AppPerm Analyzer: Malware Detection System Based on Android Permissions and Permission Groups

2020 ◽  
Vol 30 (03) ◽  
pp. 427-450 ◽  
Author(s):  
İbrahim Alper Doğru ◽  
Murat Önder
Keyword(s):  
Mobile Devices ◽  
Detection System ◽  
Risk Scores ◽  
True Positive ◽  
Android Application ◽  
Total Risk ◽  
True Negative ◽  
Android Malware ◽  
Positive Ratio ◽  
False Positive Ratio

Besides the applications aimed at increasing the efficiency of the Android mobile devices, also many malicious applications, millions of Android malware according to various security company reports, are being developed and uploaded into the application stores. In order to detect those applications, a malicious Android application detection system based on permission and permission groups namely, AppPerm Analyzer has been developed. The AppPerm Analyzer software extracts the manifest and code permissions of analyzed applications, creates duple and triple permission groups from them, calculates risk scores of these permissions and permission groups according to their usage rates in malicious and benign applications and calculates the total risk score of the analyzed application. After training the software with 7776 applications in total, it is tested with 1664 benign and 1664 malicious applications. In the tests, AppPerm Analyzer detected malicious applications with an accuracy of 96.19% at most. At this point, sensitivity (true-positive ratio) is 95.50% and specificity (true-negative ratio) is 96.88%. If a false-positive ratio up to 10% is accepted, the sensitivity increases to 99.04%.

Epileptic Seizure Detection System Based on Multi-Domain Feature and Spike Feature of EEG

2019 ◽  
Vol 16 (04) ◽  
pp. 1950016 ◽  
Author(s):  
Duanpo Wu ◽  
Zimeng Wang ◽  
Hong Huang ◽  
Guangsheng Wang ◽  
Junbiao Liu ◽  
...  
Keyword(s):  
Detection System ◽  
Epileptic Seizures ◽  
Seizure Detection ◽  
Spike Rate ◽  
Linear Discriminant ◽  
Positive Ratio ◽  
False Positive Ratio ◽  
Eeg Data ◽  
The Family

Epilepsy is caused by sudden abnormal discharges of neurons in the brain. This paper constructs an automatic seizure detection system, which combines the predicting result of multi-domain feature with the predicting result of spike rate feature to detect the occurrence of epileptic seizures. After segmenting EEG data into 5[Formula: see text]s with 80% overlap epochs, the paper extracts time domain features, frequency domain features and hurst exponents (HE) from each epoch and these features are reduced by linear discriminant analysis (LDA) to be input parameters of the random forest (RF) classifier, which provides classification of the EEG epochs concerning the existence of seizures. In parallel, the paper extracts spikes from EEG data with morphological filter and calculates the spike rate to determine whether there is seizure. Then the results obtained by these two methods are merged as the final detection result. The paper shows that the accuracy (AC), sensitivity (SE), specificity (SP) and the false positive ratio based on event (FPRE) obtained by hybrid method are 98.94%, 76.60%, 98.99% and 2.43 times/h, respectively. Finally, the paper applies the seizure detection method to do seizure warning and recording to help the family member to take care of the patients and the doctor to adjust the antiepileptic drugs (AEDs).

scholarly journals Intrusion Detection System in Manets

2019 ◽  
Vol 8 (4) ◽  
pp. 12801-12803
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Hybrid Approach ◽  
Positive Ratio ◽  
False Positive Ratio ◽  
Attack Patterns ◽  
New Type ◽  
Prevention Techniques ◽  
Ratio Detection

One of the most challenging issue nowadays is providing security on MANET architecture. The key issue in MANET is the design of intrusion detection system, that is able to detect attacks in a rapid manner .Traditional methods like genetic algorithms, fuzzy logic, game theory techniques are helpful in designing of IDs. However, these techniques have a limitation on the effects of prevention techniques in general and they are designed for a set of known attacks. These techniques are also tends to increase the false positive ratio, detection rate is low and values of ROC characteristics due to training of feature set of attack patterns . The techniques also failed to detect any new type of attacks by any existing methods. This paper focuses on designing of intrusion detection system based on hybrid approach that effectively able to detect any type of attacks using Evolutionary algorithm techniques.

