Active authentication for mobile devices utilising behaviour profiling.

With nearly 6 billion subscribers around the world, mobile devices have become an indispensable component in modern society. The majority of these devices rely upon passwords and personal identification numbers as a form of user authentication, and the weakness of these point-of-entry techniques is widely documented. Active authentication is designed to overcome this problem by utilising biometric techniques to continuously assess user identity. This paper describes a feasibility study into a behaviour profiling technique that utilises historical application usage to verify mobile users in a continuous manner. By utilising a combination of a rule-based classifier, a dynamic profiling technique and a smoothing function, the best experimental result for a users overall application usage was an equal error rate of 9.8 %. Based upon this result, the paper proceeds to propose a novel behaviour profiling framework that enables a user’s identity to be verified through their application usage in a continuous and transparent manner. In order to balance the trade-off between security and usability, the framework is designed in a modular way that will not reject user access based upon a single application activity but a number of consecutive abnormal application usages. The proposed framework is then evaluated through simulation with results of 11.45 and 4.17 % for the false rejection rate and false acceptance rate, respectively. In comparison with point-of-entry-based approaches, behaviour profiling provides a significant improvement in both the security afforded to the device and user convenience

Burn surgeons in South Africa: A rare species

Background. The high burden of burn injuries in South Africa (SA) requires surgeons skilled in burn care. However, there are few dedicated burn surgeons and properly equipped units or centres.Objectives. To quantify the involvement of surgeons in burn care in SA hospitals, identify factors that attract surgeons to pursue burn care as a career and deter them from doing so, and understand the challenges of hospitals treating burn patients around the country.Methods. This was a prospective, qualitative study. Questionnaires were handed out at the South African Burn Society Congress in September 2013 and a trade symposium in March 2014.Results. One hundred questionnaires were handed out, and there was a 70% response rate. Twenty-six (39%) of the respondents had a specialist surgical qualification. Only half the units had registrars (48%) and interns (51%) on their staff. Only 30% of the respondents were dedicated to burn care alone, the majority being involved on a part-time basis. The most common factor respondents suggested was needed to recruit future burn care providers, cited by 76%, was better facilities and resources. Other factors included training and skills development (59%), subspecialist training (55%), development of a diploma in burn care (52%), development of research (52%) and healthcare worker psychological support (45%).Conclusion. We have demonstrated that current workforce resources for burn care are inadequate, the major deficit being lack of training and the resource restricted environment. This survey provides basic information towards workforce planning, which can be used to inform the necessary strategic decisions

The effect of passive heating on heat shock protein 70 and interleukin-6: a possible treatment tool for metabolic diseases?

Exercise and physical activity remain the gold standard methods of enhancing and maintaining health and wellbeing. However, in populations that benefit most from exercise, adherence is often poor and alternatives to exercise are important to bring about health improvements. Recent work suggests a role for passive heating (PH) and heat shock proteins (HSP) in improving cardio-metabolic health. The aim of this study was to investigate the expression of HSP70 and IL-6 in response to either exercise (EX) or PH and the subsequent effect on glucose control. Fourteen males volunteered and were categorized lean (BMI 23.5 ± 2.2 Kgm-2) or overweight (29.2 ± 2.7 Kgm-2) and completed 60 minutes of either moderate cycling at a fixed rate of metabolic heat production (EX) or warm water immersion in 40 ̊C water (PH). Extracellular HSP70 increased from baseline in both conditions with no differences between PH (0.98 ± 1.1 ngmL-1) or EX (0.84 ± 1.0 ngmL-1, P=0.814). IL-6 increased following both conditions with a 2 fold increase after PH and 4 fold after EX. Energy expenditure increased by 61.0 ± 14.4 kcal (79%) after PH. Peak glucose concentration after a meal immediately following PH was reduced when compared with EX (6.3 ± 1.4mmolL-1 vs. 6.8 ± 1.2mmolL-1; P<0.05). There was no difference in 24-hour glucose area under the curve between conditions. These data indicate the potential for thermal therapy as a novel treatment and management strategy for type 2 diabetes where adherence, or ability to exercise may be compromised

User Profiling Based on Application-Level Using Network Metadata.

There is an increasing interest to identify users and behaviour profiling from network traffic metadata for traffic engineering and security monitoring. Network security administrators and internet service providers need to create the user behaviour traffic profile to make an informed decision about policing, traffic management, and investigate the different network security perspectives. Additionally, the analysis of network traffic metadata and extraction of feature sets to understand trends in application usage can be significant in terms of identifying and profiling the user by representing the user's activity. However, user identification and behaviour profiling in real-time network management remains a challenge, as the behaviour and underline interaction of network applications are permanently changing. In parallel, user behaviour is also changing and adapting, as the online interaction environment changes. Also, the challenge is how to adequately describe the user activity among generic network traffic in terms of identifying the user and his changing behaviour over time. In this paper, we propose a novel mechanism for user identification and behaviour profiling and analysing individual usage per application. The research considered the application-level flow sessions identified based on Domain Name System filtering criteria and timing resolution bins (24-hour timing bins) leading to an extended set of features. Validation of the module was conducted by collecting Net Flow records for a 60 days from 23 users. A gradient boosting supervised machine learning algorithm was leveraged for modelling user identification based upon the selected features. The proposed method yields an accuracy for identifying a user based on the proposed features up to 74

