An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment

Most current anti-worm systems and intrusion-detection systems use signature-based technology instead of anomaly-based technology. Signature-based technology can only detect known attacks with identified signatures. Existing anti-worm systems cannot detect unknown Internet scanning worms automatically because these systems do not depend upon worm behaviour but upon the worm’s signature. Most detection algorithms used in current detection systems target only monomorphic worm payloads and offer no defence against polymorphic worms, which changes the payload dynamically. Anomaly detection systems can detect unknown worms but usually suffer from a high false alarm rate. Detecting unknown worms is challenging, and the worm defence must be automated because worms spread quickly and can flood the Internet in a short time. This research proposes an accurate, robust and fast technique to detect and contain Internet worms (monomorphic and polymorphic). The detection technique uses specific failure connection statuses on specific protocols such as UDP, TCP, ICMP, TCP slow scanning and stealth scanning as characteristics of the worms. Whereas the containment utilizes flags and labels of the segment header and the source and destination ports to generate the traffic signature of the worms. Experiments using eight different worms (monomorphic and polymorphic) in a testbed environment were conducted to verify the performance of the proposed technique. The experiment results showed that the proposed technique could detect stealth scanning up to 30 times faster than the technique proposed by another researcher and had no false-positive alarms for all scanning detection cases. The experiments showed the proposed technique was capable of containing the worm because of the traffic signature’s uniqueness

Study on Safety Construction Management Plan

After studying the reality of application to occupational safety in new Iraqi building projects and sampling the situation wilt that in developed and neighboring countries, researcher found that there is a big gap in the level of safety application conditions, this indicates the need fora quick and clear reference for local engineers to use it on site for safety conditions in their projects . As a case study the monitors work the researcher studied a huge project in the United Arab Emirates.This project considered for safety requirements to highest grades. This case study may be far away from the projects in Iraq, but we hope to rise the Iraqi work level in the near future. After seeing the way of administration work and how they were rated the severity of each phase of the work, an idea was builtabout the most dangerous situations in projects with multiple floorsbuildings. To find multiple solutions to the risk, researchers identified 46 cases with their ratings, type of perceived risk in each case, and displayed a format survey to the most important specialized institutions and companies operating in Iraq and the United Arab Emirates. Finally theresearcher takes the results,and format a software that any user can use in his personal computer to studythe expected risk,how to avoid it and how to deal with it if it happens

A new generation for intelligent anti-internet worm early system detection

Worm requires host computer with an address on the Internet and any of several vulnerabilities to create a big threat environment.We propose intelligent early system detection mechanism for detecting internet worm.The mechanism is combined of three techniques: Failure Connection Detection (FCD) which concerns with detecting the internet worm and stealthy worm in which computer infected by the worm by using Artificial Immune System; and the Traffic Signature Detection (TSD) which responsible for detecting traffic signature for the worm; and the DNA Filtering Detection (DNAFD) which converts traffic signature to DNA signature and sending it to all computer that connected with the router to create a firewall for new worms.Our proposed algorithm can detect difficult stealthy internet worm in addition to detecting unknown internet worm

Server scanning worm detection by using intelligent failure connection algorithm

On July 19th 2001, Code-Red was released to the internet. After fourteen hours the worn infected 36,000 hosts. Internet worn procedure spreads autonomously from one host to another, worm requires host computer with an address on the Internet and any of several vulnerabilities to create a big threat environment. The aim of this study is to propose Server Worm Register (SWD) to register the number of computers that are infected by the worm. Our proposal decreases the false alarm in Intelligent Failure Connection Algorithm (IFCA). Our proposal also works when the computer is infected by the worm and IFCDA detected the worm, many computers that are connected through the internet will receive the warning by using our proposal. We have found IFCA is more reliable by using SWD because it reduced the false alarm

A traffic signature-based algorithm for detecting scanning internet worms

Internet worms that spread autonomously from one host to another cause major problem in today’s networks. On 25th January 2003, “Slammer” was released into the internet and after ten minutes the worm infected more than 90% of vulnerable hosts.Worms cause damage to the network by consuming its resources such as bandwidth. In this paper, we propose a method for detecting traffic signature for unknown internet worm. The proposed method has two algorithms. The first part is an Intelligent Failure Connection Algorithm (IFCA) using Artificial Immune System; IFCA is concerned with detecting the internet worm and stealthy worm. In order to reduce the number of false alarm, the impact of normal network activities is involved but TCP failure and ICMP unreachable connection on same IP address are not calculated because the internet worm strategic attack on the different IP address. The second algorithm Traffic Signature Algorithm (TSA) is concerned with capturing traffic signature of the scanning internet worm. In this paper, we show that the proposed method can detect traffic signature for MSBlaster worm

Intelligent failure connection algorithm for detecting internet worms

Morris worm showed the Internet community for the first time in 1988 that a worm could bring the Internet down in hours.Worm requires host computer with an address on the Internet and any of several vulnerabilities to create a big threat environment.We propose intelligent early system detection mechanism for detecting internet worm.The mechanism of our technique is concerned with detecting the internet worm and stealthy internet worm.The average of failure connections by using Artificial Immune System (AIS) is the main factor that our technique depends on in detecting the worm. In this paper, we show that our algorithm can detect new types of worms. This paper shows that intelligent Failure Connection Algorithm (IFCA) operation is faster than traditional algorithm in detecting worms

