• Journal of Information Processing Systems
• /
• 제8권2호
• /
• pp.347-358
• /
• 2012

Recently, security researches have been processed on the method to cover a broader range of hacking attacks at the low level in the perspective of hardware. This system security applies not only to individuals' computer systems but also to cloud environments. "Cloud" concerns operations on the web. Therefore it is exposed to a lot of risks and the security of its spaces where data is stored is vulnerable. Accordingly, in order to reduce threat factors to security, the TCG proposed a highly reliable platform based on a semiconductor-chip, the TPM. However, there have been no technologies up to date that enables a real-time visual monitoring of the security status of a PC that is operated based on the TPM. And the TPB has provided the function in a visual method to monitor system status and resources only for the system behavior of a single host. Therefore, this paper will propose a m-TMS (Mobile Trusted Monitoring System) that monitors the trusted state of a computing environment in which a TPM chip-based TPB is mounted and the current status of its system resources in a mobile device environment resulting from the development of network service technology. The m-TMS is provided to users so that system resources of CPU, RAM, and process, which are the monitoring objects in a computer system, may be monitored. Moreover, converting and detouring single entities like a PC or target addresses, which are attack pattern methods that pose a threat to the computer system security, are combined. The branch instruction trace function is monitored using a BiT Profiling tool through which processes attacked or those suspected of being attacked may be traced, thereby enabling users to actively respond.

• 정보보호학회논문지
• /
• 제28권6호
• /
• pp.1489-1497
• /
• 2018

웹 애플리케이션 서비스의 종류가 다양해짐과 동시에 사이버 위협이 급증하여 침입탐지에 대한 연구가 계속되고 있다. 기존의 단일 방어체계에서 다단계 보안으로 진행됨에 따라 대량의 보안이벤트 연관성을 분석하여 명확한 침입에 대해 대응하고 있다. 그러나 대상시스템의 OS, 서비스, 웹 애플리케이션 종류 및 버전을 실시간으로 점검하기 어려운 측면이 있고, 네트워크 기반의 보안장비에서 발생하는 침입탐지 이벤트만으로는 대상지의 취약여부와 공격의 성공여부를 확인 할 수 없는 문제점과 연관성 분석이 되지 않은 위협의 사각지대가 발생할 수 있다. 본 논문에서는 침입탐지이벤트의 유효성을 검증하기 위한 기법을 제안한다. 제안된 기법은 공격에 상응하는 대상시스템의 반응을 사상(mapping)하여 응답트래픽을 추출하고, TF-IDF를 통해 라인(line)기반으로 가중치를 환산하고 높은 수치부터 순차적으로 확인하여 대상시스템의 취약여부와 유효성이 높은 침입탐지이벤트를 검출하였다.

• International Journal of Computer Science & Network Security
• /
• 제22권6호
• /
• pp.390-399
• /
• 2022

Cyber security and resilience are phrases that describe safeguards of ICTs (information and communication technologies) from cyber-attacks or mitigations of cyber event impacts. The sole purpose of Risk models are detections, analyses, and handling by considering all relevant perceptions of risks. The current research effort has resulted in the development of a new paradigm for safeguarding services offered online which can be utilized by both service providers and users. customers. However, rather of relying on detailed studies, this approach emphasizes task selection and execution that leads to successful risk treatment outcomes. Modelling intelligent CSGs (Cyber Security Games) using MLTs (machine learning techniques) was the focus of this research. By limiting mission risk, CSGs maximize ability of systems to operate unhindered in cyber environments. The suggested framework's main components are the Threat and Risk models. These models are tailored to meet the special characteristics of online services as well as the cyberspace environment. A risk management procedure is included in the framework. Risk scores are computed by combining probabilities of successful attacks with findings of impact models that predict cyber catastrophe consequences. To assess successful attacks, models emulating defense against threats can be used in topologies. CSGs consider widespread interconnectivity of cyber systems which forces defending all multi-step attack paths. In contrast, attackers just need one of the paths to succeed. CSGs are game-theoretic methods for identifying defense measures and reducing risks for systems and probe for maximum cyber risks using game formulations (MiniMax). To detect the impacts, the attacker player creates an attack tree for each state of the game using a modified Extreme Gradient Boosting Decision Tree (that sees numerous compromises ahead). Based on the findings, the proposed model has a high level of security for the web sources used in the experiment.

