Diffusion of White-Hat Botnet Using Lifespan with Controllable Ripple Effect for Malware Removal in IoT Networks.

Self-propagating malware has been infecting thousands of IoT devices and causing security breaches worldwide. Mitigating and cleaning self-propagating malware is important but challenging because they propagate unpredictably. White-hat botnets have been used to combat self-propagating malware with the concept of fight fire-with-fire. However, white-hat botnets can also overpopulate and consume the resource of IoT devices. Later, lifespan was introduced as a self-destruct measure to restrain white-hat botnets' overpopulation, but unable to change based on real-time situations. This paper proposes a method for diffusing white-hat botnets by controlling lifespan. The main contribution of this paper is that the method uses a dynamic lifespan that increases and decreases based on the congregation's situation of the self-propagating malware and white-hat botnets. The method tackles the problem of overpopulation of white-hat botnets since they can self-propagate by controlling the ripple effect that widens the white-hat botnet's diffusion area but suppresses the number of white-hat botnets to achieve a 'zero-botnet' situation. The effectiveness in reducing the overpopulation rate was confirmed. The experiment result showed that the ripple effect could reduce the number of white-hat botnets in the network by around 80%, depending on different control parameters.

Botnet Defense System: Observability, Controllability, and Basic Command and Control Strategy.

This paper deals with the observability, controllability, and command and control strategy in the Botnet Defense System (BDS) that disinfects malicious botnets with white-hat botnets. The BDS defends an IoT system built over the Internet. The Internet is characterized by openness, but not all nodes are observable and controllable. We incorporated the concept of observability and controllability into the BDS design and theoretically clarified that the BDS can enhance its observability and controllability by utilizing its white-hat botnets. In addition, we proposed a Withdrawal strategy as a basic strategy to command and control white-hat botnets. Then, we modeled the BDS, adopted the Withdrawal strategy with agent-oriented Petri net PN2 and confirmed the effect through the simulation of the model. The result shows that even if considering observability and controllability, the BDS wiped out the malicious bots and reduced the white-hat bots to less than 1% as long as the white-hat worms were sufficiently infectious.

Water-Absorbing Bioadhesive Poly(Acrylic Acid)/Polyvinylpyrrolidone Complex Sponge for Hemostatic Agents.

BACKGROUND: Poly(acrylic acid) (PAA) is a water-soluble synthetic polymer with tissue-adhesive properties. When PAA is mixed with polyvinylpyrrolidone (PVP) in water, it forms a water-insoluble precipitate that neither swells nor adheres to tissues. METHODS AND RESULTS: We developed a novel solid/solution interface complexation method to obtain a water-swellable PAA/PVP complex. First, PAA solution was dried up in a vessel to form a film. The PAA film was then immersed in an aqueous PVP solution to obtain a highly swollen PAA/PVP hydrogel. Heat drying of the hydrogel yielded a transparent film, while freeze-drying the hydrogel provided a soft sponge. Both the PAA/PVP film and sponge could be re-swelled by water to obtain a bioadhesive gel. A relatively larger specific surface area of the sponge than that of the film led to a more rapid swelling and water absorption behavior and quick adhesion to tissues. The addition of hyaluronic acid (HA) improved the mechanical characteristics of the sponges. PAA/PVP/HA sponges had low cytotoxicity, and they exhibited high hemostatic efficiency in clinical studies after dialysis treatment or tooth extraction, even in patients on antithrombotic drugs. CONCLUSIONS: Such bioadhesive materials consisting of low-toxicity polymers have a high potential for use in medical hemostatic devices.

Preparation of a Bioadhesive Poly(Acrylic Acid)/Polyvinylpyrrolidone Complex Gel and Its Clinical Effect on Dental Hemostasis.

Poly(acrylic acid) (PAA) is a water-soluble synthetic polymer that exhibits bioadhesive properties and has been applied in various novel medical devices, such as drug-delivery carriers and hemostatic agents. PAA forms a water-insoluble complex when mixed with polyvinylpyrrolidone (PVP). If PAA and PVP are mixed in water, they form an aggregated precipitate, which neither swells nor adheres to tissues. The formation of the hydrophobic complex was caused by hydrophobic interactions between the main chains of both polymers aligned the same as a zipper. To hinder the zipper-like alignment of the polymer main chains, hyaluronic acid (HA), a macromolecular viscous polysaccharide, was added to the PVP solution prior to complex formation. When the initial concentration of PAA was lower than 0.05%, HA effectively prevented the aggregation of PAA/PVP complexes and resulted in a slightly clouded suspension. Freeze-drying of the mixture yielded a soft white sponge, which could immediately swell in water to form a highly bioadhesive hydrogel. The PAA/PVP complex prepared with HA exhibited high hemostatic efficiency in clinical studies, even in patients on antithrombotic drugs.

Machine Learning White-Hat Worm Launcher for Tactical Response by Zoning in Botnet Defense System.

