Data-driven curation, learning and analysis for inferring evolving IoT botnets in the wild

The insecurity of the Internet-of-Things (IoT) paradigm continues to wreak havoc in consumer and critical infrastructure realms. Several challenges impede addressing IoT security at large, including, the lack of IoT-centric data that can be collected, analyzed and correlated, due to the highly heterogeneous nature of such devices and their widespread deployments in Internet-wide environments. To this end, this paper explores macroscopic, passive empirical data to shed light on this evolving threat phenomena. This not only aims at classifying and inferring Internet-scale compromised IoT devices by solely observing such one-way network traffic, but also endeavors to uncover, track and report on orchestrated "in the wild" IoT botnets. Initially, to prepare the effective utilization of such data, a novel probabilistic model is designed and developed to cleanse such traffic from noise samples (i.e., misconfiguration traffic). Subsequently, several shallow and deep learning models are evaluated to ultimately design and develop a multi-window convolution neural network trained on active and passive measurements to accurately identify compromised IoT devices. Consequently, to infer orchestrated and unsolicited activities that have been generated by well-coordinated IoT botnets, hierarchical agglomerative clustering is deployed by scrutinizing a set of innovative and efficient network feature sets. By analyzing 3.6 TB of recent darknet traffic, the proposed approach uncovers a momentous 440,000 compromised IoT devices and generates evidence-based artifacts related to 350 IoT botnets. While some of these detected botnets refer to previously documented campaigns such as the Hide and Seek, Hajime and Fbot, other events illustrate evolving threats such as those with cryptojacking capabilities and those that are targeting industrial control system communication and control services

The general purpose analog computer and computable analysis are two equivalent paradigms of analog computation

In this paper we revisit one of the rst models of analog computation, Shannon's General Purpose Analog Computer (GPAC). The GPAC has often been argued to be weaker than computable analysis. As main contribution, we show that if we change the notion of GPACcomputability in a natural way, we compute exactly all real computable functions (in the sense of computable analysis). Moreover, since GPACs are equivalent to systems of polynomial di erential equations then we show that all real computable functions can be de ned by such models

Malignant Salivary Glands Tumors in Kerman Province: A Retrospective Study

Introduction: Malignant salivary glands tumors (MSGTs) are uncommon cancers. The most common site of these cancers is the parotid gland. Some investigations show these cancers preference for males than females. The majority of MSGTs arise in sixth decade of human life. According to the literature review for the present work, there is a few epidemiological researches about MSGTs in Iran and especially there isn't any study in Kerman province. So the aim of this study was investigation the incidence, sex, age, histological types, and site distribution of MSGTs in the Kerman province during the time period from March 1991 to March 2002.Methods and Materials: Documents and records of 70 patients with MSGTs diagnosed from March 1991 to March 2002 were reviewed. The patients' records were analyzed based on gender, age, location, and histopathological type of the tumor. Data were analyzed by SPSS-13.5 statistical software using t-test, chi-square, and ANOVA tests.Results: During this period of time, 70 cases (43men, 27 women) of MSGTs had been diagnosed. Mucoepidermoid carcinoma was the most common cancer (30%) and the parotid was the most affected site (70%). The age range was 10-86 years old with the overall mean age of 50.18 ± 17.97.Discussion: Despite a considerable volume of literatures written about MSGTs in many countries, the incidence of these cancers haven't as yet been thoroughly documented or analyzed in Iran. However, comparison between the findings of this study with the results of other investigations showed a relative consistency