A Novel Ensemble Method for Advanced Intrusion Detection in Wireless Sensor Networks

© 2020 IEEE. With the increase of cyber attack risks on critical infrastructures monitored by networked systems, robust Intrusion Detection Systems (IDSs) for protecting the information have become vital. Designing an IDS that performs with maximum accuracy with minimum false alarms is a challenging task. Ensemble method considered as one of the main developments in machine learning in the past decade, it finds an accurate classifier by combining many classifiers. In this paper, an ensemble classification procedure is proposed using Random Forest (RF), DensityBased Spatial Clustering of Applications with Noise (DBSCAN) and Restricted Boltzmann Machine (RBM) as base classifiers. RF, DBSCAN, and RBM techniques have been used for classification purposes. The ensemble model is introduced for achieving better results. Bayesian Combination Classification (BCC) has been adopted as a combination technique. Independent BCC (IBCC) and Dependent BCC (DBCC) have been tested for performance comparison. The model shows a promising result for all classes of attacks. DBCC performs over IBCC in terms of accuracy and detection rates. Through simulations under a wireless sensor network scenario, we have verified that DBCC-based IDS works with \approx 100\% detection and \approx 1.0 accuracy rate in the existence of intrusive behavior in the tested Wireless Sensor Network (WSN)

Prior Knowledge based Advanced Persistent Threats Detection for IoT in a Realistic Benchmark

The number of Internet of Things (IoT) devices being deployed into networks is growing at a phenomenal level, which makes IoT networks more vulnerable in the wireless medium. Advanced Persistent Threat (APT) is malicious to most of the network facilities and the available attack data for training the machine learning-based Intrusion Detection System (IDS) is limited when compared to the normal traffic. Therefore, it is quite challenging to enhance the detection performance in order to mitigate the influence of APT. Therefore, Prior Knowledge Input (PKI) models are proposed and tested using the SCVIC-APT- 2021 dataset. To obtain prior knowledge, the proposed PKI model pre-classifies the original dataset with unsupervised clustering method. Then, the obtained prior knowledge is incorporated into the supervised model to decrease training complexity and assist the supervised model in determining the optimal mapping between the raw data and true labels. The experimental findings indicate that the PKI model outperforms the supervised baseline, with the best macro average F1-score of 81.37%, which is 10.47% higher than the baseline.Comment: IEEE Global Communications Conference (Globecom), 2022, 6 pages, g figures, 6 table

Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats

Despite its technological benefits, Internet of Things (IoT) has cyber weaknesses due to the vulnerabilities in the wireless medium. Machine learning (ML)-based methods are widely used against cyber threats in IoT networks with promising performance. Advanced persistent threat (APT) is prominent for cybercriminals to compromise networks, and it is crucial to long-term and harmful characteristics. However, it is difficult to apply ML-based approaches to identify APT attacks to obtain a promising detection performance due to an extremely small percentage among normal traffic. There are limited surveys to fully investigate APT attacks in IoT networks due to the lack of public datasets with all types of APT attacks. It is worth to bridge the state-of-the-art in network attack detection with APT attack detection in a comprehensive review article. This survey article reviews the security challenges in IoT networks and presents the well-known attacks, APT attacks, and threat models in IoT systems. Meanwhile, signature-based, anomaly-based, and hybrid intrusion detection systems are summarized for IoT networks. The article highlights statistical insights regarding frequently applied ML-based methods against network intrusion alongside the number of attacks types detected. Finally, open issues and challenges for common network intrusion and APT attacks are presented for future research.Comment: ACM Computing Surveys, 2022, 35 pages, 10 Figures, 8 Table

Availability constrained routing and wavelength assignment techniques for optical WDM networks

