Herndon, VA, United States

Network Security Technology

www.netsec.net/
Herndon, VA, United States
SEARCH FILTERS
Time filter
Source Type

Yang G.,Beijing University of Posts and Telecommunications | Tian Z.,Harbin Institute of Technology | Duan W.,Network Security Technology
Journal of Chemical and Pharmaceutical Research | Year: 2014

Advanced persistent threat (APT) has received broad interest in recent years. APT stands for aiming at specific goal, experienced attackers use advanced technique and take a long period of time to collect information or break the network. APT can’t be blocked through traditional ways for the incubation period always being several month even years, and the initial invasion always being too complicated to be prevented. Faced these threats, a new efficient approach should be discovered and applicated to protect our network. © 2014, Journal of Chemical and Pharmaceutical Research. All rights reserved.


Liu W.,Nanyang Normal University | Qiu B.,Hebei University of Technology | Cui M.,Nanyang Normal University | Ding J.,Network Security Technology
PLoS ONE | Year: 2017

Depth image-based rendering (DIBR), which is used to render virtual views with a color image and the corresponding depth map, is one of the key techniques in the 2D to 3D conversion process. Due to the absence of knowledge about the 3D structure of a scene and its corresponding texture, DIBR in the 2D to 3D conversion process, inevitably leads to holes in the resulting 3D image as a result of newly-exposed areas. In this paper, we proposed a structure-aided depth map preprocessing framework in the transformed domain, which is inspired by recently proposed domain transform for its low complexity and high efficiency. Firstly, our framework integrates hybrid constraints including scene structure, edge consistency and visual saliency information in the transformed domain to improve the performance of depth map preprocess in an implicit way. Then, adaptive smooth localization is cooperated and realized in the proposed framework to further reduce over-smoothness and enhance optimization in the non-hole regions. Different from the other similar methods, the proposed method can simultaneously achieve the effects of hole filling, edge correction and local smoothing for typical depth maps in a united framework. Thanks to these advantages, it can yield visually satisfactory results with less computational complexity for high quality 2D to 3D conversion. Numerical experimental results demonstrate the excellent performances of the proposed method. © 2017 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Ke Y.,Network Security Technology | Zhang M.,Network Security Technology | Liu J.,Network Security Technology
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2017

This paper proposes a novel scheme of separable multiple bits reversible data hiding in encrypted domain based on LWE (Learning withErrors). Multi-band data could be embedded by recoding the redundancy of ciphertext, which does enhance the capacity of embedding data. With embedded ciphertext, the additional data can be extracted by using data-hiding key, and the original data can be recovered losslessly by using decryption key, the processes of extraction and decryption are separable.By deducing the error probability of the scheme, parameters in the scheme which directly related to the scheme’s correctness is mainly discussed, and reasonable ranges of the parameters are obtained by experiments. When analyzing the security, the probability distribution function of the embedded cipher text is deduced and the statistic features of ciphertext are analyzed, which both proved the embedded data isn’t detective. The proposed scheme is based on encryption process, so it can apply to different kinds of media vehicle.Experimental results have demonstrated that the proposed scheme can not only achieve statistical security without degrading the quality of encryption, but realize that 1bit original data can maximally load multiple-bit additional data in encrypted domain. © Springer International Publishing AG 2017.


Sui L.,Xi'an University of Science and Technology | Sui L.,Network Security Technology | Duan K.,Xi'an University of Science and Technology | Liang J.,Xi'an University of Technology | Hei X.,Xi'an University of Science and Technology
Optics Express | Year: 2014

A double-image encryption is proposed based on the discrete fractional random transform and logistic maps. First, an enlarged image is composited from two original images and scrambled in the confusion process which consists of a number of rounds. In each round, the pixel positions of the enlarged image are relocated by using cat maps which are generated based on two logistic maps. Then the scrambled enlarged image is decomposed into two components. Second, one of two components is directly separated into two phase masks and the other component is used to derive the ciphertext image with stationary white noise distribution by using the cascaded discrete fractional random transforms generated based on the logistic map. The cryptosystem is asymmetric and has high resistance against to the potential attacks such as chosen plaintext attack, in which the initial values of logistic maps and the fractional orders are considered as the encryption keys while two decryption keys are produced in the encryption process and directly related to the original images. Simulation results and security analysis verify the feasibility and effectiveness of the proposed encryption scheme. © 2014 Optical Society of America.


