An Iterative and Toolchain-Based Approach to Automate Scanning and Mapping Computer Networks

As today's organizational computer networks are ever evolving and becoming more and more complex, finding potential vulnerabilities and conducting security audits has become a crucial element in securing these networks. The first step in auditing a network is reconnaissance by mapping it to get a comprehensive overview over its structure. The growing complexity, however, makes this task increasingly effortful, even more as mapping (instead of plain scanning), presently, still involves a lot of manual work. Therefore, the concept proposed in this paper automates the scanning and mapping of unknown and non-cooperative computer networks in order to find security weaknesses or verify access controls. It further helps to conduct audits by allowing comparing documented with actual networks and finding unauthorized network devices, as well as evaluating access control methods by conducting delta scans. It uses a novel approach of augmenting data from iteratively chained existing scanning tools with context, using genuine analytics modules to allow assessing a network's topology instead of just generating a list of scanned devices. It further contains a visualization model that provides a clear, lucid topology map and a special graph for comparative analysis. The goal is to provide maximum insight with a minimum of a priori knowledge.Comment: 7 pages, 6 figure

DeepRoute: Herding Elephant and Mice Flows with Reinforcement Learning

International audienceWide area networks are built to have enough resilience and flexibility, such as offering many paths between multiple pairs of end-hosts. To prevent congestion, current practices involve numerous tweaking of routing tables to optimize path computation, such as flow diversion to alternate paths or load balancing. However, this process is slow, costly and require difficult online decision-making to learn appropriate settings, such as flow arrival rate, workload, and current network environment. Inspired by recent advances in AI to manage resources, we present DeepRoute, a model-less reinforcement learning approach that translates the path computation problem to a learning problem. Learning from the network environment, DeepRoute learns strategies to manage arriving elephant and mice flows to improve the average path utilization in the network. Comparing to other strategies such as prioritizing certain flows and random decisions, DeepRoute is shown to improve average network path utilization to 30% and potentially reduce possible congestion across the whole network. This paper presents results in simulation and also how DeepRoute can be demonstrated by a Mininet implementation

Tracking replication enzymology in vivo by genome-wide mapping of ribonucleotide incorporation

Ribonucleotides are frequently incorporated into DNA during eukaryotic replication. Here we map the genome-wide distribution of these ribonucleotides as markers of replication enzymology in budding yeast, using a new 5′-DNA end-mapping method, Hydrolytic End Sequencing. HydEn-Seq of DNA from ribonucleotide excision repair-deficient strains reveals replicase- and strand-specific patterns of ribonucleotides in the nuclear genome. These patterns support the role of DNA polymerases α and δ in lagging strand replication and of DNA polymerase ε in leading strand replication. They identify replication origins, termination zones and variations in ribonucleotide incorporation frequency across the genome that exceed three orders of magnitude. HydEn-Seq also reveals strand-specific 5′-DNA ends at mitochondrial replication origins, suggesting unidirectional replication of a circular genome. Given the conservation of enzymes that incorporate and process ribonucleotides in DNA, HydEn-Seq can be used to track replication enzymology in other organisms

Prediction of second neurological attack in patients with clinically isolated syndrome using support vector machines

The aim of this study is to predict the conversion from clinically isolated syndrome to clinically definite multiple sclerosis using support vector machines. The two groups of converters and non-converters are classified using features that were calculated from baseline data of 73 patients. The data consists of standard magnetic resonance images, binary lesion masks, and clinical and demographic information. 15 features were calculated and all combinations of them were iteratively tested for their predictive capacity using polynomial kernels and radial basis functions with leave-one-out cross-validation. The accuracy of this prediction is up to 86.4% with a sensitivity and specificity in the same range indicating that this is a feasible approach for the prediction of a second clinical attack in patients with clinically isolated syndromes, and that the chosen features are appropriate. The two features gender and location of onset lesions have been used in all feature combinations leading to a high accuracy suggesting that they are highly predictive. However, it is necessary to add supporting features to maximise the accuracy. © 2013 IEEE

