Vasile Claudiu Perta

Mobile offloading in the wild: Findings and lessons learned through a real-life experiment with a new cloud-aware system

Mobile-cloud offloading mechanisms delegate heavy mobile computation to the cloud. In real life use, the energy tradeoff of computing the task locally or sending the input data and the code of the task to the cloud is often negative, especially with popular communication intensive jobs like social-networking, gaming, and emailing. We design and build a working implementation of CDroid, a system that tightly couples the device OS to its cloud counterpart. The cloud-side handles data traffic through the device efficiently and, at the same time, caches code and data optimally for possible future offloading. In our system, when offloading decision takes place, input and code are likely to be already on the cloud. CDroid makes mobile cloud offloading more practical enabling offloading of lightweight jobs and communication intensive apps. Our experiments with real users in everyday life show excellent results in terms of energy savings and user experience.

Clone2Clone (C2C): Peer-to-Peer Networking of Smartphones on the Cloud

In this work we introduce Clone2Clone (C2C), a distributed peer-to-peer platform for cloud clones of smartphones. C2C shows dramatic performance improvement that is made possible by offloading communication between smartphones on the cloud. Along the way toward C2C, we study the performance of device-clones hosted in various virtualization environments in both private (local servers) and public (Amazon EC2) clouds. We build the first Amazon Customized Image (AMI) for AndroidOS—a key tool to get reliable performance measures of mobile cloud systems—and show how it boosts up performance of Android images on the Amazon cloud service. We then design, build, and implement C2C. Upon it we build CloneDoc, a secure real-time collaboration system for smartphone users. We measure the performance of CloneDoc by means of experiments on a testbed of 16 Android smartphones and clones hosted on both private and public cloud services. We show that C2C makes it possible to implement distributed execution of advanced peer-to-peer services in a network of mobile smartphones reducing 3 times the cellular data traffic and saving 99%, 80%, and 30% of the battery for respectively security checks, user status update and document editing.

CloneDoc: exploiting the cloud to leverage secure group collaboration mechanisms for smartphones

The limited battery of smartphones makes it hard for users to fully exploit their devices. Recent research considers offloading mobile computation to the cloud to improve efficiency and to extend battery life. We design Clone2Clone (C2C), a distributed p2p platform for software cloud clones of smartphones. Upon C2C we implement CloneDoc, a secure real-time collaboration system for smartphone users. We measure the performance of CloneDoc on a testbed of six Android smartphones and clones hosted on the Amazon cloud service and show that C2C based protocols can significantly improve battery-life compared to protocols that do not make use of C2C.

CDroid: towards a cloud-integrated mobile operating system

Current offloading mechanisms for mobile energyhungry apps consider the cloud as a separate remote support to the mobile devices. We take a different approach: We present CDroid, a system residing partially on the device and partially on a cloud software clone coupled with the device, and uses the cloud-side as just-another-resource of the real device. It enhances the user-experience by improving web navigation, compressing and caching web-pages, blocking unwanted ads, and protects user data by virus scanning apps on the cloud-side prior installation on the real-device. CDroid puts the first steps towards a hybrid cloud-integrated mobile system of the future.

A Glance through the VPN Looking Glass: IPv6 Leakage and DNS Hijacking in Commercial VPN Clients

Abstract Commercial Virtual Private Network (VPN) services have become a popular and convenient technology for users seeking privacy and anonymity. They have been applied to a wide range of use cases, with commercial providers often making bold claims regarding their ability to fulfil each of these needs, e.g., censorship circumvention, anonymity and protection from monitoring and tracking. However, as of yet, the claims made by these providers have not received a sufficiently detailed scrutiny. This paper thus investigates the claims of privacy and anonymity in commercial VPN services. We analyse 14 of the most popular ones, inspecting their internals and their infrastructures. Despite being a known issue, our experimental study reveals that the majority of VPN services suffer from IPv6 traffic leakage. The work is extended by developing more sophisticated DNS hijacking attacks that allow all traffic to be transparently captured.We conclude discussing a range of best practices and countermeasures that can address these vulnerabilities

Exploring HTTP Header Manipulation In-The-Wild

Headers are a critical part of HTTP, and it has been shown that they are increasingly subject to middlebox manipulation. Although this is well known, little is understood about the general regional and network trends that underpin these manipulations. In this paper, we collect data on thousands of networks to understand how they intercept HTTP headers in-the-wild. Our analysis reveals that 25% of measured ASes modify HTTP headers. Beyond this, we witness distinct trends among different regions and AS types; e.g., we observe high numbers of cache headers in poorly connected regions. Finally, we perform an in-depth analysis of the types of manipulations and how they differ across regions.

A first look at user activity on Tinder

Mobile dating apps have become a popular means to meet potential partners. Although several exist, one recent addition stands out amongst all others. Tinder presents its users with pictures of people geographically nearby, whom they can either like or dislike based on first impressions. If two users like each other, they are allowed to initiate a conversation via the chat feature. In this paper we use a set of curated profiles to explore the behaviour of men and women in Tinder. We reveal differences between the way men and women interact with the app, highlighting the strategies employed. Women attain large numbers of matches rapidly, whilst men only slowly accumulate matches. Most notably, our results indicate that a little effort in grooming profiles, especially for male users, goes a long way in attracting attention.

Exploiting Delay Patterns for User IPs Identification in Cellular Networks

A surprisingly high number of mobile carriers worldwide do not block unsolicited traffic from reaching their mobile devices from the open Internet or from within the cellular network. This exposes mobile users to a class of low-resource attacks that could compromise their privacy and security. In this work we describe a methodology that allows an adversary to identify a victim device in the cellular network by just sending messages to its user through one or more messaging apps available today on the mobile market. By leveraging network delays produced by mobile devices in different radio states and the timeliness of push notifications, we experimentally show how our methodology is able to quickly identify the target device within 20 messages in the worst case through measurements on a large mobile network.

A Needle in the Haystack - Delay Based User Identification in Cellular Networks

In this work, we discuss a technique for identifying users in cellular networks that exploits the effect that RRC state machine transitions have on the measured round-trip time of mobile devices. Our preliminary experiments performed in a controlled environment, show that it is possible to leverage popular real-time messaging apps, such as Facebook, WhatsApp and Viber, to trigger an observable delay pattern on a users device, and use it to identify the device.