Jin H.,Xi'an University of Science and Technology | Jin H.,Network Security Technology | Wang Y.,Xi'an University of Science and Technology
Infrared Physics and Technology | Year: 2014

This paper proposes a novel image fusion scheme based on contrast pyramid (CP) with teaching learning based optimization (TLBO) for visible and infrared images under different spectrum of complicated scene. Firstly, CP decomposition is employed into every level of each original image. Then, we introduce TLBO to optimizing fusion coefficients, which will be changed under teaching phase and learner phase of TLBO, so that the weighted coefficients can be automatically adjusted according to fitness function, namely the evaluation standards of image quality. At last, obtain fusion results by the inverse transformation of CP. Compared with existing methods, experimental results show that our method is effective and the fused images are more suitable for further human visual or machine perception. © 2014 Elsevier B.V. All rights reserved.


An anonymous hacking group which goes by the name of Shadow Brokers claims to have acquired software tools that belong to hackers linked to the National Security Agency of the United States. The previously unknown group said that it broke into the cyberespionage organization known as the Equation Group and has now put the hacking tools that it acquired up for auction. In addition to selling the hacking tools to whoever would end up as the highest bidder, the Shadow Brokers said that if it will be paid 1 million bitcoins, which currently carries a value of about $568 million, the cyberweapons will be publicly released. To back up its claims, the Shadow Brokers uploaded what looks like attack code that focuses on the security systems of routers that direct computer traffic online. According to security experts, the code looks legitimate, affecting routers manufactured by three United States companies and two Chinese companies. Specifically, the companies involved are Cisco Systems, Fortinet, Juniper Networks, Shaanxi Networkcloud Information Technology and Beijing Topsec Network Security Technology. As to the statement of Shadow Brokers that it actually has acquired such tools from the NSA-linked hackers, that is up for debate. Security experts are saying that either the group was able to carry out a one-of-a-kind security breach or that the group has put in place an elaborate hoax. Last year, researchers from Kaspersky Lab described the Equation Group as one of the most advanced hacking groups in the world. The compressed data that accompanied the post by the Shadow Brokers had a size of just over 256 MB and is said to contain hacking tools that are dated as early as 2010 belonging to the Equation Group. The posted data, which is composed mostly of poorly coded python scripts and batch scripts, has not yet been proven to actually have come from the Equation Group. However, there was little doubt that the data did indeed come from an advanced group of hackers. "These files are not fully fake for sure," said CrySys security researcher Bencsáth Boldizsár, who is widely credited for the discovery of the Flame espionage malware platform, which is linked to the Equation Group. In the email to Ars Technica, Boldizsár added that the files are likely part of the toolset of the NSA as important attack-related files, with the first guess being that they are indeed somehow linked to the Equation Group. Boldizsár's findings have been echoed by other security researchers, including Comae Technologies FZE founder Matt Suiche and International Computer Science Institute's Nicholas Weaver. A researcher from the Citizen Lab of the University of Toronto, Claudio Guarnieri, said that it would seem that the NSA launched an attack and then someone managed to trace the origin of the attack and launched a counter-hack. Guarnieri cautions that it is still too early to tell if the code and other data uploaded by the Shadow Brokers can definitely be linked to the Equation Group or to the NSA. However, he added that the code coincides with some of the exploits that was part of the catalogue leaked by infamous NSA whistleblower Edward Snowden back in 2013. © 2017 Tech Times, All rights reserved. Do not reproduce without permission.