Malicious botnets such as Mirai are a major threat to IoT networks regarding cyber security. The Botnet Defense System (BDS) is a network security system based on the concept of "fight fire with fire", and it uses white-hat botnets to fight against malicious botnets. However, the existing white-hat Worm Launcher of the BDS decides the number of white-hat worms, but it does not consider the white-hat worms' placement. This paper proposes a novel machine learning (ML)-based white-hat Worm Launcher for tactical response by zoning in the BDS. The concept of zoning is introduced to grasp the malicious botnet spread with bias over the IoT network. This enables the Launcher to divide the network into zones and make tactical responses for each zone. Three tactics for tactical responses for each zone are also proposed. Then, the BDS with the Launcher is modeled by using agent-oriented Petri nets, and the effect of the proposed Launcher is evaluated. The result shows that the proposed Launcher can reduce the number of infected IoT devices by about 30%.

Monitoring and Predicting the Size of Fine Particles Prepared in a Fluidized-Bed Granulator Using a Handheld-Type Raman Spectrometer.

We prepared two kinds of fine particles by treating lactose monohydrate (Lac) with the same formulation in a fluidized-bed granulator, which differed in the spraying air pressure. Raman intensities of treated Lac during processing were measured using a handheld-type Raman spectrometer and plotted against particle size. As particle size increased, Raman intensity decreased in both operating conditions. A linear relationship between them was observed, and regression lines were obtained with good correlation coefficients as calibration curves in both operating conditions. We also prepared two other types of fine particles by treating Lac with the same formulation in a fluidized-bed granulator, which differed in the scale or processing mechanism. The particle size could be successfully predicted using the calibration curve obtained taking powder porosity into consideration. Based on this study, we present a new at-line approach in process analytical technology to monitor and predict particle size using a handheld-type Raman spectrometer.

Combinations of Drug Candidate Properties Affecting Development Success and Discontinuation for 5 Diseases: Lymphoma, Non-Small Cell Lung Cancer, Arthritis, Depression, and Alzheimer Disease.

The effects of the properties of drug candidates on their successful approval for the treatment of diseases are substantial. However, the success rate of candidates when their properties are combined has not been sufficiently evaluated. We aimed to identify combinations of properties (target, action, and modality) that increased the approval success rate of drug candidates for 5 diseases as well as to understand the characteristics of discontinued candidates. We calculated the approval success rates by combining the properties of drug candidates developed for 5 diseases (non-small cell lung cancer, lymphoma, arthritis, depression, and Alzheimer disease [AD]), using candidates for which clinical development was initiated between 2000 and 2010. We also analyzed the phases and the reasons for the discontinuation of candidates of the 5 diseases for which development was discontinued. Probable combinations of properties with relatively high success rates for the diseases except for Alzheimer disease were found. These combinations of properties were considered appropriate in light of the pathology of each disease. The percentage of candidates discontinued in phase III for Alzheimer disease was higher than that for the other diseases. The reasons for discontinuation showed different trends between combinations of properties that had high and low approval success rates. As the effects of the properties of candidates on the success rate vary depending on the intended disease, pharmaceutical companies need to consider the probability of success of candidates for individual diseases for more efficient candidate selection.

Approval success rates of drug candidates based on target, action, modality, application, and their combinations.

The current success rate of a drug candidate, from the beginning of the clinical trial to receiving marketing approval, is about 10%-20%, and it has not changed during the past few decades. Therefore, pharmaceutical companies are under pressure to select one compound, among many others, with a high probability of success. The differences in drug features affect their probabilities of approval success. In this study, we examined the approval success rates of drug candidates, developed in the United States, the European Union, or Japan, by focusing on four parameters ("drug target," "drug action," "drug modality," and "drug application") and their combinations, and identified factors that conditioned the outcome of the drug development process. We obtained a total success rate of 12.8%, after evaluating 3999 compounds. Moreover, after analyzing the combinations of these parameters, the approval success rates of drugs that corresponded to the following categories-a stimulant in drug action or an enzyme in drug target and biologics (excluding monoclonal antibody) in drug modality-were high (34.1% and 31.3%, respectively). Univariate and multivariate logistic regression analyses revealed that stimulant in drug action, and "B" (blood and blood forming organs), "G" (genito-urinary system and sex), and "J" (anti-infectives for systemic use) in drug application were statistically associated with high approval success rates. We found several parameters and their combinations that affected drug approval success rates. Our results could assist pharmaceutical companies in evaluating the probability of success of their drug candidates and, thus, in efficiently conducting the clinical development process.

White-Hat Worm to Fight Malware and Its Evaluation by Agent-Oriented Petri Nets †.

