Conditional hybrid approach for intrusion detection

Background and Objective: Inspecting all packets to detect intrusions faces challenges when coping with a high volume of traffic.Packet-based detection processes every payload on the wire, which degrades the performance of intrusion-detection systems.This issue requires the introduction of a flow-based IDS approach that reduces the amount of data to be processed by examining aggregated information of related packets in the form of flow.However, flow-based detection still suffers from the generation of false positive alerts due to lack of completed data input.This study proposed a model to improve packet-based performance and reduce flow-based false positive rate by combining flow-based with packet-based detection to compensate for their mutual shortcomings.This proposed model is named as conditional hybrid intrusion detection.Materials and Methods: In this model, only malicious flows marked by flow-based must be further analyzed by packet-based detection.For packet-based detection to communicate with flow-based detection, input framework approach was used.To evaluate the proposed detection methods, public datasets were replayed in different traffic rates into both the proposed method and default Bro implementations in a testbed controlled environment.Results: Experimental evaluation shows that the proposed approach was able to detect all infected hosts reported and corresponding datasets.At 200 Mbps rate, proposed approach can save 50.6% of memory and 18.1% of CPU usage compared with default Bro packet-based detection. Experiments demonstrated that the default Bro packet-based can handle bandwidth up to 100 Mbps without packets drop, while 200 Mbps in the proposed approach. Conclusion: Experimental evaluation showed that the proposed model gains a significant performance improvement, in term of resource consumption and packet drop rate compared with a default Bro packet-based detection implementation.The proposed approach can mitigate the false positive rate of flow-based detection and reduce the resource consumption of packet-based detection, while preserving detection accuracy.This study can be considered as skeleton model to be applied for intrusion or monitoring detection systems

Application of the bees algorithm to the selection features for manufacturing data

Data with a large number of features tend to be deficient in accuracy and precision. Some of the features may contain irrelevant information caused by data redundancy or by noise. A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. Each “bee” represents a possible set of features. The MLP classification error is computed for a data set with those features. This information is supplied to the Bees Algorithm to enable it to select the combination of features producing the lowest classification error. The proposed method has been tested on data collected in semiconductor manufacturing. The results presented in the paper clearly demonstrate the effectiveness of the method

Data clustering using the bees algorithm

Clustering is concerned with partitioning a data set into homogeneous groups. One of the most popular clustering methods is k-means clustering because of its simplicity and computational efficiency. K-means clustering involves search and optimization. The main problem with this clustering method is its tendency to converge to local optima. The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. This paper proposes a clustering method that integrates the simplicity of the k-means algorithm with the capability of the Bees Algorithm to avoid local optima. The paper presents test results to demonstrate the efficacy of the proposed algorithm

Diagnostic Value of Manual and Computerized Methods of Dental Casts Analysis

Objective: The aim of this study was to evaluate the validity of computerized and manual methods of dental cast analysis.Materials and Methods: Twenty set-ups of upper and lower casts using artificial teeth corresponding to various malocclusions were created for a diagnostic in vitro study. Values of tooth size were calculated from the isolated artificial teeth out of the set-ups, results were considered as a gold standard for the tooth size. Arch width was calculated from the existing set-ups on the dentins.Impressions were taken of the casts with alginate and duplicated with dental stone. Models were measured with digital caliper manually. Then images were taken from the occlusal views of the casts by a digital camera. Measurements were done on digital images with the AutoCAD software.The results of the computerized and manual methods were compared with the gold standard.Intra class correlation coefficient of reliability was used to measure the accuracy ofthe methods and the Friedman technique used to evaluate the significance of differences.Results: Results indicated that all measurements were highly correlated, e.g. gold standard and manual (0.9613-0.9991), gold standard and computerized (0.7118-0.9883), manual and computerized (0.6734-0.9914). Statistically significant differences were present between these methods (P<0.05), but they proved not to be clinically significant.Conclusion: Manual measurement is still the most accurate method when compared to the computerized measurements and the results of measurement by computer should be interpreted with caution

Heterozygous loss of keratinocyte TRIM16 expression increases melanocytic cell lesions and lymph node metastasis

© 2019, The Author(s). Purpose: The tripartite motif (TRIM)16 acts as a tumour suppressor in both squamous cell carcinoma (SCC) and melanoma. TRIM16 is known to be secreted by keratinocytes, but no studies have been reported yet to assess the relationship between TRIM16 keratinocyte expression and melanoma development. Methods: To study the role of TRIM16 in skin cancer development, we developed a keratinocyte TRIM16-specific knockout mouse model, and used the classical two-stage skin carcinogenesis challenge method, to assess the loss of keratinocyte TRIM16 on both papilloma, SCC and melanoma development in the skin after topical carcinogen treatment. Results: Heterozygous, but not homozygous, TRIM16 knockout mice exhibited an accelerated development of skin papillomas and melanomas, larger melanoma lesions and an increased potential for lymph node metastasis. Conclusion: This study provides the first evidence that keratinocyte loss of the putative melanoma tumour suppressor protein, TRIM16, enhances melanomagenesis. Our data also suggest that TRIM16 expression in keratinocytes is involved in cross talk between keratinocytes and melanocytes, and has a role in melanoma tumorigenesis

