A fruitful direction for future data mining research will be the development of techniques that incorporate privacy concerns. Specifically, we address the following question. Since the primary task in data mining is the development of models about aggregated data, can we develop accurate models without access to precise information in individual data records? We consider the concrete case of building a decision-tree classifier from training data in which the values of individual records have been perturbed. The resulting data records look very different from the original records and the distribution of data values is also very different from the original distribution. While it is not possible to accurately estimate original values in individual data records, we propose a novel reconstruction procedure to accurately estimate the distribution of original data values. By using these reconstructed distributions, we are able to build classifiers whose accuracy is comparable to the accuracy of classifiers built with the original data.

Privacy-preserving data mining

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

A Survey on Mobile Edge Computing: The Communication Perspective

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

In this paper we address the issue of privacy preserving data mining. Specifically, we consider a scenario in which two parties owning confidential databases wish to run a data mining algorithm on the union of their databases, without revealing any unnecessary information. Our work is motivated by the need both to protect privileged information and to enable its use for research or other purposes.

The above problem is a specific example of secure multi-party computation and, as such, can be solved using known generic protocols. However, data mining algorithms are typically complex and, furthermore, the input usually consists of massive data sets. The generic protocols in such a case are of no practical use and therefore more efficient protocols are required. We focus on the problem of decision tree learning with the popular ID3 algorithm. Our protocol is considerably more efficient than generic solutions and demands both very few rounds of communication and reasonable bandwidth.

https://link.springer.com/content/pdf/10.1007/s00145-001-0019-2.pdf

Privacy Preserving Data Mining

Mobile edge computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks leveraging mobile base stations. As a promising edge technology, it can be applied to mobile, wireless, and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end-users. MEC provides seamless integration of multiple application service providers and vendors toward mobile subscribers, enterprises, and other vertical segments. It is an important component in the 5G architecture which supports variety of innovative applications and services where ultralow latency is required. This paper is aimed to present a comprehensive survey of relevant research and technological developments in the area of MEC. It provides the definition of MEC, its advantages, architectures, and application areas; where we in particular highlight related research and future directions. Finally, security and privacy issues and related existing solutions are also discussed.

/pdf/mobile-edge-computing-a-survey-3eu2fzhuxk.pdf

Mobile Edge Computing: A Survey

Data products (macrodata or tabular data and micro-data or raw data records), are designed to inform public or business policy, and research or public information Securing these products against unauthorized accesses has been a long-term goal of the database security research community and the government statistical agencies Solutions to this problem require combining several techniques and mechanisms Recent advances in data mining and machine learning algorithms have, however, increased the security risks one may incur when releasing data for mining from outside parties Issues related to data mining and security have been recognized and investigated only recently This paper deals with the problem of limiting disclosure of sensitive rules In particular it is attempted to selectively hide some frequent itemsets from large databases with as little as possible impact on other non-sensitive frequent itemsets Frequent itemsets are sets of items that appear in the database "frequently enough" and identifying them is usually the first step toward association/correlation rule or sequential pattern mining Experimental results are presented along with some theoretical issues related to this problem

/pdf/disclosure-limitation-of-sensitive-rules-4rjrixtx5w.pdf

Disclosure limitation of sensitive rules

Creating context-aware ad hoc collaborative systems remains to be one of the primary hurdles hampering the ubiquitous deployment of IT and communication services Especially under mission-critical scenarios, these services must often adhere to strict timing deadlines We believe empowering such realtime collaboration systems requires context-aware application platforms working in conjunction with ultra-low latency data transmissions In this paper, we make a strong case that this could be accomplished by combining the novel communication architectures being proposed for 5G with the principles of Mobile Edge Computing (MEC) We show that combining 5G with MEC would enable inter- and intra-domain use cases that are otherwise not feasible

Enabling Real-Time Context-Aware Collaboration through 5G and Mobile Edge Computing

Next generation 5G communication systems will need to employ a range of diverse technologies in order to support vehicle-to-everything (V2X) use cases, ultimately leading to accident-free, cooperative autonomous vehicles that use the available roadway efficiently. V2X is considered as one of the most challenging applications of 5G, as it requires ultra-reliable and low-latency communication for safety-critical use cases and has to provide high data rates in many scenarios. This paper discusses design aspects for the radio access in 5G V2X. Selected key technologies and their integration towards future 5G V2X physical layer are addressed. We discuss channel modeling in the context of 5G V2X use cases and we present first results for frame structure and numerology design, coexistence with earlier systems, multi-link synchronization, and multi-antenna transmission techniques.

Design aspects for 5G V2X physical layer

Design and analysis of compressive antenna arrays for direction of arrival estimation

Objective: To assess the effect of acidulated phosphate fluoride gel (APF), sodium fluoride varnish (NaF) and casein phosphopeptide-amorphous calcium phosphate fluoride paste (CPP-ACPF) on the dental erosion produced by coca cola in primary and permanent teeth. Design: Sixty extracted human primary molars (n = 30) and young permanent premolars (n = 30) were used in this study. The coronal portion of each tooth was sectioned mesio-distally. Specimens were prepared by embedding the crown sections in acrylic resin blocks leaving the enamel surfaces exposed. Specimens were ground, polished and randomly assigned to one of three groups each of 10 according to the protective agent used: APF gel (1.23% F), NaF varnish (0.1%F), and CPP-ACPF paste (0.2%F). Half of the exposed enamel surface was protected with adhesive tape during the treatment of the remaining surface according to their group. Six daily demineralization-remineralization cycles of 5 minutes of immersion in a cola drink (pH 2.3) and 30 minutes in artificial saliva were conducted for 14 days. Surface Vickers Micro-hardness readings were recorded at baseline and 14 days later for both halves. Percentage surface microhardness reduction (%SMHR) was then calculated. Data were analyzed using ANOVA and Duncan's post-hoc test ( p < 0.05). Results: All of the tested fluoride treatments were able to reduce erosive enamel loss in both primary and permanent groups. In primary teeth only APF gel showed significantly higher anti-erosive effect than both fluoride varnish and CPP- ACPF paste. In permanent teeth both CPP-ACPF paste and APF gel showed significantly higher protective anti- erosive effect than fluoride varnish. Conclusions: under the conditions of this study, all of the tested fluoride treatments were able to reduce erosive enamel loss in both primary and permanent teeth. Primary and permanent enamel substrates reacted differently to different fluoridated compounds. CPP-ACPF paste is a promising remineralizing material. (Sherine B Y Badr 1 , Mohamed A Ibrahim. Protective effect of three different fluoride pretreatments on artificially induced dental erosion in primary and permanent teeth. Journal of American Science 2010;6(11):442-451). (ISSN: 1545-1003).

/pdf/protective-effect-of-three-different-fluoride-pretreatments-257l8wlbeg.pdf

Mohamed Ibrahim

Papers

Disclosure limitation of sensitive rules

Enabling Real-Time Context-Aware Collaboration through 5G and Mobile Edge Computing

Design aspects for 5G V2X physical layer

Design and analysis of compressive antenna arrays for direction of arrival estimation

Protective effect of three different fluoride pretreatments on artificially induced dental erosion in primary and permanent teeth