Biblio

The static and dynamic malware analysis are used by industrialists and academics to understand malware capabilities and threat level. The antimalware industries calculate malware threat levels using different techniques which involve human involvement and a large number of resources and analysts. As malware complexity, velocity and volume increase, it becomes impossible to allocate so many resources. Due to this reason, it is projected that the number of malware apps will continue to rise, and that more devices will be targeted in order to commit various sorts of cybercrime. It is therefore necessary to develop techniques that can calculate the damage or threat posed by malware automatically as soon as it is identified. In this way, early warnings about zero-day (unknown) malware can assist in allocating resources for carrying out a close analysis of it as soon as it is identified. In this paper, a fuzzy modelling approach is described for calculating the potential risk of malicious programs through static malware analysis.

Cloud provides a low maintenance and affordable storage to various applications and users. The data owner allows the cloud users to access the documents placed in the cloud service provider based on the user's access control vector provided to the cloud users by the data owners. In such type of scenarios, the confidentiality of the documents exchanged between the cloud service provider and the users should be maintained. The existing approaches used to provide this facility are not computation and communication efficient for performing key updating in the data owner side and the key recovery in the user side. This paper discusses the key management services provided to the cloud users. Remote key management and client-side key management are two approaches used by cloud servers. This paper also aims to discuss the method for destroying the encryption/decryption group keys for shared data to securing the data after deletion. Crypto Shredding or Crypto Throw technique is deployed for the same.

Since trajectory data is widely collected and utilized for scientific research and business purpose, publishing trajectory without proper privacy-policy leads to an acute threat to individual data. Recently, several methods, i.e., k-anonymity, l-diversity, t-closeness have been studied, though they tend to protect by reducing data depends on a feature of each method. When a strong privacy protection is required, these methods have excessively reduced data utility that may affect the result of scientific research. In this research, we suggest a novel approach to tackle this existing dilemma via an adding noise trajectory on a vector-based grid environment.

In most applications, security attributes are pretty difficult to meet but it becomes even a bigger challenge when talking about Grid Computing. To secure data passes in Grid Systems, we need a professional scheme that does not affect the overall performance of the grid system. Therefore, we previously developed a new security scheme “ULTRA GRIDSEC” that is used to accelerate the performance of the symmetric key encryption algorithms for both stream and block cipher encryption algorithms. The scheme is used to accelerate the security of data pass between elements of our newly developed pure peer-to-peer desktop grid framework, “HIMAN”. It also enhances the security of the encrypted data resulted from the scheme and prevents the problem of weak keys of the encryption algorithms. This paper covers the analysis and evaluation of this scheme showing the different factors affecting the scheme performance, and covers the efficiency of the scheme from the security prospective. The experimental results are highlighted for two types of encryption algorithms, TDES as an example for the block cipher algorithms, and RC4 as an example for the stream cipher algorithms. The scheme speeds up the former algorithm by 202.12% and the latter one by 439.7%. These accelerations are also based on the running machine's capabilities.

A key exchange protocol is an important primitive in the field of information and network security and is used to exchange a common secret key among various parties. A number of key exchange protocols exist in the literature and most of them are based on the Diffie-Hellman (DH) problem. But, these DH type protocols cannot resist to the modern computing technologies like quantum computing, grid computing etc. Therefore, a more powerful non-DH type key exchange protocol is required which could resist the quantum and exponential attacks. In the year 2013, Lei and Liao, thus proposed a lattice-based key exchange protocol. Their protocol was related to the NTRU-ENCRYPT and NTRU-SIGN and so, was referred as NTRU-KE. In this paper, we identify that NTRU-KE lacks the authentication mechanism and suffers from the man-in-the-middle (MITM) attack. This attack may lead to the forging the authenticated users and exchanging the wrong key.

Critical infrastructures have suffered from different kind of cyber attacks over the years. Many of these attacks are performed using malwares by exploiting the vulnerabilities of these resources. Smart power grid is one of the major victim which suffered from these attacks and its SCADA system are frequently targeted. In this paper we describe our proposed framework to analyze smart power grid, while its SCADA system is under attack by malware. Malware propagation and its effects on SCADA system is the focal point of our analysis. OMNeT++ simulator and openDSS is used for developing and analyzing the simulated smart power grid environment.

The rapid development of Internet has resulted in massive information overloading recently. These information is usually represented by high-dimensional feature vectors in many related applications such as recognition, classification and retrieval. These applications usually need efficient indexing and search methods for such large-scale and high-dimensional database, which typically is a challenging task. Some efforts have been made and solved this problem to some extent. However, most of them are implemented in a single machine, which is not suitable to handle large-scale database.In this paper, we present a novel data index structure and nearest neighbor search algorithm implemented on Apache Spark. We impose a grid on the database and index data by non-empty grid cells. This grid-based index structure is simple and easy to be implemented in parallel. Moreover, we propose to build a scalable KNN graph on the grids, which increase the efficiency of this index structure by a low cost in parallel implementation. Finally, experiments are conducted in both public databases and synthetic databases, showing that the proposed methods achieve overall high performance in both efficiency and accuracy.

This paper proposes a novel plan of compacting encoded pictures with helper data. The substance manager scrambles the first uncompressed pictures furthermore creates some helper data, which will be utilized for information pressure and picture recreation. At that point, the channel supplier who can't get to the first substance may pack the encoded information by a quantization technique with ideal parameters that are gotten from a piece of helper data and a pressure proportion mutilation criteria, and transmit the packed information, which incorporate a scrambled sub-picture, the quantized information, the quantization parameters and an alternate piece of assistant data. At recipient side, the key picture substance can be reproduced utilizing the packed scrambled information and the mystery key.

Science Gateways bridge multiple computational grids and clouds, acting as overlay cyber infrastructure. Gateways have three logical tiers: a user interfacing tier, a resource tier and a bridging middleware tier. Different groups may operate these tiers. This introduces three security challenges. First, the gateway middleware must manage multiple types of credentials associated with different resource providers. Second, the separation of the user interface and middleware layers means that security credentials must be securely delegated from the user interface to the middleware. Third, the same middleware may serve multiple gateways, so the middleware must correctly isolate user credentials associated with different gateways. We examine each of these three scenarios, concentrating on the requirements and implementation of the middleware layer. We propose and investigate the use of a Credential Store to solve the three security challenges.

Being the most important critical infrastructure in Cyber-Physical Systems (CPSs), a smart grid exhibits the complicated nature of large scale, distributed, and dynamic environment. Taxonomy of attacks is an effective tool in systematically classifying attacks and it has been placed as a top research topic in CPS by a National Science Foundation (NSG) Workshop. Most existing taxonomy of attacks in CPS are inadequate in addressing the tight coupling of cyber-physical process or/and lack systematical construction. This paper attempts to introduce taxonomy of attacks of agent-based smart grids as an effective tool to provide a structured framework. The proposed idea of introducing the structure of space-time and information flow direction, security feature, and cyber-physical causality is innovative, and it can establish a taxonomy design mechanism that can systematically construct the taxonomy of cyber attacks, which could have a potential impact on the normal operation of the agent-based smart grids. Based on the cyber-physical relationship revealed in the taxonomy, a concrete physical process based cyber attack detection scheme has been proposed. A numerical illustrative example has been provided to validate the proposed physical process based cyber detection scheme.