Cloud Computing on Smartphone

Cloud computing is the most recent technology for data storage & access. Cloud computing includes specific space on the server, the data can be accessed from or stored on the cloud. Cloud computing results into the high speed data accessed capability. Now a days, Every organization have their own cloud where the data is stored related to their work and whenever required it is accessed. Cloud computing is the platform as a service, key players in this sector is Google, Amazon and Microsoft. Smartphone’s and tablets have another growing market so these two technologies combined to form the new concept that is the Smartphone application will access the cloud. The platform evaluated which are suitable for the Smartphone devices is Amazon Web Services. These services allow features like Compute, Database & Storage. Keywords—cloud computing, Smartphones,Android,Amazon

Device-Based Isolation for Securing Cryptographic Keys

In this work, we describe an eective device-based isolation approach for achieving data security. Device-based isolation leverages the proliferation of personal computing devices to provide strong run-time guarantees for the condentiality of secrets. To demonstrate our isolation approach, we show its use in protecting the secrecy of highly sensitive data that is crucial to security operations, such as cryptographic keys used for decrypting ciphertext or signing digital signatures. Private key is usually encrypted when not used, however, when being used, the plaintext key is loaded into the memory of the host for access. In our threat model, the host may be compromised by attackers, and thus the condentiality of the host memory cannot be preserved. We present a novel and practical solution and its prototype called DataGuard to protect the secrecy of the highly sensitive data through the storage isolation and secure tunneling enabled by a mobile handheld device. DataGuard can be deployed for the key protection of individuals or organizations

Dual channel-based network traffic authentication

In a local network or the Internet in general, data that is transmitted between two computers (also known as network traffic or simply, traffic) in that network is usually classified as being of a malicious or of a benign nature by a traffic authentication system employing databases of previously observed malicious or benign traffic signatures, i.e., blacklists or whitelists, respectively. These lists typically consist of either the destinations (i.e., IP addresses or domain names) to which traffic is being sent or the statistical properties of the traffic, e.g., packet size, rate of connection establishment, etc. The drawback with the list-based approach is its inability to offer a fully comprehensive solution since the population of the list is likely to go on indefinitely. This implies that at any given time, there is a likelihood of some traffic signatures not being present in the list, leading to false classification of traffic. From a security standpoint, whitelists are a safer bet than blacklists since their underlying philosophy is to block anything that is unknown hence in the worst case, are likely to result in high false rejects with no false accepts. On the other hand, blacklists block only what is known and therefore are likely to result in high false accepts since unknown malicious traffic will be accepted, e.g., in the case of zero-day attacks (i.e., new attacks whose signatures have not yet been analyzed by the security community). Despite this knowledge, the most commonly used traffic authentication solutions, e.g., antivirus or antimalware solutions, have predominantly employed blacklists rather than whitelists in their solutions. This can perhaps be attributed to the fact that the population of a blacklist typically requires less user involvement than that of a whitelist. For instance, malicious traffic signatures (i.e., behavior or destinations) are usually the same across a population of users; hence, by observing malicious activity from a few users, a global blacklist that is applicable to all users can be created. Whitelist generation, on the other hand, tends to be more user-specific as what may be considered acceptable or benign traffic to one user may not be considered the same to a different user. As a result, users are likely to find whitelist-based solutions that require their participation to be both cumbersome and inconveniencing. This dissertation offers a whitelist-based traffic authentication solution that reduces the active participation of users in whitelist population. By relying on activity that users regularly engage in while interacting with their computers (i.e., typing), we are able to identify legitimate destinations to which users direct their traffic and use these to populate the whitelist, without requiring the users to deviate from their normal behavior. Our solution requires users to type the destinations of their outgoing traffic requests only once, after which any subsequent requests to that destination are authenticated without the need for them to be typed again. Empirical results from testing our solution in a real time traffic analysis scenario showed that relatively low false reject rates for legitimate traffic with no false accepts for illegitimate traffic are achievable. Additionally, an investigation into the level of inconvenience that the typing requirement imposes on the users revealed that, since users are likely to engage in this (typing) activity during the course of utilizing their computer\u27s resources, this requirement did not pose a significant deterrent to them from using the system

An Approach to QoS-based Task Distribution in Edge Computing Networks for IoT Applications

abstract: Internet of Things (IoT) is emerging as part of the infrastructures for advancing a large variety of applications involving connections of many intelligent devices, leading to smart communities. Due to the severe limitation of the computing resources of IoT devices, it is common to offload tasks of various applications requiring substantial computing resources to computing systems with sufficient computing resources, such as servers, cloud systems, and/or data centers for processing. However, this offloading method suffers from both high latency and network congestion in the IoT infrastructures. Recently edge computing has emerged to reduce the negative impacts of tasks offloading to remote computing systems. As edge computing is in close proximity to IoT devices, it can reduce the latency of task offloading and reduce network congestion. Yet, edge computing has its drawbacks, such as the limited computing resources of some edge computing devices and the unbalanced loads among these devices. In order to effectively explore the potential of edge computing to support IoT applications, it is necessary to have efficient task management and load balancing in edge computing networks. In this dissertation research, an approach is presented to periodically distributing tasks within the edge computing network while satisfying the quality-of-service (QoS) requirements of tasks. The QoS requirements include task completion deadline and security requirement. The approach aims to maximize the number of tasks that can be accommodated in the edge computing network, with consideration of tasks’ priorities. The goal is achieved through the joint optimization of the computing resource allocation and network bandwidth provisioning. Evaluation results show the improvement of the approach in increasing the number of tasks that can be accommodated in the edge computing network and the efficiency in resource utilization.Dissertation/ThesisDoctoral Dissertation Computer Engineering 201

Enhancing Web Browsing Security

Web browsing has become an integral part of our lives, and we use browsers to perform many important activities almost everyday and everywhere. However, due to the vulnerabilities in Web browsers and Web applications and also due to Web users\u27 lack of security knowledge, browser-based attacks are rampant over the Internet and have caused substantial damage to both Web users and service providers. Enhancing Web browsing security is therefore of great need and importance.;This dissertation concentrates on enhancing the Web browsing security through exploring and experimenting with new approaches and software systems. Specifically, we have systematically studied four challenging Web browsing security problems: HTTP cookie management, phishing, insecure JavaScript practices, and browsing on untrusted public computers. We have proposed new approaches to address these problems, and built unique systems to validate our approaches.;To manage HTTP cookies, we have proposed an approach to automatically validate the usefulness of HTTP cookies at the client-side on behalf of users. By automatically removing useless cookies, our approach helps a user to strike an appropriate balance between maximizing usability and minimizing security risks. to protect against phishing attacks, we have proposed an approach to transparently feed a relatively large number of bogus credentials into a suspected phishing site. Using those bogus credentials, our approach conceals victims\u27 real credentials and enables a legitimate website to identify stolen credentials in a timely manner. to identify insecure JavaScript practices, we have proposed an execution-based measurement approach and performed a large-scale measurement study. Our work sheds light on the insecure JavaScript practices and especially reveals the severity and nature of insecure JavaScript inclusion and dynamic generation practices on the Web. to achieve secure and convenient Web browsing on untrusted public computers, we have proposed a simple approach that enables an extended browser on a mobile device and a regular browser on a public computer to collaboratively support a Web session. A user can securely perform sensitive interactions on the mobile device and conveniently perform other browsing interactions on the public computer