Dalgaboyu bölmeli çoğullama (WDM) tekniği ile optik ağlar tarafından sunulan yüksek bandgenişliği, optik hatlarda veya ağ bileşenlerinde oluşabilecek hatalar karşısında da yoğun miktarda veri kaybı riskini beraberinde getirmektedir. Bu durumun önüne geçmek için, bağlantılar belirli bir sürdürülebilirlik politikası ile korunarak kurulmaktadır. Ağda oluşabilecek hata durumlarınnda da bağlantının kullanılabilir ve sunulan hizmetin kesintisiz olması kullanıcılar tarafından beklenmektedir. Bu nedenle, bağlantı istekleri kurulurken, yol ve dalgaboyu atamasında, ilgili sürdürülebilirlik politikası altında kullanılabilirlik kısıtının göz önünde bulundurulması gerekmektedir. Bu çalışmada, paylaşımlı yol koruma politikası altında kurulan bağlantıların kullanılabilirlik isteklerini göz önünde bulundurarak yol ve dalgaboylarını atayan iki farklı teknik önerilmektedir. Bu tekniklerden ilki, G-DAP (Global Differentiated Availability-Aware Provisioning) sezgisel olarak yedek dalgaboyu kanalları üzerinde, her bir kullanılabilirlik sınıfı için global bir paylaşım derecesi kestirir. Diğer teknik LBL-DAP (Link-By-Link Differentiated Availability-Aware Provisioning) ise bir optimizasyon modeli kullanarak, her bir kullanılabilirlik sınıfı için yedek kanallar üzerindeki paylaşım derecesini, her bir optik hat için ayrıca hesaplar. Bağlantı isteklerinin %98, %99, %99.9, %99.99% ve %99.999 kullanılabilik düzeyinin birinden geldiği ortamda yapılan testlerde, önerilen teknikler yaygın olan CAFES (Compute-A-Feasible Solution) algoritmasıyla NSFNET ve EON topolojilerinde karşılaştırılmıştır. Bağlantıların sınıflar arasında düzgün ve heterojen dağıldığı ortamlarda toplanan sonuçlar, önerilen tekniklerin daha yüksek bağlantı kabul oranı ve kullanılabilirlik sağladığını göstermektedir. Ayrıca, yedek kaynak kullanım oranını düşürmesi nedeniyle LBL-DAP’ın en iyi başarımı sağladığı görülmüştür. Anahtar Kelimeler: Optik ağlar, dalgaboyu bölmeli çoğullama, kullanılabilirlik, yol atama.As a result of the increase in the bandwidth demand of the next generation Internet applications, Optical Wavelength division Multiplexing (WDM) networks seem to be the most appropriate technology that can be deployed in the backbone. Optical WDM networks introduce the advantage of offering bandwidth partitioned into a number of gigabits per second wavelength channels. However, the advantage introduced by the huge bandwidth offer also introduces a disadvantage when the network experiences a failure. Service interrupts on any component along the lightpath may lead to significant amount of data loss since the fiber capacity is huge. Factors like multiple errors, long fault recovery duration, and component failure characteristics introduce availability constraint for the network elements, and also for the connections. Therefore, connections are required to be provisioned by taking availability constraint into consideration. In short, availability stands for the probability of a network component, a channel or a link being in the operational state at any time t. Significant amount of the previous work is concerned with availability aware routing and wavelength assignment (RWA) under shared backup protection. The first and the most common availability aware routing scheme is compute-a-feasible-solution (CAFES). In this scheme, a number of candidate working paths are selected. For each working path, a corresponding backup path is selected by forcing the backup channels to be shared. The working and backup path pair that leads to the highest availability or another lowest cost metric is selected, and assigned to the incoming connection request. In this work, we present two dynamic connection provisioning schemes for differentiated availability-constrained RWA. Both of the schemes are derived from the conventional reliable provisioning scheme CAFES. In the dynamic environment, connections arrive with the availability requirements of 98% (class-1), 99% (class-2), 99.9% (class-3), 99.99% (class-4), and 99.999% (class-5). First scheme is called Global Differentiated Availability-aware Provisioning (G-DAP). This scheme monitors the average availability per connection for each class and resource-overbuild throughout the network. In order to enhance the performance of the connection provisioning, G-DAP also takes the advantage of the trade-off between resource overbuild and connection unavailability where resource overbuild is the ratio of the number of backup channels to the number of working channels in the network, and unavailability is one's complement of the availability. Based on the change in these two parameters it attempts to specify a feasible global sharing degree for all wavelength channels per availability class. The trade-off function is defined as the product of these two parameters. Hence, if the tradeoff is monitored to be decreasing for the related availability class, the last action (increment or decrement) taken on the sharing degree of that class is repeated; otherwise, it is reversed. The second scheme is called Link-by-Link Differentiated Availability-aware Provisioning (LBL-DAP). LBL-DAP estimates a separate feasible sharing degree per class for the channels of each link. It periodically runs an integer linear programming (ILP) function to obtain the feasible sharing degrees on each link. When searching for a backup RWA configuration, both schemes modify the link costs based on the feasible sharing degree obtained for the availability class of the incoming connection and current load for the connection?s class on the link respectively. Since we aim to improve the performance in terms of resource overbuild, connection availability, and blocking probability, we use the conventional reliable provisioning scheme, CAFES as a base in our simulations. Moreover, since connections arrive with differentiated availability requirements, we also modify CAFES to enable a connection to be provisioned unprotected if a selected working path can meet its availability requirement. Thus, resource consumption overhead of this scheme is modified for its favor. Performance of G-DAP and LBL-DAP are compared to that of CAFES by simulation under NSFNET and EON topologies. Simulation results are collected under two different conditions where the connection requests are distributed uniformly and heterogeneously among the availability classes. It is shown that the proposed schemes lead to enhanced blocking ratio and connection availability. Moreover, by taking the advantage of optimization and considering the feasible sharing degrees for the links separately, LBL-DAP also introduces significant decrease in resource overbuild. Keywords: Optical networks, wavelength division multiplexing, availability, routing

