The transformation of vast amount of information through the network channels appeared widely from one site to another and these information may be disclosed to the third party or the attackers. Thus, the protection process of transformed information is a complex process that can be established through the Intrusion Detection System (IDS). Concealment and unity of information are the most important issues achieved through the intrusion detection system. The process of intrusion detection can be used with wireless or wired networks via making use of hardware or software techniques. Consequently, this caused to have lots of new techniques for IDS in various environments and different levels of network. Unfortunately, most of these techniques do not implemented together for increasing the security of the network. This leaded us to provide a review of the recent papers including a general view of intrusion detection in various environments through the networking and using various techniques. As a result, the most important intend for this paper is to embrace the most new progressions in this region. This may help the researchers to have a general knowledge on different techniques for protection through IDS and various types of intrusion and its detection techniques.

In today's world, the swift increase of utilizing mobile services and simultaneously discovering of the cloud computing services, made the Mobile Cloud Computing (MCC) selected as a wide spread technology among mobile users. Thus, the MCC incorporates the cloud computing with mobile services for achieving facilities in daily using mobile. The capability of mobile devices is limited of computation context, memory capacity, storage ability, and energy. Thus, relying on cloud computing can handle these troubles in the mobile surroundings. Cloud Computing gives computing easiness and capacity such provides availability of services from anyplace through the Internet without putting resources into new foundation, preparing, or application authorizing. Additionally, Cloud Computing is an approach to expand the limitations or increasing the abilities dynamically. The primary favourable position of Cloud Computing is that clients just use what they require and pay for what they truly utilize. Mobile cloud computing is a form for various services, where a mobile gadget is able to utilize the cloud for data saving, seeking, information mining, and multimedia preparing. Cloud computing innovation is also causes many new complications in side of safety and gets to direct when users store significant information with cloud servers. As the clients never again have physical ownership of the outsourced information, makes the information trustworthiness, security, and authenticity insurance in Cloud Computing is extremely difficult and conceivably troublesome undertaking. In MCC environments, it is hard to find a paper embracing most of the concepts and issues such as: architecture, computational offloading, challenges, security issues, authentications and so on. In this paper we discuss these concepts with presenting a review of the most recent papers in the domain of MCC.

Segmentation of optical disk (OD) and blood vessel is one of the significant steps in automatic diabetic retinopathy (DR) detecting. In this paper, a new technique is presented for OD segmentation that depends on the histogram template matching algorithm and OD size. In addition, Kirsch method is used for Blood Vessel (BV) segmentation which is one of the popular methods in the edge detection and image processing technique. The template matching algorithm is used for finding the center of the OD. In this step, the histogram of each RGB (Red, Green, and Blue) planes are founded and then the cross-correlation is founded between the template and the original image, OD location is the point with maximum cross-correlation between them. The OD size varies according to the camera field of sight and the resolution of the original image. The rectangle size of OD is not the same for various databases, the estimated size for DRIVE, STARE, DIARTDB0, and DIARTDB1 are 80×80, 140×140, 190×190, and 190×190 respectively. After finding the OD center and rectangle size of OD, a binary mask is created with Region of Interest (ROI) for segmenting the OD. The DIARTDB0 is used to evaluate the proposed technique, the result is robust and vital with an accuracy of 96%.