design an email that the “victim” would open using social engineering techniques, known as a targeted malicious email (TME). It was important to understand the motivation behind TME because this affected the success of the attack. TME needed to pay more attention to the list of recipients and the content of the emails, as well as the process of delivery. TME distribution was also limited to specific groups of users. This meant that the email contents could be crafted to match the interests of the target group. The content template was applied to the sending email. In order to deliver the email, the tool had to be able to interact with the SMTP server to send out the email. Open relay server was selected for managing this process. The tool was able to harvest email addresses, send deceptive messages based on social engineering and perform targeted email attacks using the CMS School web site at the University of Greenwich as the “victim”. In conclusion, a strategy is proposed to prevent automated tools such as the one presented from gathering the information for use in spam mail

Removal efficiencies of constructed wetland and efficacy of plant on treating benzene

Leaking underground petroleum storage poses human and environmental health risks as it contaminates the soil and the groundwater. Of the many contaminants, benzene – a major constituent of gasoline, is of primary concern. It is an identified carcinogen with a permissible limit set at a low level of 0.005 mg L−1. This poses technical and regulatory challenge to remediation of contaminated sites. Various specialized treatment methods are available, but despite of the high removal efficiencies of sophisticated treatments, the residual level still poses health risks. Thus, additional alternative ways that are cost effective and require minimum technical expertise are necessary, and a constructed wetland (CW) is a potential alternative. This study evaluates the performance of a surface flow type CW for the removal of benzene from the contaminated water. It further determines the efficacy of a common reed plant Phragmites karka in treating benzene. Planted and unplanted CW were acclimated with benzene for 16 wk and tested for an 8-d hydraulic retention time at benzene levels of 66 and 45 mg L−1. Results indicate that the planted CW performed better and gave reliable and stable results

ĐÁNH GIÁ TIỀM NĂNG ĐẤT ĐAI CHO PHÁT TRIỂN CÂY ĂN TRÁI TẠI HUYỆN CHÂU THÀNH, TỈNH BẾN TRE

The aim of this article is to determine the potential of land for fruit development in Chau Thanh district, Ben Tre province, for the development of centralized production zones. Reports on agricultural production, socio-economic development and statistical yearbooks were collected. In addition, the study consulted 18 experts and 37 households directly engaging in agricultural production. An in-depth interview with agricultural managers was also conducted to determine the current status and collect the economic data on the fruit production models. In addition, the land potential for crops was estimated according to the land evaluation method of FAO (1976 and 2007). The results show that Chau Thanh is a purely agricultural district with typical crops such as coconuts, pomelos, rambutans, and durians. The soil, water, and climate characteristics enable us to identify seven physical adaptation zones, six economic adaptation zones, and seven mixed zones for the crops. On that basis, we build six agricultural production zones for Chau Thanh that are sustainable and adaptable to saline intrusion.Mục đích của bài báo này là xác định tiềm năng đất đai cho phát triển cây ăn trái tại huyện Châu Thành, làm cơ sở định hướng và phát triển vùng sản xuất tập trung. Dữ liệu nghiên cứu được thu thập từ các báo cáo về tình hình sản xuất nông nghiệp, phát triển kinh tế – xã hội và niên giám thống kê. Bên cạnh đó, 18 chuyên gia và 37 người dân trực tiếp sản xuất nông nghiệp được tham vấn ý kiến, đồng thời tổ chức một cuộc phỏng vấn sâu các nhà quản lý nông nghiệp để xác định hiện trạng và thu thập thông tin sản xuất của các mô hình cây ăn trái. Phương pháp đánh giá thích nghi đất đai của FAO (1976 và 2007) được sử dụng để xác định tiềm năng đất đai cho các loại cây trồng. Kết quả cho thấy Châu Thành là một huyện thuần nông, với các loại cây trồng đặc trưng như dừa, bưởi, chôm chôm và sầu riêng. Với các đặc tính đất đai về điều kiện đất, nước và khí hậu đã xác định được bảy vùng thích nghi tự nhiên, sáu vùng thích nghi kinh tế và bảy vùng thích nghi kinh tế kết hợp tự nhiên cho các loại cây trồng. Trên cơ sở đó, chúng tôi đã xây dựng được sáu vùng sản xuất nông nghiệp mang tính bền vững và thích ứng với tình hình xâm nhập mặn của huyện

Histopathological Alterations in the Livers of Chronic Hepatitis Patients Exposed to Agent Orange/Dioxin in Vietnam

We investigated changes in some laboratory indices and the liver histology of chronic hepatitis patients who were exposed to dioxin. In 2014, we collected liver biopsy samples for histopathological examination from 33 chronic hepatitis patients living around the Da Nang Airbase, which is a dioxin-contaminated area due to the herbicide spraying in Vietnam. Dioxin exposure was measured by its levels in the blood. METAVIR classification was used to clarify the liver fibrosis stage. Laboratory tests included ten biochemical and six hematological indices that were measured in the blood. A regression linear model and binary logistic regression were used for data analysis. The observed alterations in the liver at the histological level mainly comprised hydropic degenerative hepatocytes, lymphocytes and polynuclear leukocytes surrounding the liver cells and granular and lipoic degeneration. In addition, increased TCDD levels were associated with increasing aminotransferase (AST), alanine aminotransferase, protein and total bilirubin levels and liver fibrosis stage. Similarly, increased TEQ-PCDD/Fs levels were associated with higher levels of AST and protein and liver fibrosis stage. In conclusion, dioxin exposure altered the liver histology and increased some biochemical marker indices and the liver fibrosis stage of chronic hepatitis patients living in dioxin-contaminated areas in Da Nang, Vietnam