DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

This project sought to fabricate a flexible gas sensor based on a short functionalized multi-walled carbon nanotubes (f-MWCNTs) network for nitrogen dioxide gas detection. The network was prepared by filtration from the suspension (FFS) method and modified by coating with a layer of polypyrrole conductive polymer (PPy) prepared by the oxidative chemical polymerization to improve the properties of the network. The structural, optical, and morphological properties of the f-MWCNTs and f-MWCNTs/PPy network were studied using X-ray diffraction (XRD), Fourie-transform infrared (FTIR), with an AFM (atomic force microscopy). XRD proved that the structure of f-MWCNTs is unaffected by the synthesis procedure. The FTIR spectra verified the existence o

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

Surveillance cameras are video cameras used for the purpose of observing an area. They are often connected to a recording device or IP network, and may be watched by a security guard or law enforcement officer. In case of location have less percentage of movement (like home courtyard during night); then we need to check whole recorded video to show where and when that motion occur which are wasting in time. So this paper aims at processing the real time video captured by a Webcam to detect motion in the Scene using MATLAB 2012a, with keeping in mind that camera still recorded which means real time detection. The results show accuracy and efficiency in detecting motion

Medium Access Control (MAC) spoofing attacks relate to an attacker altering the manufacturer assigned MAC address to any other value. MAC spoofing attacks in Wireless Fidelity (WiFi) network are simple because of the ease of access to the tools of the MAC fraud on the Internet like MAC Makeup, and in addition to that the MAC address can be changed manually without software. MAC spoofing attacks are considered one of the most intensive attacks in the WiFi network; as result for that, many MAC spoofing detection systems were built, each of which comes with its strength and weak points. This paper logically identifies and recognizes the weak points
and masquerading paths that penetrate the up-to-date existing detection systems. Then the

Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

Sequence covering array (SCA) generation is an active research area in recent years. Unlike the sequence-less covering arrays (CA), the order of sequence varies in the test case generation process. This paper reviews the state-of-the-art of the SCA strategies, earlier works reported that finding a minimal size of a test suite is considered as an NP-Hard problem. In addition, most of the existing strategies for SCA generation have a high order of complexity due to the generation of all combinatorial interactions by adopting one-test-at-a-time fashion. Reducing the complexity by adopting one-parameter- at-a-time for SCA generation is a challenging process. In addition, this reduction facilitates the supporting for a higher strength of

The goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through  finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy