64,515 research outputs found
Security challenges of small cell as a service in virtualized mobile edge computing environments
Research on next-generation 5G wireless networks is currently attracting a lot of attention in both academia and industry. While 5G development and standardization activities are still at their early stage, it is widely acknowledged that 5G systems are going to extensively rely on dense small cell deployments, which would exploit infrastructure and network functions virtualization (NFV), and push the network intelligence towards network edges by embracing the concept of mobile edge computing (MEC). As security will be a fundamental enabling factor of small cell as a service (SCaaS) in 5G networks, we present the most prominent threats and vulnerabilities against a broad range of targets. As far as the related work is concerned, to the best of our knowledge, this paper is the first to investigate security challenges at the intersection of SCaaS, NFV, and MEC. It is also the first paper that proposes a set of criteria to facilitate a clear and effective taxonomy of security challenges of main elements of 5G networks. Our analysis can serve as a staring point towards the development of appropriate 5G security solutions. These will have crucial effect on legal and regulatory frameworks as well as on decisions of businesses, governments, and end-users
A Polynomial Time Algorithm for Spatio-Temporal Security Games
An ever-important issue is protecting infrastructure and other valuable
targets from a range of threats from vandalism to theft to piracy to terrorism.
The "defender" can rarely afford the needed resources for a 100% protection.
Thus, the key question is, how to provide the best protection using the limited
available resources. We study a practically important class of security games
that is played out in space and time, with targets and "patrols" moving on a
real line. A central open question here is whether the Nash equilibrium (i.e.,
the minimax strategy of the defender) can be computed in polynomial time. We
resolve this question in the affirmative. Our algorithm runs in time polynomial
in the input size, and only polylogarithmic in the number of possible patrol
locations (M). Further, we provide a continuous extension in which patrol
locations can take arbitrary real values. Prior work obtained polynomial-time
algorithms only under a substantial assumption, e.g., a constant number of
rounds. Further, all these algorithms have running times polynomial in M, which
can be very large
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
A Taxonomy of Self-configuring Service Discovery Systems
We analyze the fundamental concepts and issues in service
discovery. This analysis places service discovery in the context of distributed
systems by describing service discovery as a third generation
naming system. We also describe the essential architectures and the
functionalities in service discovery. We then proceed to show how service
discovery fits into a system, by characterizing operational aspects.
Subsequently, we describe how existing state of the art performs service
discovery, in relation to the operational aspects and functionalities, and
identify areas for improvement
An Empirical Study on Android for Saving Non-shared Data on Public Storage
With millions of apps that can be downloaded from official or third-party
market, Android has become one of the most popular mobile platforms today.
These apps help people in all kinds of ways and thus have access to lots of
user's data that in general fall into three categories: sensitive data, data to
be shared with other apps, and non-sensitive data not to be shared with others.
For the first and second type of data, Android has provided very good storage
models: an app's private sensitive data are saved to its private folder that
can only be access by the app itself, and the data to be shared are saved to
public storage (either the external SD card or the emulated SD card area on
internal FLASH memory). But for the last type, i.e., an app's non-sensitive and
non-shared data, there is a big problem in Android's current storage model
which essentially encourages an app to save its non-sensitive data to shared
public storage that can be accessed by other apps. At first glance, it seems no
problem to do so, as those data are non-sensitive after all, but it implicitly
assumes that app developers could correctly identify all sensitive data and
prevent all possible information leakage from private-but-non-sensitive data.
In this paper, we will demonstrate that this is an invalid assumption with a
thorough survey on information leaks of those apps that had followed Android's
recommended storage model for non-sensitive data. Our studies showed that
highly sensitive information from billions of users can be easily hacked by
exploiting the mentioned problematic storage model. Although our empirical
studies are based on a limited set of apps, the identified problems are never
isolated or accidental bugs of those apps being investigated. On the contrary,
the problem is rooted from the vulnerable storage model recommended by Android.
To mitigate the threat, we also propose a defense framework
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