CD30 and ALK combination therapy has high therapeutic potency in RANBP2-ALK-rearranged epithelioid inflammatory myofibroblastic sarcoma

Background: Epithelioid inflammatory myofibroblastic sarcoma (eIMS) is characterised by perinuclear ALK localisation, CD30 expression and early relapse despite crizotinib treatment. We aimed to identify therapies to prevent and/or treat ALK inhibitor resistance. Methods: Malignant ascites, from an eIMS patient at diagnosis and following multiple relapses, were used to generate matched diagnosis and relapse xenografts. Results: Xenografts were validated by confirmation of RANBP2-ALK rearrangement, perinuclear ALK localisation and CD30 expression. Although brentuximab-vedotin (BV) demonstrated single-agent activity, tumours regrew during BV therapy. BV resistance was associated with reduced CD30 expression and induction of ABCB1. BV resistance was reversed in vitro by tariquidar, but combination BV and tariquidar treatment only briefly slowed xenograft growth compared with BV alone. Combining BV with either crizotinib or ceritinib resulted in marked tumour shrinkage in both xenograft models, and resulted in prolonged tumour-free survival in the diagnosis compared with the relapse xenograft. Conclusions: CD30 is a therapeutic target in eIMS. BV efficacy is limited by the rapid emergence of resistance. Prolonged survival with combination ALK and CD30-targeted-therapy in the diagnosis model provides the rationale to trial this combination in eIMS patients at diagnosis. This combination could also be considered for other CD30-positive, ALK-rearranged malignancies

Inhibitors of the Oncogenic PA2G4-MYCN Protein-Protein Interface

MYCN is a major oncogenic driver for neuroblastoma tumorigenesis, yet there are no direct MYCN inhibitors. We have previously identified PA2G4 as a direct protein-binding partner of MYCN and drive neuroblastoma tumorigenesis. A small molecule known to bind PA2G4, WS6, significantly decreased tumorigenicity in TH-MYCN neuroblastoma mice, along with the inhibition of PA2G4 and MYCN interactions. Here, we identified a number of novel WS6 analogues, with 80% structural similarity, and used surface plasmon resonance assays to determine their binding affinity. Analogues #5333 and #5338 showed direct binding towards human recombinant PA2G4. Importantly, #5333 and #5338 demonstrated a 70-fold lower toxicity for normal human myofibroblasts compared to WS6. Structure-activity relationship analysis showed that a 2,3 dimethylphenol was the most suitable substituent at the R1 position. Replacing the trifluoromethyl group on the phenyl ring at the R2 position, with a bromine or hydrogen atom, increased the difference between efficacy against neuroblastoma cells and normal myofibroblast toxicity. The WS6 analogues inhibited neuroblastoma cell phenotype in vitro, in part through effects on apoptosis, while their anti-cancer effects required both PA2G4 and MYCN expression. Collectively, chemical inhibition of PA2G4-MYCN binding by WS6 analogues represents a first-in-class drug discovery which may have implications for other MYCN-driven cancers

A novel combination therapy targeting ubiquitin-specific protease 5 in MYCN-driven neuroblastoma

Histone deacetylase (HDAC) inhibitors are effective in MYCN-driven cancers, because of a unique need for HDAC recruitment by the MYCN oncogenic signal. However, HDAC inhibitors are much more effective in combination with other anti-cancer agents. To identify novel compounds which act synergistically with HDAC inhibitor, such as suberanoyl hydroxamic acid (SAHA), we performed a cell-based, high-throughput drug screen of 10,560 small molecule compounds from a drug-like diversity library and identified a small molecule compound (SE486-11) which synergistically enhanced the cytotoxic effects of SAHA. Effects of drug combinations on cell viability, proliferation, apoptosis and colony forming were assessed in a panel of neuroblastoma cell lines. Treatment with SAHA and SE486-11 increased MYCN ubiquitination and degradation, and markedly inhibited tumorigenesis in neuroblastoma xenografts, and, MYCN transgenic zebrafish and mice. The combination reduced ubiquitin-specific protease 5 (USP5) levels and increased unanchored polyubiquitin chains. Overexpression of USP5 rescued neuroblastoma cells from the cytopathic effects of the combination and reduced unanchored polyubiquitin, suggesting USP5 is a therapeutic target of the combination. SAHA and SE486-11 directly bound to USP5 and the drug combination exhibited a 100-fold higher binding to USP5 than individual drugs alone in microscale thermophoresis assays. MYCN bound to the USP5 promoter and induced USP5 gene expression suggesting that USP5 and MYCN expression created a forward positive feedback loop in neuroblastoma cells. Thus, USP5 acts as an oncogenic cofactor with MYCN in neuroblastoma and the novel combination of HDAC inhibitor with SE486-11 represents a novel therapeutic approach for the treatment of MYCN-driven neuroblastoma