A suspect-oriented intelligent and automated computer forensic analysis

Computer forensics faces a range of challenges due to the widespread use of computing technologies. Examples include the increasing volume of data and devices that need to be analysed in any single case, differing platforms, use of encryption and new technology paradigms (such as cloud computing and the Internet of Things). Automation within forensic tools exists, but only to perform very simple tasks, such as data carving and file signature analysis. Investigators are responsible for undertaking the cognitively challenging and time-consuming process of identifying relevant artefacts. Due to the volume of cyber-dependent (e.g., malware and hacking) and cyber-enabled (e.g., fraud and online harassment) crimes, this results in a large backlog of cases. With the aim of speeding up the analysis process, this paper investigates the role that unsupervised pattern recognition can have in identifying notable artefacts. A study utilising the Self-Organising Map (SOM) to automatically cluster notable artefacts was devised using a series of four cases. Several SOMs were created – a File List SOM containing the metadata of files based upon the file system, and a series of application level SOMs based upon metadata extracted from files themselves (e.g., EXIF data extracted from JPEGs and email metadata extracted from email files). A total of 275 sets of experiments were conducted to determine the viability of clustering across a range of network configurations. The results reveal that more than 93.5% of notable artefacts were grouped within the rank-five clusters in all four cases. The best performance was achieved by using a 10 × 10 SOM where all notables were clustered in a single cell with only 1.6% of the non-notable artefacts (noise) being present, highlighting that SOM-based analysis does have the potential to cluster notable versus noise files to a degree that would significantly reduce the investigation time. Whilst clustering has proven to be successful, operationalizing it is still a challenge (for example, how to identify the cluster containing the largest proportion of notables within the case). The paper continues to propose a process that capitalises upon SOM and other parameters such as the timeline to identify notable artefacts whilst minimising noise files. Overall, based solely upon unsupervised learning, the approach is able to achieve a recall rate of up to 93%. © 2016 Elsevier Lt

Activity Recognition using wearable computing.

A secure, user-convenient approach to authenticate users on their mobile devices is required as current approaches (e.g., PIN or Password) suffer from security and usability issues. Transparent Authentication Systems (TAS) have been introduced to improve the level of security as well as offer continuous and unobtrusive authentication (i.e., user friendly) by using various behavioural biometric techniques. This paper presents the usefulness of using smartwatch motion sensors (i.e., accelerometer and gyroscope) to perform Activity Recognition for the use within a TAS. Whilst previous research in TAS has focused upon its application in computers and mobile devices, little attention is given to the use of wearable devices - which tend to be sensor-rich highly personal technologies. This paper presents a thorough analysis of the current state of the art in transparent and continuous authentication using acceleration and gyroscope sensors and a technology evaluation to determine the basis for such an approach. The best results are average Euclidean distance scores of 5.5 and 11.9 for users\u27 intra acceleration and gyroscope signals respectively and 24.27 and 101.18 for users\u27 inter acceleration and gyroscope activities accordingly. The findings demonstrate that the technology is sufficiently capable and the nature of the signals captured sufficiently discriminative to be useful in performing Activity Recognition

Substrate specificity of bacterial oligosaccharyltransferase suggests a common transfer mechanism for the bacterial and eukaryotic systems

The PgIB oligosaccharyltransferase (OTase) of Campylobacter jejuni can be functionally expressed in Escherichia coli, and its relaxed oligosaccharide substrate specificity allows the transfer of different glycans from the lipid carrier undecaprenyl pyrophosphate to an acceptor protein. To investigate the substrate specificity of PgIB, we tested the transfer of a set of lipid-linked polysaccharides in E. coli and Salmonella enterica serovar Typhimurium. A hexose linked to the C-6 of the monosaccharide at the reducing end did not inhibit the transfer of the O antigen to the acceptor protein. However, PgIB required an acetamido group at the C-2. A model for the mechanism of PgIB involving this functional group was proposed. Previous experiments have shown that eukaryotic OTases have the same requirement, suggesting that eukaryotic and prokaryotic OTases catalyze the transfer of oligosaccharides by a conserved mechanism. Moreover, we demonstrated the functional transfer of the C. jejuni glycosylation system into S. enterica. The elucidation of the mechanism of action and the substrate specificity of PgIB represents the foundation for engineering glycoproteins that will have an impact on biotechnology

Some Like It Fat: Comparative Ultrastructure of the Embryo in Two Demosponges of the Genus Mycale (Order Poecilosclerida) from Antarctica and the Caribbean

0000-0002-7993-1523© 2015 Riesgo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License [4.0], which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The attached file is the published version of the article