• 융합보안논문지
• /
• 제12권1호
• /
• pp.35-42
• /
• 2012

데이터 트래픽의 증가와 대용량 실시간 서비스와 관련된 요구사항들의 증가는 음성이나 전용선 서비스를 주된 목적으로 하는 기존의 시간분할 다중화(TDM: Time Division Multiplexing) 기반 네트워크에서 좀 더 유연하고 동적인 구성이 가능한 광 네트워크로의 전환을 요구하고 있다. 이러한 광 네트워크는 데이터, 비디오, 그리고 음성을 전달할 수 있는 다수의 채널을 제공하는 핵심 인프라가 되었다. 이를 위해 차세대 패킷광 통합망은 네트워크 이상이 발생하여도 용인할 수 있는 수준의 서비스를 지속적으로 제공할 수 있어야 한다. 또한 신속하고 최적화된 복구(restoration) 정책은 GMPLS(Generalized Multi-Protocol Label Switching) 기반 제어평면을 사용으로 하는 차세대 패킷광 통합망의 가장 중요한 요구사항이 되었다. 본 논문은 GMPLS 기반 다계층 패킷광 통합망에서 신속하고 일원화된 복구를 지원하기 위한 계층적인 다계층 복구방식을 살펴보고 이를 지원하기 위한 구현방식을 제안하는 것을 목적으로 하고 있다. 또한 본 논문에서는 기존의 신호 및 라우팅 프로토콜을 수정하지 않고 제안한 방식을 구현할 수 있는 방안의 제안을 목적으로 하고 있다.

• International Journal of Computer Science & Network Security
• /
• 제22권10호
• /
• pp.113-130
• /
• 2022

Sophisticated automation-based electronics world, more electrical and electronic devices are being used by people from different regions across the universe. Different manufacturers and vendors develop and market a wide variety of power generation and utilization devices under different operating parameters and conditions. People use a variety of appliances which use electrical energy as power source. These appliances or gadgets utilize the generated energy in different ratios. Night time the utilization will be less when compared with day time utilization of power. In industrial areas especially mechanical industries or Heavy machinery usage regions power utilization will be a diverse at different time intervals and it vary dynamically. This always causes a fluctuation in the grid lines because of the random and intermittent use of these apparatus while the power generating apparatus is made to operate to provide a steady output. Hence it necessitates designing and developing a method to optimize the power generated and the power utilized. Lot of methodologies has been proposed in the recent years for effective optimization and economical load dispatch. One such technique based on intelligent and evolutionary based is Black Widow Optimization BWO. To enhance the optimization level BWO is hybridized. In this research BWO based optimize the load for multi area is proposed to optimize the cost function. A three type of system was compared for economic loads of 16, 40, and 120 units. In this research work, BWO is used to improve the convergence rate and is proven statistically best in comparison to other algorithms such as HSLSO, CGBABC, SFS, ISFS. Also, BWO algorithm best optimize the cost parameter so that dynamically the load and the cost can be controlled simultaneously and hence effectively the generated power is maximum utilized at different time intervals with different load capacity in different regions of utilization.

• International Journal of Computer Science & Network Security
• /
• 제23권12호
• /
• pp.101-106
• /
• 2023

Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2001년도 추계학술발표논문집 (하)
• /
• pp.943-946
• /
• 2001

대부분의 안전한 운영체제는 주체와 객체에 보안 등급을 부여하여 운영하는 다중등급 정책(MLP: Multi-Level Policy)을 수용하고 있으며, BLP 모델은 이 정책을 표현하는 검증된 대표적인 모델이다. 하지만 이러한 다중 등급 보안 운영체제들은 접근 주체인 프로세스가 접근 객체로서 존재하는 등급화 된 프로그램을 실행 시 새로운 프로세스를 위한 보안 등급을 부여해야 하는데, 접근 주체와 접근 객체의 보안 등급이 다를 경우 보안 등급 결정 문제가 발생하며 정보보호의 목적에 위배되는 결과가 발생한다. 이에 본 논문에서는 위에 언급된 문제를 해결할 수 있는 방안을 BLP 모델 측면에서 고찰한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제3권1호
• /
• pp.5-25
• /
• 2009