Occurrence of Tomato Leaf Miner Tuta Absoluta Meyrick(Lepidoptera:Gelechiidae) in Duhok Region (A)

The aim of this work is to investigate the population density and infestation percentage of Tuta absoluta on tomato crop Lycopersicum esculentumMill under field conditions in three locations at Duhok province/ Kurdistan region/ northern of Iraq in 2012. The average number of mines/ leaflet, larvae/ leaf and larvae/ fruit during the study season were 2.33, 0.34 and 0.61 respectively. The results showed a significant differences in infestation percentage and number of male per trap among the three locations. The highest percentage of infestation was recorded in September as 74.00, 72.00 and 60.00 for Summel, Shekhan and Zawita respectively. The maximum number of males/ trap/ week was 1205.40 recorded on 26/8/2012 in Summel. Concerning the use of pheromone trap for pest monitoring, linear regression analysis results was significant between trap catches and the number of mines per leaf and the infestation rate of leave

Genomic alterations and the incidence of brain metastases in advanced and metastatic non-small cell lung cancer: a systematic review and meta-analysis.

BackgroundBrain metastases (BM) in patients with advanced and metastatic non-small cell lung cancer (NSCLC) are linked with poor prognosis. Identifying genomic alterations associated with BM development could influence screening and determine targeted treatment. We aimed to establish prevalence and incidence in these groups, stratified by genomic alterations.Patients and methodsA PRISMA-compliant systematic review and meta-analysis was conducted (PROSPERO ID CRD42022315915). Articles published in MEDLINE, EMBASE, and Cochrane Library between January 2000-May 2022 were included. Prevalence at diagnosis, and incidence of new BM per year were obtained, including patients with EGFR, ALK, KRAS, and other alterations. Pooled incidence rates were calculated using random effects models.ResultsSixty-four unique articles were included (24,784 NSCLC patients with prevalence data from forty-five studies and 9,058 NSCLC patients with incidence data from forty studies). Pooled BM prevalence at diagnosis was 28.6% (45 studies, 95% Confidence Interval [CI] 26.1-31.0), and highest in patients that are ALK-positive (34.9%) or with RET-translocations (32.2%). With a median follow-up of 24 months, per-year incidence of new BM was 0.13 in the wild-type group (14 studies, 95% CI 0.11-0.16). Incidence was 0.16 in the EGFR group (16 studies, 95% CI 0.11-0.21), 0.17 in the ALK group (5 studies, 95% CI 0.10-0.27), 0.10 in the KRAS group (4 studies, 95% CI 0.06-0.17), 0.13 in the ROS1 group (3 studies, 95% CI 0.06-0.28), and 0.12 in the RET group (2 studies, 95% CI 0.08-0.17).ConclusionsComprehensive meta-analysis indicates a higher prevalence and incidence of BM in patients with certain targetable genomic alterations. This supports brain imaging at staging and follow-up, and the need for targeted therapies with brain penetrance

Genome-wide analysis of blood lipid metabolites in over 5000 South Asians reveals biological insights at cardiometabolic disease loci.

Funder: PfizerFunder: NovartisFunder: National Institute for Health ResearchFunder: MerckBackgroundGenetic, lifestyle, and environmental factors can lead to perturbations in circulating lipid levels and increase the risk of cardiovascular and metabolic diseases. However, how changes in individual lipid species contribute to disease risk is often unclear. Moreover, little is known about the role of lipids on cardiovascular disease in Pakistan, a population historically underrepresented in cardiovascular studies.MethodsWe characterised the genetic architecture of the human blood lipidome in 5662 hospital controls from the Pakistan Risk of Myocardial Infarction Study (PROMIS) and 13,814 healthy British blood donors from the INTERVAL study. We applied a candidate causal gene prioritisation tool to link the genetic variants associated with each lipid to the most likely causal genes, and Gaussian Graphical Modelling network analysis to identify and illustrate relationships between lipids and genetic loci.ResultsWe identified 253 genetic associations with 181 lipids measured using direct infusion high-resolution mass spectrometry in PROMIS, and 502 genetic associations with 244 lipids in INTERVAL. Our analyses revealed new biological insights at genetic loci associated with cardiometabolic diseases, including novel lipid associations at the LPL, MBOAT7, LIPC, APOE-C1-C2-C4, SGPP1, and SPTLC3 loci.ConclusionsOur findings, generated using a distinctive lipidomics platform in an understudied South Asian population, strengthen and expand the knowledge base of the genetic determinants of lipids and their association with cardiometabolic disease-related loci

Microbiologically-influenced corrosion of the electroless-deposited NiP-TiNi – Coating

In this study, we reveal the microbiologically influenced corrosion (MIC) behavior of the new electroless NiP-TiNi nanocomposite coating in simulated seawater using the electrochemical impedance spectroscopy (EIS) technique after different periods of incubation time (7, 10, 14, 21, 28 days) in a sulfate-reducing bacteria (SRB) medium. The biofilm formation and the corrosion products were characterized using the scanning electron microscope (SEM) and X-ray photoelectron spectroscopy (XPS). The EIS results revealed the carbon steel (CS)/NiP-TiNi and NiP-TiNi/SRB biofilm interfaces' characteristics after different incubation times in the SRB media. EIS measurements revealed that the NiP-TiNi nanocomposite coating's MIC resistances are superior relative to API X80 carbon steel and a TiNi-free NiP coating, with ∼93% of corrosion inhibition efficiency after 28 days of incubation