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Mobile applications and devices have played a significant role in boosting global businesses that encompass various domains such as health, education, banking, and transportation. These tools have become indispensable for everyday activities, and its applications have been developing rapidly with diverse features and platforms. However, this has created new problems and security challenges. To ensure the quality and security of these applications, a rigorous and systematic testing using cloud-based environment is required. By employing systematic mapping study (SMS) method, this paper will examine the empirical studies that address the issues on cloud-based mobile application testing. This paper presents a total of 23 primary studies that investigate cloud based mobile application testing and the effect of Testing as a Service (TaaS). The majority of these studies (56.5%) contribute to literature with a number of framework proposals. A large proportion of the studies (60.9%) analyzed Android applications, and usually supported a single type of mobile app testing. Other than that, the majority of the studies (52.2%) have failed to investigate the outcomes of TaaS, despite a plethora of services that offers TaaS. The SMS method conducted in this paper has identified gaps in literature, which are: 1) there is a lack of general and scalable approaches to support the diverse types of mobile app testing for applications using various platforms, and 2) the lack of evaluation methods such as case study to validate the proposed approaches.  

Despite the popularity of 802.11 based networks, they suffer several types of DoS attack, launched by an attacker whose aim is to make an access point (AP) unavailable to legitimate users. One of the most common DoS attacks on 802.11 based networks is to deplete the resources of the AP. A serious situation like this can occur when the AP receives a burst of connection requests. This paper addresses this common DoS attack and proposes a lightweight puzzle, based on pattern-matching. Using a pattern-matching technique, this model adequately resists resource-depletion attacks in terms of both puzzle generation and solution verification. Using a sensible series of contextual comparisons, the outcomes were modelled by a simulator, and the security definition and proofs are verified, among other results.

With the popularity of Internet of Things (IoT) technology, the security of the IoT network has become an important issue. Traditional intrusion detection systems have their limitations when applied to the IoT network due to resource constraints and the complexity. This research focusses on the design, implementation and testing of an intrusion detection system which uses a hybrid placement strategy based on a multi-agent system, blockchain and deep learning algorithms. The system consists of the following modules: data collection, data management, analysis, and response. The National security lab–knowledge discovery and data mining NSL-KDD dataset is used to test the system. The results demonstrate the efficiency of deep learning algorithms when detecting attacks from the transport layer. The experiment indicates that deep learning algorithms are suitable for intrusion detection in IoT network environment.

Cloud Computing Security is a new era of computer technology and opens a new research area and creates a lot of opportunity of exploration. One of the new implementation in Cloud is Intrusion Detection System (IDS).There are problems with existing IDS approach in Cloud environment. Implementing traditional IDS need a lot of self-maintenance and did not scale with the customer security requirements. In addition, maintenance of traditional IDS in Cloud Computing system requires expertise and consumes more time where not each Cloud user has. A decentralized traditional IDS approach where being deployed in current Cloud Computing infrastructure will make the IDS management become complicated. Each user's IDS will not be the same in term of type and configurations and each user may have outdated signatures. Inter VM's communication also become a big concern when we implementing Cloud Computing system where communication between Clouds are not monitored and controlled by the traditional IDS. A specific IDS model for Cloud computing is required to solve these problems. In this paper, we develop a prototype of Cloud IDS inspired by Dendritic Cell mechanism. Experiment result proved that Cloud IDS was able to detect any attempt to attack the Cloud environment. The experiments show that the Cloud IDS model based on Dendritic Cell algorithm able to identify and detect novel threat that targeting Cloud environment.

Academic credentials hold great significance as they portray a person's educational qualifications, which have a substantial impact on their future achievements. Nevertheless, these certificates are often exposed to various security risks like unauthorized access, forgery, and tampering, as conventional access control mechanisms such as passwords or physical documents are inadequate to ensure their privacy and safety. This research presents a fresh approach to access control, employing the Hyperledger Fabric blockchain technology to secure academic certificates' privacy. The suggested access control protocol intends to guarantee that only authorized individuals have access to academic certificates, thus ensuring their privacy and safeguarding them from any unauthorized access. The methodology involved identifying stakeholders and determining their roles and required permissions. Students are granted full permissions, while other parties can only read and execute the certificates. The protocol is designed with ihe following two functions: locking and unlocking the certificate. When a student locks their certificate, it becomes unreadable to any other party, including the issuing university. The certificate can only be unlocked by the certificate owner, making it readable by authorized parties like potential employers or verification services. The study's results demonstrate that the proposed access control protocol is effective in protecting academic certificates' privacy while ensuring appropriate access control. The protocol allows students to lock and unlock their certificates, giving them complete control over their certificates' privacy. Only authorized parties can access the certificates, and their access is limited to reading and executing the certificates. The proposed protocol's performance was evaluated through performance evaluation, indicating that it has a high throughput rate and low latency. The protocol's effectiveness was tested through various use cases by varying the specifications of key parameters, and the results show that the protocol has high throughput and low latency at different transaction rates.

