Security and privacy challenges in mobile cloud computing

https://people.cs.vt.edu/~irchen/ps/Mitchell-comcom14a.pdf

Review: A survey of intrusion detection in wireless network applications

The scale of Internet-connected systems has increased considerably, and these systems are being exposed to cyberattacks more than ever. The complexity and dynamics of cyberattacks require protecting mechanisms to be responsive, adaptive, and scalable. Machine learning, or more specifically deep reinforcement learning (DRL), methods have been proposed widely to address these issues. By incorporating deep learning into traditional RL, DRL is highly capable of solving complex, dynamic, and especially high-dimensional cyber defense problems. This article presents a survey of DRL approaches developed for cyber security. We touch on different vital aspects, including DRL-based security methods for cyber-physical systems, autonomous intrusion detection techniques, and multiagent DRL-based game theory simulations for defense strategies against cyberattacks. Extensive discussions and future research directions on DRL-based cyber security are also given. We expect that this comprehensive review provides the foundations for and facilitates future studies on exploring the potential of emerging DRL to cope with increasingly complex cyber security problems.

Deep Reinforcement Learning for Cyber Security.

On cloud security requirements, threats, vulnerabilities and countermeasures: A survey

Data mining and machine learning methods for sustainable smart cities traffic classification: a survey

A machine learning based intrusion detection scheme for data fusion in mobile clouds involving heterogeneous client networks

Wireless Body Area Networks (WBANs) have gained a lot of research attention in recent years since they offer tremendous benefits for remote health monitoring and continuous, real-time patient care. However, as with any wireless communication, data security in WBANs is a challenging design issue. Since such networks consist of small sensors placed on the human body, they impose resource and computational restrictions, thereby making the use of sophisticated and advanced encryption algorithms infeasible. This calls for the design of algorithms with a robust key generation / management scheme, which are reasonably resource optimal. This paper presents a security suite for WBANs, comprised of IAMKeys, an independent and adaptive key management scheme for improving the security of WBANs, and KEMESIS, a key management scheme for security in inter-sensor communication. The novelty of these schemes lies in the use of a randomly generated key for encrypting each data frame that is generated independently at both the sender and the receiver, eliminating the need for any key exchange. The simplicity of the encryption scheme, combined with the adaptability in key management makes the schemes simple, yet secure. The proposed algorithms are validated by performance analysis.

A security suite for wireless body area networks

Wireless Body Area Networks (WBANs) have gained a lot of research attention in recent years since theyoffer tremendous benefits for remote health monitoring and continuous, real-time patient care. However, as with any wireless communication, data security in WBANs is a challenging design issue. Since such networks consist of small sensors placed on the human body, they impose resource and computational restrictions, thereby making the use of sophisticated and advanced encryption algorithms infeasible. This calls for the design of algorithms with a robust key generation / management scheme, which are reasonably resource optimal. This paper presents a security suite for WBANs, comprised of IAMKeys, an independent and adaptive key management scheme for improving the security of WBANs, and KEMESIS, a key management scheme for security in inter-sensor communication. The novelty of these schemes lies in the use of a randomly generated key for encrypting each data frame that is generated independently at both the sender and the receiver, eliminating the need for any key exchange. The simplicity of the encryption scheme, combined with the adaptability in key management makes the schemes simple, yet secure. The proposed algorithms are validated by performance analysis.

/pdf/a-security-suite-for-wireless-body-area-networks-4vlt2aq3tp.pdf

With the development of the World Wide Web (WWW) and virtualization technologies, cloud computing has started to play a key role in the new computation era. Cloud computing can be used to serve a wide range of applications, from personal to organizational, by means of various infrastructure, software, and platform services. However, the ease of access from terminal devices to powerful processing units and information-rich databases makes the cloud susceptible to a variety of different attacks. The widespread use of cloud computing brings with it a hoard of security, privacy and integrity issues. In this paper, we propose an innovative authentication scheme for mobile cloud computing, MDA. The proposed scheme only uses existing hardware and platforms to prevent most of the potential attacks during the authentication process between a mobile device and the cloud. Technically, the encrypted hashed message (i.e. message digest) is employed by MDA to achieve secure authentication. The performance of MDA is evaluated via protocol simulation and security analysis.

Message digest as authentication entity for mobile cloud computing

The emerging area of mobile cloud computing will influence the future of varied applications, such as electronic commerce and health informatics. It is expected to rise in popularity over other models in cloud computing. This is facilitated by its simplicity, accessibility and ease of use. With mobile cloud computing, resource-constrained mobile devices could capitalize on the computation/storage resources of cloud servers via communication networks. Despite the advantage of this innovative computing model, mobile devices in mobile cloud computing are open to more security risks because they often have to access cloud servers through untrusted networks from different locations. Therefore, security is a critical problem to be tackled in mobile cloud computing. One of the most important aspects of mobile cloud computing security is to establish authenticated communication sessions between mobile devices and cloud servers. In this paper, we present a novel authentication scheme, Message Digest-based Authentication (MDA). Technically, MDA strategically incorporates hashing, in addition to traditional user ID and passwords, to achieve mutual authentication. The effectiveness of MDA is validated with Scyther, a widely-used security protocol analyzer. Our experimental results indicate that MDA is capable of withstanding a variety of different security attacks, such as man-in-the-middle, replay attacks, etc.

/pdf/mda-message-digest-based-authentication-for-mobile-cloud-2beg1kphvc.pdf

Saurabh Dey

Papers

A machine learning based intrusion detection scheme for data fusion in mobile clouds involving heterogeneous client networks

A security suite for wireless body area networks

A security suite for wireless body area networks

Message digest as authentication entity for mobile cloud computing

MDA: message digest-based authentication for mobile cloud computing