In recent years the popularity of multi-hop wireless networks has been growing. Its flexible topology and abundant routing path enables many types of applications. However, the lack of a centralized controller often makes it difficult to design a reliable service in multi-hop wireless networks. While packet routing has been the center of attention for decades, recent research focuses on data discovery such as file sharing in multi-hop wireless networks. Although there are many peer-to-peer lookup (P2P-lookup) schemes for wired networks, they have inherent limitations for multi-hop wireless networks. First, a wired P2P-lookup builds a search structure on the overlay network and disregards the underlying topology. Second, the performance guarantee often relies on specific topology models such as random graphs, which do not apply to multi-hop wireless networks. Past studies on wireless P2P-lookup either combined existing solutions with known routing algorithms or proposed tree-based routing, which is prone to traffic congestion. In this paper, we present two wireless P2P-lookup schemes that strictly build a topology-dependent structure. We first propose the Ring Interval Graph Search (RIGS) that constructs a DHT only through direct connections between the nodes. We then propose the ValleyWalk, a loosely-structured scheme that requires simple local hints for query routing. Packet-level simulations showed that RIGS can find the target with near-shortest search length and ValleyWalk can find the target with near-shortest search length when there is at least 5% object replication. We also provide an analytic bound on the search length of ValleyWalk.

• 한국사회복지학
• /
• 제62권1호
• /
• pp.211-235
• /
• 2010

본 연구는 장애인 사회보장수급권의 실효성 기준에 관한 연구이다. 시민권론과 기본권론 그리고 장애인 복지 논의들을 결합하여 장애인 사회보장수급권의 실효성을 가늠할 수 있는 기준을 마련함으로써, 장애인을 위한 사회보장이 명목적이지 않고 실효적으로 존재하기 위해 요구되는 구체적인 지침을 제시하는 데 그 목적이 있다. 일반적인 사회보장수급권의 실효성 논의를 토대로 사회보장수급권의 4대권리 영역과 5대 일반원칙을 도출하고, 이를 장애인의 3대 사회보장 영역에 적용할 수 있도록 확대하였다. 또한 장애인 집단의 특수성을 반영한 구체적인 기준을 설정하였다. 각 기준들을 개별 법률에 적용하는 동 기준의 측정치는 '높다'와 '낮다'이다. 이러한 장애인 사회보장수급권의 실효성에 관한 기준 연구는 다음과 같은 함의가 존재한다. 첫째, 정책적 측면에서 동 기준은 장애인 사회보장 제도의 수준에 대한 객관적인 인식을 가능하게 한다. 둘째, 이론적 측면에서 동 연구는 학제간 연구를 통해 일반적인 사회보장수급권의 실효성에 대한 논의를 보다 확장시킴과 동시에 장애인 사회보장수급권의 실효성 기준을 구체적으로 제시함으로써 실증 연구의 토대를 마련하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권7호
• /
• pp.2599-2613
• /
• 2015

Multi-index hashing (MIH) is the state-of-the-art method for indexing binary codes, as it di-vides long codes into substrings and builds multiple hash tables. However, MIH is based on the dataset codes uniform distribution assumption, and will lose efficiency in dealing with non-uniformly distributed codes. Besides, there are lots of results sharing the same Hamming distance to a query, which makes the distance measure ambiguous. In this paper, we propose a data-oriented multi-index hashing method (DOMIH). We first compute the covariance ma-trix of bits and learn adaptive projection vector for each binary substring. Instead of using substrings as direct indices into hash tables, we project them with corresponding projection vectors to generate new indices. With adaptive projection, the indices in each hash table are near uniformly distributed. Then with covariance matrix, we propose a ranking method for the binary codes. By assigning different bit-level weights to different bits, the returned bina-ry codes are ranked at a finer-grained binary code level. Experiments conducted on reference large scale datasets show that compared to MIH the time performance of DOMIH can be improved by 36.9%-87.4%, and the search accuracy can be improved by 22.2%. To pinpoint the potential of DOMIH, we further use near-duplicate image retrieval as examples to show the applications and the good performance of our method.