There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Data Mining - Concepts and Techniques.

The term photonic crystals appears because of the analogy between electron waves in crystals and the light waves in artificial periodic dielectric structures. During the recent years the investigation of one-, two-and three-dimensional periodic structures has attracted a widespread attention of the world optics community because of great potentiality of such structures in advanced applied optical fields. The interest in periodic structures has been stimulated by the fast development of semiconductor technology that now allows the fabrication of artificial structures, whose period is comparable with the wavelength of light in the visible and infrared ranges.

http://ieeexplore.ieee.org/iel5/6354/16969/00781867.pdf

Photonic crystals

Smartphone» have become a prime target for cyber criminals. Android being the market leader is the major target of malicious attackers. Covert techniques used by the malware make them hard to detect with signature based methods. In this paper, we present AndroPIn — a novel Android based malware detection tool using Permissions and Intents. The proposed framework overcomes the limitation of stealthy techniques used by malware by exploiting the usage pattern of permissions and intents. These features, which play a major role in sharing user data and device resources cannot be obfuscated or altered. These vital features are well suited for resource constrained smartphones. Experimental evaluation on a corpus of real-world malware and benign apps demonstrate that the proposed algorithm can effectively detect malicious apps with a low runtime overheads and is resilient to common obfuscations methods.

AndroPIn: Correlating Android permissions and intents for malware detection

Most of the current cloud computing platforms offer Infrastructure as a Service (IaaS) model, which aims to provision basic virtualised computing resources as on-demand and dynamic services. Nevertheless, a single cloud does not have limitless resources to offer to its users, hence the notion of an Inter-Cloud enviroment where a cloud can use the infrastructure resources of other clouds. However, there is no common framework in existence that allows the service owners to seamlessly provision even some basic services across multiple cloud service providers, albeit not due to any inherent incompatibility or proprietary nature of the foundation technologies on which these cloud platforms are built. In this paper we present a novel solution which aims to cover a gap in a subsection of this problem domain. Our solution offers a security architecture that enables service owners to provision a dynamic and service-oriented secure virtual private network on top of multiple cloud IaaS providers. It does this by leveraging the scalability, robustness and flexibility of peer-to-peer overlay techniques to eliminate the manual configuration, key management and peer churn problems encountered in setting up the secure communication channels dynamically, between different components of a typical service that is deployed on multiple clouds. We present the implementation details of our solution as well as experimental results carried out on two commercial clouds.

/pdf/secure-communication-using-dynamic-vpn-provisioning-in-an-2vr99i7g4i.pdf

Secure communication using dynamic VPN provisioning in an Inter-Cloud environment

Social media is extensively used nowadays and is gaining popularity among the users with the increasing growth in the network capacity, connectivity, and speed. Moreover, affordable prices of data plans, especially mobile data packages, have considerably increased the use of multimedia by different users. This includes terrorists who use social media platforms to promote their ideology and intimidate their adversaries. It is therefore very important to develop automated solutions to semantically analyse given multimedia contents to assist law enforcement agencies in the preventive policing of online activities. A major challenge for the social media forensic analysis is to preserve the privacy of citizens who use online social networking platforms. This paper presents results of European H2020 project RED-Alert that aims to enable secure and privacy preserving data processing; hence the malicious content and the corresponding personality can be tracked while the privacy of innocent citizens can be preserved. We have mined seven social media channels for content and providing support for ten languages for analysis. Our proposed solution is designed to ensure security and policing of online contents by detecting terrorist material. We have used speech recognition, face and object detection besides audio event detection to extract information from multimedia files. We have applied anonymization techniques to ensure the privacy of citizens using social media. We have discussed the challenges and prospects of this work especially the need of using digital forensic techniques while respecting European and national data protection laws notably GDPR.

/pdf/privacy-preserving-social-media-forensic-analysis-for-4iyj3ebbwm.pdf

Privacy-Preserving Social Media Forensic Analysis for Preventive Policing of Online Activities

Surname (family name) analysis is used in geography to understand population origins, migration, identity, social norms and cultural customs. Some of these are supposedly evolved over generations. Surnames exhibit good statistical properties that can be used to extract information in names data set such as automatic detection of ethnic or community groups in names. An e-mail address, often contains surname as a substring. This containment may be full or partial. An e-mail address categorization based on semantics of surnames is the objective of this paper. This is achieved in two phases. First phase deals with surname representation and clustering. Here, a vector space model is proposed where latent semantic analysis is performed. Clustering is done using the method called average-linkage method. In the second phase, an email is categorized as belonging to one of the categories (discovered in first phase). For this, substring matching is required, which is done in an efficient way by using suffix tree data structure. We perform experimental evaluation for the 500 most frequently occurring surnames in India and United Kingdom. Also, we categorize the e-mail addresses that have these surnames as substrings.

/pdf/e-mail-address-categorization-based-on-semantics-of-surnames-1y3aj4pxk8.pdf

E-mail address categorization based on semantics of surnames

This paper proposes an algorithm to perform privacy-preserving (PP) speaker recognition using Gaussian mixture models (GMM). We consider a scenario where the users have to enrol their voice biometric with the third-party service providers to access different services (i.e., banking). Once the enrolment is done, the users can authenticate themselves to the system using their voice instead of passwords. Since the voice is unique for individuals, storing the users’ voice features at the third-party server raises privacy concerns. Hence, in this paper we propose a novel technique using randomization to perform voice authentication, which allows users to enrol and authenticate their voice in the encrypted domain, hence privacy is preserved. To achieve this, we redesign the GMM to work on encrypted domain. The proposed algorithm is validated using the widely used TIMIT speech corpus. Experimental results demonstrate that the proposed PP algorithm does not degrade the performance compared to the non-PP method and achieve 96.16% true positive rate and 1.77% false positive rate. Demonstration on Android smartphone shows that the algorithm can be executed within two seconds with only 30% of CPU power.

Muttukrishnan Rajarajan

Papers

AndroPIn: Correlating Android permissions and intents for malware detection

Secure communication using dynamic VPN provisioning in an Inter-Cloud environment

Privacy-Preserving Social Media Forensic Analysis for Preventive Policing of Online Activities

E-mail address categorization based on semantics of surnames

Redesign of Gaussian Mixture Model for Efficient and Privacy-preserving Speaker Recognition