Li H.,Network Security Technology | Hu C.,Network Security Technology
Proceedings - IEEE INFOCOM | Year: 2013

Fine-grained traffic identification (FGTI) reveals the context/purpose of each packet that flows through the network nodes/links. Instead of only indicating the application/protocol that a packet is related to, FGTI further maps the packet to a meaningful user behavior or application context. In this paper, we propose a Rule Organized Optimal Matching (ROOM) for fast and memory efficient fine-grained traffic identification. ROOM splits the identification rules into several fields and elaborately organizes the matching order of the fields. We formulate and model the optimal rule organization problem of ROOM mathematically, which is demonstrated to be NP-hard, and then we propose an approximate algorithm to solve the problem with the time complexity of O(N 2) (N is the number of fields in a rule). In order to perform evaluations, we implement ROOM and related work as real prototype systems. Also, real traces collected in wired Internet and mobile Internet are used as the experiment input. The evaluations show very promising results: 1.6X to 104.7X throughput improvement is achieved by ROOM in the real system with acceptable small memory cost. © 2013 IEEE.


Yu D.,Hangzhou Dianzi University | Zhang Y.,Hangzhou Dianzi University | Ge J.,Hangzhou Dianzi University | Wu W.,Network Security Technology
Proceedings - International Computer Software and Applications Conference | Year: 2013

Structural design patterns address concerns related to high-level structures for applications being developed. Accurately recovered instances of structural design patterns support development related tasks like program comprehension and reengineering. However, the detection of structural design pattern instances is not always a straightforward task. The lack of documentation, the ad-hoc nature of programming and the possible variants of pattern instances often lead to the low accuracy of detection. In this paper, we present an approach to the detection of instances of structural design patterns using source codes. We first transform the source codes and predefined patterns into graphs, with the classes as nodes and the relations as edges. We then identify the instances of sub-patterns that would be the possible constituents of pattern instances by means of subgraph discovery. The sub-pattern instances are further merged by joint classes to see if the collective matches one of the predefined patterns. Compared with existing approaches, our approach focuses on simple sub-patterns, not complicated patterns. In this way, it can not only simplify the detection process, but also detect multiple pattern instances at a time. The results of the experiments on detecting pattern instances of Adapter, Bridge, Composite, Decorator and Proxy from 4 open source software systems demonstrate that our approach obtains better precision than the existing approaches. © 2013 IEEE.


Yu D.,Hangzhou Dianzi University | Geng P.,Hangzhou Dianzi University | Wu W.,Network Security Technology
Proceedings - Asia-Pacific Software Engineering Conference, APSEC | Year: 2012

Software Product Line Engineering organizes the commonality and the variability of domain feature model in order to achieve large-scale software reuse. Although there are a variety of approaches to the construction of domain feature models, they are however difficult to locate inconsistency caused by frequent changes occurring in the process of evolution. This paper presents a novel approach to the construction of domain feature model and its trace ability with corresponding requirements. It first constructs a set of feature models for individual applications within same domain and their trace ability to corresponding application requirements. Then, it merges all application feature models to form the domain feature model and constructs the trace ability between features in different models. It finally extracts the domain requirements and the trace ability between domain requirements and domain features. The case of software product line for labor market monitoring applications verifies this new approach, and shows that it can not only construct domain feature model automatically and effectively, but also help locate affected requirements while features change or vice versa. © 2012 IEEE.


DUBLIN--(BUSINESS WIRE)--Research and Markets has announced the addition of the "Network Security Technology TechVision Opportunity Engine" newsletter to their offering. Technical Insights presents its latest research subscription-the Network Security Technology (NST) Alert. This monthly subscription analyzes recent global advancements across a range of security technologies that address privacy of network communications, information security, access control, and security for remote access to c

Loading Network Security Technology collaborators
Loading Network Security Technology collaborators