Brachial Plexus Anatomy: Normal and Variant

Effective brachial plexus blockade requires a thorough understanding of the anatomy of the plexus, as well as an appreciation of anatomic variations that may occur. This review summarizes relevant anatomy of the plexus, along with variations and anomalies that may affect nerve blocks conducted at these levels. The Medline, Cochrane Library, and PubMed electronic databases were searched in order to compile reports related to the anatomy of the brachial plexus using the following free terms: "brachial plexus", "median nerve", "ulnar nerve", "radial nerve", "axillary nerve", and "musculocutanous nerve". Each of these was then paired with the MESH terms "anatomy", "nerve block", "anomaly", "variation", and "ultrasound". Resulting articles were hand searched for additional relevant literature. A total of 68 searches were conducted, with a total of 377 possible articles for inclusion. Of these, 57 were found to provide substantive information for this review. The normal anatomy of the brachial plexus is briefly reviewed, with an emphasis on those features revealed by use of imaging technologies. Anomalies of the anatomy that might affect the conduct of the various brachial plexus blocks are noted. Brachial plexus blockade has been effectively utilized as a component of anesthesia for upper extremity surgery for a century. Over that period, our understanding of anatomy and its variations has improved significantly. The ability to explore anatomy at the bedside, with real-time ultrasonography, has improved our appreciation of brachial plexus anatomy as well

IoT Vulnerability Scanning: A State of the Art

Our modern life becomes more and more dependent on tech-nology and services provided through an increasing number of deployed devices «Things» which are connected over networks that can sometimes be accessed remotely via the Internet. Although this Internet of Things (IoT) has led to innovations and improvements to our way of life, it has created many issues, especially related to cybersecurity. Ensuring the security of the IoT ecosystem can be achieved using pro-active security processes, including vulnerability scanning. In this paper, we capture the state of the art of the process that is IoT vulnerability scanning to determine its popularity and maturity. We have captured the di_erent motivations for vulnerability scanning, the scanning space, process, and faced challenges. A Systematic Literature Review (SLR) has been con-ducted to achieve this goal, and the results are presented hereof. More-over, we conducted a group of experiments to assess the status of IoT services and their associated vulnerabilities in the Nordic countries and found that additional work is needed to improve the security of the IoT ecosystem

Evaluation of the relationship between the topographical anatomy in the axillary region of the brachial plexus and the body mass index

WOS: 000439345200023PubMed ID: 28871408To investigate the topographic anatomy of the median, musculocutaneous, radial and ulnar nerves with respect to the axillary artery and to seek whether these configurations are associated with baseline descriptive data including age, gender, and body-mass index. This cross-sectional trial was carried out on 199 patients (85 women, 114 men; average age: 46.78 +/- 15.45 years) in the department of anaesthesiology and reanimation of a tertiary care center. Topographic anatomy of the median, musculocutaneous, radial and ulnar nerves was assessed with ultrasonography. Localization of these nerves with respect to the axillary artery was marked on the map demonstrating 16 zones around the axillary artery. Frequencies of localizations of every nerve in these zones were recorded, and the correlation of these locations with descriptive data including age, gender and BMI was investigated. There was no difference between women and men for the distribution of the median (p = 0.74), ulnar (p = 0.35) and radial (p = 0.64) nerves. However, the musculocutaneous nerve was more commonly located in Zone A13 in men compared to women (p = 0.02). The localization of the median (p = 0.85), ulnar (p = 0.27) and radial (p = 0.88) nerves did not differ remarkably between patients with BMI < 25 kg/m(2) and patients with BMI 25 kg/m(2). Notably, the musculocutaneous nerve was more often determined in Zone A10 in cases with BMI 25 kg/m(2) (p = 0.001). Our results imply that the alignment of the musculocutaneous nerve may vary in men and overweight people. This fact must be considered by the anaesthetist before planning the axillary block of brachial plexus. All these informations may enlighten the planning stages of the brachial plexus blockade