scholarly journals A Dynamic and Combined Phishing Detection Technique

2020 ◽  
Vol 9 (5) ◽  
pp. 1421-1425
Keyword(s):  
Web Applications ◽  
Cyber Attacks ◽  
Grocery Shopping ◽  
Cyber Attack ◽  
True Negative ◽  
Positive Ratio ◽  
Phishing Attacks ◽  
Internet Users ◽  
False Positive Ratio ◽  
Phishing Detection

With the quick advancement of web applications, internet users are spending more and more time with these applications .They utilize the benefits of the internet in doing all the day-to-day chores from reading newspaper to grocery shopping .This makes them prone to various kinds of cyber-attacks such as phishing , password attack , malwares etc...Phishing is one of the most common cyber-attack which is made by the attackers to take the users’ delicate data . In phishing attack the users are first tempted with attractive offers and are then redirected to illegitimate (phishing) websites which ask for their credentials .In spite of the alert and awareness spread against these types of cyber-attacks , people continue to fall prey and get affected .The attackers have evolved with time and craft the attacks in such a way that the phishing websites and emails may seem real .Many systems and algorithms have been developed to predict phishing attacks .However ,the achievement rate of phishing attacks stays high and it’s detection is prone towards high true negative and false positive ratio. Therefore ,to deal with this conundrum we are putting forward a generalized algorithm for phishing detection with improved accuracy.

scholarly journals Fully Automatic Fall Risk Assessment Based on a Fast Mobility Test

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1338
Author(s):  
Wojciech Tylman ◽  
Rafał Kotas ◽  
Marek Kamiński ◽  
Paweł Marciniak ◽  
Sebastian Woźniak ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Fall Risk ◽  
Low Cost ◽  
Body Movement ◽  
Sole Source ◽  
Timed Up And Go ◽  
True Negative ◽  
Fall Risk Assessment ◽  
Positive Ratio ◽  
Mobility Test

This paper presents a fall risk assessment approach based on a fast mobility test, automatically evaluated using a low-cost, scalable system for the recording and analysis of body movement. This mobility test has never before been investigated as a sole source of data for fall risk assessment. It can be performed in a very limited space and needs only minimal additional equipment, yet provides large amounts of information, as the presented system can obtain much more data than traditional observation by capturing minute details regarding body movement. The readings are provided wirelessly by one to seven low-cost micro-electro-mechanical inertial measurement units attached to the subject’s body segments. Combined with a body model, these allow segment rotations and translations to be computed and for body movements to be recreated in software. The subject can then be automatically classified by an artificial neural network based on selected values in the test, and those with an elevated risk of falls can be identified. Results obtained from a group of 40 subjects of various ages, both healthy volunteers and patients with vestibular system impairment, are presented to demonstrate the combined capabilities of the test and system. Labelling of subjects as fallers and non-fallers was performed using an objective and precise sensory organization test; it is an important novelty as this approach to subject labelling has never before been used in the design and evaluation of fall risk assessment systems. The findings show a true-positive ratio of 85% and true-negative ratio of 63% for classifying subjects as fallers or non-fallers using the introduced fast mobility test, which are noticeably better than those obtained for the long-established Timed Up and Go test.

An Android Malware Detection System Based on Feature Fusion

2018 ◽  
Vol 27 (6) ◽  
pp. 1206-1213 ◽  
Author(s):  
Jian Li ◽  
Zheng Wang ◽  
Tao Wang ◽  
Jinghao Tang ◽  
Yuguang Yang ◽  
...  
Keyword(s):  
Feature Fusion ◽  
Detection System ◽  
Malware Detection ◽  
Android Malware ◽  
Android Malware Detection

scholarly journals Coupling Uncertainties with Accuracy Assessment in Object-based Slum Detections, Case Study: Jakarta, Indonesia

2017 ◽  
Author(s):  
Jati Pratomo ◽  
Monika Kuffer ◽  
Javier Martinez ◽  
Divyani Kohli
Keyword(s):  
Land Tenure ◽  
Classification Accuracy ◽  
Accuracy Assessment ◽  
False Negative ◽  
National Policy ◽  
True Positive ◽  
True Negative ◽  
Object Based ◽  
The Impact

Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our research analyses the impact of uncertainties in measuring the accuracy of OBIA-based slum detection. We selected Jakarta as our case study area, because of a national policy of slum eradication, which is causing rapid changes in slum areas. Our research comprises of four parts: slum conceptualization, ruleset development, implementation, and accuracy and uncertainty measurements. Existential and extensional uncertainty arise when producing reference data. The comparison of a manual expert delineations of slums with OBIA slum classification results into four combinations: True Positive, False Positive, True Negative and False Negative. However, the higher the True Positive (which lead to a better accuracy), the lower the certainty of the results. This demonstrates the impact of extensional uncertainties. Our study also demonstrates the role of non-observable indicators (i.e., land tenure), to assist slum detection, particularly in areas where uncertainties exist. In conclusion, uncertainties are increasing when aiming to achieve a higher classification accuracy by matching manual delineation and OBIA classification.