Cor triatriatum sinister: two cases diagnosed in adulthood and a review of literature

Cor triatriatum sinister is a rare condition caused by a membrane within left atrium that separates pulmonary veins from mitral valve (10). While the condition is usually diagnosed at childhood, rare presentation during adulthood is observed when the membrane is incomplete. We report two cases of incomplete cor triatriatum sinister diagnosed during adulthood and review literature for this rare anomaly

Apoptosis in Gingival Overgrowth Tissues

Variations in the balance between cell proliferation and apoptosis could contribute to the etiology of gingival overgrowth. The aim of this study was to test the hypothesis that, in fibrotic gingival lesions, fibroblast proliferation is stimulated and apoptosis is decreased. Apoptotic index, caspase 3 expression, the proliferative index, FOXO1 expression, and histological inflammation were measured in situ. Analysis of data showed that apoptosis decreased in all forms of gingival overgrowth examined (p \u3c 0.05), and inflammation caused a small but significant increase compared with non-inflamed tissues (p \u3c 0.05). The greatest decrease of apoptosis occurred in the most fibrotic tissues. Cell proliferation was elevated in all forms of gingival overgrowth tested, independent of inflammation (p \u3c 0.05). To identify potential mechanisms of transcriptional regulation of apoptosis, we assessed FOXO1 and caspase 3 expression levels and found them to correlate well with diminished apoptosis. Analysis of data suggests that increased fibroblast proliferation and a simultaneous decrease in apoptosis contribute to gingival overgrowth

Rates of lobar atrophy in asymptomatic MAPT mutation carriers.

IntroductionThe aim of this study was to investigate the rates of lobar atrophy in the asymptomatic microtubule-associated protein tau (MAPT) mutation carriers.MethodsMAPT mutation carriers (n = 14; 10 asymptomatic, 4 converters from asymptomatic to symptomatic) and noncarriers (n = 13) underwent structural magnetic resonance imaging and were followed annually with a median of 9.2 years. Longitudinal changes in lobar atrophy were analyzed using the tensor-based morphometry with symmetric normalization algorithm.ResultsThe rate of temporal lobe atrophy in asymptomatic MAPT mutation carriers was faster than that in noncarriers. Although the greatest rate of atrophy was observed in the temporal lobe in converters, they also had increased atrophy rates in the frontal and parietal lobes compared to noncarriers.DiscussionAccelerated decline in temporal lobe volume occurs in asymptomatic MAPT mutation carriers followed by the frontal and parietal lobe in those who have become symptomatic. The findings have implications for monitoring the progression of neurodegeneration during clinical trials in asymptomatic MAPT mutation carriers

Do magnetic resonance imaging features differ between persons with multiple sclerosis of various races and ethnicities?

Those of African American or Latin American descent have been demonstrated to have more severe clinical presentations of multiple sclerosis (MS) than non-Latin American White people with MS. Concurrently, radiological burden of disease on magnetic resonance imaging (MRI) in African Americans with MS has also been described as being more aggressive. Here, we review MRI studies in diverse racial and ethnic groups (adult and pediatric) investigating lesion burden, inflammation, neurodegeneration, and imaging response to disease modifying therapy. We also discuss why such disparities may exist beyond biology, and how future studies may provide greater insights into underlying differences