In recent past years, Deep Learning presented an excellent performance in different areas like image recognition, pattern matching, and even in cybersecurity. The Deep Learning has numerous advantages including fast solving complex problems, huge automation, maximum application of unstructured data, ability to give high quality of results, reduction of high costs, no need for data labeling, and identification of complex interactions, but it also has limitations like opaqueness, computationally intensive, need for abundant data, and more complex algorithms. In our daily life, we used many applications that use Deep Learning models to make decisions based on predictions, and if Deep Learning models became the cause of misprediction due to internal/external malicious effects, it may create difficulties in our real life. Furthermore, the Deep Learning training models often have sensitive information of the users and those models should not be vulnerable and expose security and privacy. The algorithms of Deep Learning and machine learning are still vulnerable to different types of security threats and risks. Therefore, it is necessary to call the attention of the industry in respect of security threats and related countermeasures techniques for Deep Learning, which motivated the authors to perform a comprehensive survey of Deep Learning security and privacy security challenges and countermeasures in this paper. We also discussed the open challenges and current issues.

With the advent of cloud computing and wireless sensor networks, the number of cyberattacks has rapidly increased. Therefore, the proportionate security of networks has become a challenge for organizations. Information security advisors of organizations face difficult and complex decisions in the evaluation and selection of information security controls that permit the defense of their resources and assets. Information security controls must be selected based on an appropriate level of security. However, their selection needs intensive investigation regarding vulnerabilities, risks, and threats prevailing in the organization as well as consideration of the implementation, mitigation, and budgetary constraints of the organization. The goal of this paper was to improve the information security control analysis method by proposing a formalized approach, i.e., fuzzy Analytical Hierarchy Process (AHP). This approach was used to prioritize and select the most relevant set of information security controls to satisfy the information security requirements of an organization. We argue that the prioritization of the information security controls using fuzzy AHP leads to an efficient and cost-effective assessment and evaluation of information security controls for an organization in order to select the most appropriate ones. The proposed formalized approach and prioritization processes are based on International Organization for Standardization and the International Electrotechnical Commission (ISO/IEC) 27001:2013. But in practice, organizations may apply this approach to any information security baseline manual.

The progress of membrane technology with the development of membranes with controlled parameters led to porous membranes. These membranes can be formed using different methods and have numerous applications in science and technology. Anodization of aluminum in this aspect is an electro-synthetic process that changes the surface of the metal through oxidation to deliver an anodic oxide layer. This process results in a self-coordinated, exceptional cluster of round and hollow formed pores with controllable pore widths, periodicity, and thickness. Categorization in barrier type and porous type films, and different methods for the preparation of membranes, have been discussed. After the initial introduction, the paper proceeds with a brief overview of anodizing process. That engages anodic aluminum oxide (AAO) layers to be used as formats in various nanotechnology applications without the necessity for expensive lithographical systems. This review article surveys the current status of the investigation on AAO membranes. A comprehensive analysis is performed on AAO membranes in applications; filtration, sensors, drug delivery, template-assisted growth of various nanostructures. Their multiple usages in nanotechnology have also been discussed to gather nanomaterials and devices or unite them into specific applications, such as nano-electronic gadgets, channel layers, and clinical platforms tissue designing. From this review, the fact that the specified enhancement of properties of AAO can be done by varying geometric parameters of AAO has been highlighted. No review paper focused on a detailed discussion of multiple applications of AAO with prospects and challenges. Also, it is a challenge for the research community to compare results reported in the literature. This paper provides tables for easy comparison of reported applications with membrane parameters. This review paper represents the formation, properties, applications with objective consideration of the prospects and challenges of AAO applications. The prospects may appeal to researchers to promote the development of unique membranes with functionalization and controlled geometric parameters and check the feasibility of the AAO membranes in nanotechnology and devices.

Cloud Technology is a most challenging modern area in the field of modern technologies in which assets (e.g., CPU and capacity) can be rented and discharged by the clients through internet on-demand basis. The cloud computing has been giving virtual computing services to a little, medium and extensive industries, and services, for example, infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Cloud computing has a great combination with the agile software development as a research area. Many researchers worked in Agile Cloud field. The software industries are using the agile methodology for efficient software development need some platform to get quick feedback from the client. Therefore, the agile-cloud is a great combination for it but due to security reasons that directly influence the less adoption of cloud in software industries. This paper reports the survey results of software industries. The total of seven IT industries and many professionals was involved in this paper. However, this paper also contributes and reveals how existing issues can affect agile-cloud adoption for efficient software development. Furthermore, we do not find any type of survey conducted in Pakistan's software industries-related to cloud-agile adoption.

Cloud Computing is one of the most important trend and newest area in the field of information technology in which resources (e.g. CPU and storage) can be leased and released by customers through the Internet in an on-demand basis. The adoption of Cloud Computing in Education and developing countries is real an opportunity. Although Cloud computing has gained popularity in Pakistan especially in education and industry, but its impact in Pakistan is still unexplored especially in Higher Education Department. Already published work investigated in respect of factors influencing on adoption of cloud computing but very few investigated said analysis in developing countries. The Higher Education Institutions (HEIs) of Punjab, Pakistan are still not focused to discover cloud adoption factors. In this study, we prepared cloud adoption model for Higher Education Institutions (HEIs) of Punjab, a survey was carried out from 900 students all over Punjab. The survey was designed based upon literature and after discussion and opinions of academicians. In this paper, 34 hypothesis were developed that affect the cloud computing adoption in HEIs and tested by using powerful statistical analysis tools i.e. SPSS and SmartPLS. Statistical findings shows that 84.44% of students voted in the favor of cloud computing adoption in their colleges, while 99% supported Reduce Cost as most important factor in cloud adoption.