A new kind of malware called Mirai is spreading like wildfire. Mirai is characterized by targeting Internet of Things (IoT) devices. Since IoT devices are increasing explosively, it is not realistic to manage their vulnerability by human-wave tactics. This paper proposes a new approach that uses a white-hat worm to fight malware. The white-hat worm is an extension of an IoT worm called Hajime and introduces lifespan and secondary infectivity (the ability to infect a device infected by Mirai). The proposed white-hat worm was expressed as a formal model with agent-oriented Petri nets called PN 2 . The model enables us to simulate a battle between the white-hat worm and Mirai. The result of the simulation evaluation shows that (i) the lifespan successfully reduces the worm's remaining if short; (ii) if the worm has low secondary infectivity, its effect depends on the lifespan; and (iii) if the worm has high secondary infectivity, it is effective without depending on the lifespan.

Gene expression profiling of granule cells and Purkinje cells in the zebrafish cerebellum.

The structure of the neural circuitry of the cerebellum, which functions in some types of motor learning and coordination, is generally conserved among vertebrates. However, some cerebellar features are species specific. It is not clear which genes are involved in forming these conserved and species-specific structures and functions. This study uses zebrafish transgenic larvae expressing fluorescent proteins in granule cells, Purkinje cells, or other cerebellar neurons and glial cells to isolate each type of cerebellar cells by fluorescence-activated cell sorting and to profile their gene expressions by RNA sequencing and in situ hybridization. We identify genes that are upregulated in granule cells or Purkinje cells, including many genes that are also expressed in mammalian cerebella. Comparison of the transcriptomes in granule cells and Purkinje cells in zebrafish larvae reveals that more developmental genes are expressed in granule cells, whereas more neuronal-function genes are expressed in Purkinje cells. We show that some genes that are upregulated in granule cells or Purkinje cells are also expressed in the cerebellum-like structures. Our data provide a platform for understanding the development and function of the cerebellar neural circuits in zebrafish and the evolution of cerebellar circuits in vertebrates. J. Comp. Neurol. 525:1558-1585, 2017. © 2016 Wiley Periodicals, Inc.

Type IV Collagen Controls the Axogenesis of Cerebellar Granule Cells by Regulating Basement Membrane Integrity in Zebrafish.

Granule cells (GCs) are the major glutamatergic neurons in the cerebellum, and GC axon formation is an initial step in establishing functional cerebellar circuits. In the zebrafish cerebellum, GCs can be classified into rostromedial and caudolateral groups, according to the locations of their somata in the corresponding cerebellar lobes. The axons of the GCs in the caudolateral lobes terminate on crest cells in the dorsal hindbrain, as well as forming en passant synapses with Purkinje cells in the cerebellum. In the zebrafish mutant shiomaneki, the caudolateral GCs extend aberrant axons. Positional cloning revealed that the shiomaneki (sio) gene locus encodes Col4a6, a subunit of type IV collagen, which, in a complex with Col4a5, is a basement membrane (BM) component. Both col4a5 and col4a6 mutants displayed similar abnormalities in the axogenesis of GCs and retinal ganglion cells (RGCs). Although type IV collagen is reported to control axon targeting by regulating the concentration gradient of an axonal guidance molecule Slit, Slit overexpression did not affect the GC axons. The structure of the BM surrounding the tectum and dorsal hindbrain was disorganized in the col4a5 and col4a6 mutants. Moreover, the abnormal axogenesis of the caudolateral GCs and the RGCs was coupled with aberrant BM structures in the type IV collagen mutants. The regrowth of GC axons after experimental ablation revealed that the original and newly formed axons displayed similar branching and extension abnormalities in the col4a6 mutants. These results collectively suggest that type IV collagen controls GC axon formation by regulating the integrity of the BM, which provides axons with the correct path to their targets.

Establishment of Gal4 transgenic zebrafish lines for analysis of development of cerebellar neural circuitry.

The cerebellum is involved in some forms of motor coordination and motor learning. Here we isolated transgenic (Tg) zebrafish lines that express a modified version of Gal4-VP16 (GFF) in the cerebellar neural circuits: granule, Purkinje, or eurydendroid cells, Bergmann glia, or the neurons in the inferior olive nuclei (IO) which send climbing fibers to Purkinje cells, with the transposon Tol2 system. By combining GFF lines with Tg lines carrying a reporter gene located downstream of Gal4 binding sequences (upstream activating sequence: UAS), we investigated the anatomy and developmental processes of the cerebellar neural circuitry. Combining an IO-specific Gal4 line with a UAS reporter line expressing the photoconvertible fluorescent protein Kaede demonstrated the contralateral projections of climbing fibers. Combining a granule cell-specific Gal4 line with a UAS reporter line expressing wheat germ agglutinin (WGA) confirmed direct and/or indirect connections of granule cells with Purkinje cells, eurydendroid cells, and IO neurons in zebrafish. Time-lapse analysis of a granule cell-specific Gal4 line revealed initial random movements and ventral migration of granule cell nuclei. Transgenesis of a reporter gene with another transposon Tol1 system visualized neuronal structure at a single cell resolution. Our findings indicate the usefulness of these zebrafish Gal4 Tg lines for studying the development and function of cerebellar neural circuits.