Academic certificates are integral to an individual's education and career prospects, yet conventional paper-based certificates pose challenges with their transport and vulnerability to forgery. In response to this predicament, institutions have taken measures to release e-certificates, though ensuring authenticity remains a pressing concern. Blockchain technology, recognised for its attributes of security, transparency, and decentralisation, presents a resolution to this problem and has garnered attention from various sectors. While blockchain-based academic certificate management systems have been proposed, current systems exhibit some security and privacy limitations. To address these issues, this research proposes a new Decentralised Control Verification Privacy-Centered (DCVPC) protocol based on Hyperledger Fabric blockchain for preserving the privacy of academic certificates. The proposed protocol aims to protect academic certificates' privacy by granting complete authority over all network nodes, creating channels for universities to have their private environment, and limiting access to the ledger. The protocol is highly secure, resistant to attacks, and allows improved interoperability and automation of the certificate verification process. A proof-of-concept was developed to demonstrate the protocol's functionality and performance. The proposed protocol presents a promising solution for enhancing security, transparency, and privacy of academic certificates. It guarantees that the certificate's rightful owner is correctly identified, and the issuer is widely recognised. This research makes a valuable contribution to the area of blockchain-based academic certificate management systems by introducing a new protocol that addresses the present security and privacy limitations.

Academic certificate authentication is crucial in safeguarding the rights and opportunities of individuals who have earned academic credentials. This authentication helps prevent fraud and forgery, ensuring that only those who have genuinely earned certificates can use them for education and career opportunities. With the increased use of online education and digital credentials in the digital age, the importance of academic certificate authentication has significantly grown. However, traditional techniques for authentication, such as QR code, barcode, and watermarking, have limitations regarding security and privacy. Therefore, proposing a privacy-centred protocol to enhance the security and authentication of academic certificates is vital to improve the trust and credibility of digital academic certificates, ensuring that individuals' rights and opportunities are protected. In this context, we adopted the Challenge Handshake Authentication (CHA) protocol to propose the Certificate Verification Privacy Control Protocol (CVPC). We implemented it using Python and Flask with a Postgres database and an MVT structure for the application. The results of the implementation demonstrate that the proposed protocol effectively preserves privacy during the academic certificate issuance and verification process. Additionally, we developed a proof of concept to evaluate the proposed protocol, demonstrating its functionality and performance. The PoC provided insights into the strengths and weaknesses of the proposed protocol and highlighted its potential to prevent forgery and unauthorised access to academic certificates. Overall, the proposed protocol has the potential to significantly enhance the security and authenticity of academic certificates, improving the overall trust and credibility of the academic credentialing system.

The term Cloud computing is not new anymore in computing technology. This form of computing technology previously considered only as marketing term, but today Cloud computing not only provides innovative improvements in resource utilisation but it also creates a new opportunities in data protection mechanisms where the advancement of intrusion detection technologies  are blooming rapidly. From the perspective of security, Cloud computing also introduces concerns about data protection and intrusion detection mechanism. This paper surveys, explores and informs researchers about the latest developed Cloud Intrusion Detection Systems by providing a comprehensive taxonomy and investigating possible solutions to detect intrusions in cloud computing systems. As a result, we provide a comprehensive review of Cloud Intrusion Detection System research, while highlighting the specific properties of Cloud Intrusion Detection System. We also present taxonomy on the key issues in Cloud Intrusion Detection System area and discuss the different approaches taken to solve the issues. We conclude the paper with a critical analysis of challenges that have not fully solved.

Mobile applications and devices have played a significant role in boosting global businesses that encompass various domains such as health, education, banking, and transportation. These tools have become indispensable for everyday activities, and its applications have been developing rapidly with diverse features and platforms. However, this has created new problems and security challenges. To ensure the quality and security of these applications, a rigorous and systematic testing using cloud-based environment is required. By employing systematic mapping study (SMS) method, this paper will examine the empirical studies that address the issues on cloud-based mobile application testing. This paper presents a total of 23 primary studies that investigate cloud based mobile application testing and the effect of Testing as a Service (TaaS). The majority of these studies (56.5%) contribute to literature with a number of framework proposals. A large proportion of the studies (60.9%) analyzed Android applications, and usually supported a single type of mobile app testing. Other than that, the majority of the studies (52.2%) have failed to investigate the outcomes of TaaS, despite a plethora of services that offers TaaS. The SMS method conducted in this paper has identified gaps in literature, which are: 1) there is a lack of general and scalable approaches to support the diverse types of mobile app testing for applications using various platforms, and 2) the lack of evaluation methods such as case study to validate the proposed approaches.

Purpose – Ambient service provisioning with the least human participation in a pervasive computing environment, which is composed of interconnected devices and sensors, raises several trust and security issues. Accurate measuring of the integrity of the nodes that are willing to interact in this intimate environment can boost the trust evolution process, particularly in the uncertainty state and initiation phase. The paper aims to discuss these issues. Design/methodology/approach – The paper presents a unified approach in calculating the trust value among the nodes by leveraging some trusted computing functionalities. The approach aggregates different trust metrics like context, recommendation, and history to compute the trust index of each party more accurately. The paper also describes several existing remote attestation techniques including the chosen attestation technique for the model. The paper simulated the behaviour of the model in different scenarios and evaluates its responsiveness when the trustworthiness among peer nodes can be attested. Findings – The results obtained from different simulated scenarios demonstrate the usefulness of the proposed model. It is shown that trust evaluation process in the proposed model is very granular and also can be fine-tuned according to the application and context. The model strength in solving the uncertain situations and assigning appropriate initial trust values is shown, as well. Finally, the paper describes the future research plan to evaluate the accuracy of the model. Originality/value – The novel idea of applying remote attestation in trust determination may open up new avenues of research in the study of trust management and trust models.