scholarly journals Comparison Study Between Local TSH IRMA Kit (CRRT) and Imported TSH IRMA Kit (Riakey, Korea)

2019 ◽  
Vol 4 (2) ◽  
pp. 77
Author(s):  
Gina Mondrida ◽  
Triningsih Triningsih ◽  
Kristina Dwi Purwanti ◽  
Sutari Sutari ◽  
Sri Setyowati ◽  
...  
Keyword(s):  
False Negative ◽  
Thyroid Stimulating Hormone ◽  
The Body ◽  
True Positive ◽  
Comparison Study ◽  
Complex Matrix ◽  
Normal Range ◽  
True Negative ◽  
Immunoassay Technique ◽  
Tsh Levels

<p><em>Thyroid Stimulating Hormone</em> (TSH) is one of hormones that our body need for growth of brains, bones and other tissues and regulate the metabolism in the body. Normal range of TSH for adult is from 0.3 to 5.5 µIU/ml, whereas for baby ranged from 3 to 18 µIU/ml. An Immunoradiometricassay (IRMA) is one of immunoassay technique using radionuclide as the tracer to detect low quantity of analyte. This technique is suitable for determine TSH levels in human blood serum which has complex matrix and various concentration. The Center for Radioisotope and Radiopharmaceutical Technology (CRRT)-BATAN has developed a reagent of TSH IRMA kit. The aim of this research is to compare between local TSH IRMA kit (CRRT-BATAN) and imported TSH IRMA kit (Riakey, Korea) toward 110 adult samples obtained from PTKMR - BATAN. The results showed 97 samples as true negative, 5 samples as true positive, 1 sample as false negative and 7 samples false positive. The comparison study gave diagnostic sensitivity as much as 83.33 %, diagnostic spesificity as much as 93.27 % and accuracy as much as 92.72 %.</p>

Abstract P387: Race and Sex Differences Exist in the Volumes of Visceral Adipose Tissue Associated With Prevalent Hypertension in Middle Age Adults

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Christina M Shay ◽  
Prasenjeet N Motghare ◽  
David R Jacobs ◽  
Cora E Lewis ◽  
J. Greg Terry ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Adipose Tissue ◽  
Black Women ◽  
White Women ◽  
Middle Age ◽  
White Men ◽  
True Positive ◽  
True Negative ◽  
Cut Points ◽  
Visceral Adipose

Background: Higher visceral adipose tissue (VAT) volume is associated with greater risk for hypertension (HTN). Although VAT volume and prevalence of HTN vary by sex and race, the differences in VAT volumes associated with identification of individuals with prevalent HTN across these groups is unclear. Objective: To determine VAT volume cut points that maximize true positive, true negative and optimal identification of prevalent HTN and to compare the cut points across sex and race groups. Methods: Data were examined from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a multi-center longitudinal study of the development of cardiovascular risk in black and white men and women ages 18-30 years at baseline. In 2010-11, the Year 25 exam was performed (43-55 years) and VAT volume (cm3) was quantified by computed tomography based on two 5 mm contiguous slices at the level of the 4th-5th lumbar vertebra (n=3,153). HTN was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg and/or anti-hypertension medication use. Receiver operating characteristic (ROC) curve analysis was used to identify VAT volume cut points associated with true positive, true negative and optimal identification of prevalent HTN. Results: Year 25 prevalence of HTN ranged from 18.2% (white women) to 49.4% (black women); mean VAT volume ranged from 113.5 cm3 (white women) to 172.1 cm3 (white men). White males exhibited the highest VAT volumes (22-36% higher) and black women exhibited the lowest VAT volumes (3-50% lower) associated with true positive, true negative and optimal identification of HTN compared to other race/sex groups (Table 1). VAT volumes associated with HTN among black participants were generally lower than those exhibited for whites. Conclusions: Although the utility of VAT alone to identify HTN cases is modest - likely a result of unaccounted HTN confounders - these findings display the distinct race- and sex-specific differences in VAT volumes associated with prevalent HTN in middle age adults.

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