Modeling, analysis and defense strategies against Internet attacks.

Third, we have analyzed the tradeoff between delay caused by filtering of worms at routers, and the delay due to worms' excessive amount of network traffic. We have used the optimal control problem, to determine the appropriate tradeoffs between these two delays for a given rate of a worm spreading. Using our technique we can minimize the overall network delay by finding the number of routers that should perform filtering and the time at which they should start the filtering process.Many early Internet protocols were designed without a fundamentally secure infrastructure and hence vulnerable to attacks such as denial of service (DoS) attacks and worms. DoS attacks attempt to consume the resources of a remote host or network, thereby denying or degrading service to legitimate users. Network forensics is an emerging area wherein the source or the cause of the attacker is determined using IDS tools. The problem of finding the source(s) of attack(s) is called the "trace back problem". Lately, Internet worms have become a major problem for the security of computer networks, causing considerable amount of resources and time to be spent recovering from the disruption of systems. In addition to breaking down victims, these worms create large amounts of unnecessary network data traffic that results in network congestion, thereby affecting the entire network.In this dissertation, first we solve the trace back problem more efficiently in terms of the number of routers needed to complete the track back. We provide an efficient algorithm to decompose a network into connected components and construct a terminal network. We show that for a terminal network with n routers, the trace back can be completed in O(log n) steps.Second, we apply two classical epidemic SIS and SIR models to study the spread of Internet Worm. The analytical models that we provide are useful in determining the rate of spread and time required to infect a majority of the nodes in the network. Our simulation results on large Internet like topologies show that in a fairly small amount of time, 80% of the network nodes is infected

The Messianic Banquet: theological, liturgical and pastoral implications for Eucharistic practice especially in times of sickness and death

This thesis deals with the theological image of the Messianic Banquet and the theological, liturgical, and pastoral history and implications of the Eucharist, especially as they relate to sickness and death (near-death), particularly as observed in the Korean Presbyterian Church (Tonghap). To examine the images and meanings of the Messianic Banquet in the Eucharist, the thesis begins with meanings of the Messianic Banquet from the first century to the fourth century, and then explores John Calvin's eucharistic theology and early Korean Protestant worship. After finding the principal meaning of the Messianic Banquet in the Eucharist to be that of a foretaste of the meal in the Kingdom of Heaven, I used that image to add a new perspective to existing eucharistic rites in the Korean Presbyterian Church's Book of Common Worship (2008), especially as it pertains to the communion of the sick and dying

Identification of human-induced initiating events in the low power and shutdown operation using the Commission Error Search and Assessment method

AbstractHuman-induced initiating events, also called Category B actions in human reliability analysis, are operator actions that may lead directly to initiating events. Most conventional probabilistic safety analyses typically assume that the frequency of initiating events also includes the probability of human-induced initiating events. However, some regulatory documents require Category B actions to be specifically analyzed and quantified in probabilistic safety analysis.An explicit modeling of Category B actions could also potentially lead to important insights into human performance in terms of safety. However, there is no standard procedure to identify Category B actions. This paper describes a systematic procedure to identify Category B actions for low power and shutdown conditions. The procedure includes several steps to determine operator actions that may lead to initiating events in the low power and shutdown stages.These steps are the selection of initiating events, the selection of systems or components, the screening of unlikely operating actions, and the quantification of initiating events. The procedure also provides the detailed instruction for each step, such as operator's action, information required, screening rules, and the outputs.Finally, the applicability of the suggested approach is also investigated by application to a plant example

Behavior-based anomaly detection on big data

Recently, cyber-targeted attacks such as APT (Advanced Persistent Threat) are rapidly growing as a social and national threat. It is an intelligent cyber-attack that infiltrates the target organization and enterprise clandestinely using various methods and causes considerable damage by making a final attack after long-term and through preparations. These attacks are threatening cyber worlds such as Internet by infecting and attacking the devices on this environment with the malicious code, and by destroying them or gaining their authorities. Detecting these attacks requires collecting and analysing data from various sources (network, host, security equipment, and devices) over the long haul. Therefore, we propose the method that can recognize the cyber-targeted attack and detect the abnormal behavior based on Big Data. The proposed approach analyses faster and precisely various logs and monitoring data using Big Data storage and processing technology. In particular, we evaluated that the suspicious behavior analysis using MapReduce is effective in analysing large-scale behavior monitoring and log data from various sources

User Detection Performance Analysis for Grant-Free Uplink Transmission in Large-Scale Antenna Systems

In this paper, user detection performance of a grant-free uplink transmission in a large scale antenna system is analyzed, in which a general grant-free multiple access is considered as the system model and Zadoff-Chu sequence is used for the uplink pilot. The false alarm probabilities of various user detection schemes under the target detection probabilities are evaluated

Context-Aware Planning and Environment-Aware Memory for Instruction Following Embodied Agents

Accomplishing household tasks such as 'bringing a cup of water' requires planning step-by-step actions by maintaining knowledge about the spatial arrangement of objects and the consequences of previous actions. Perception models of the current embodied AI agents, however, often make mistakes due to a lack of such knowledge but rely on imperfect learning of imitating agents or an algorithmic planner without knowledge about the changed environment by the previous actions. To address the issue, we propose CPEM (Context-aware Planner and Environment-aware Memory) to incorporate the contextual information of previous actions for planning and maintaining spatial arrangement of objects with their states (e.g., if an object has been moved or not) in an environment to the perception model for improving both visual navigation and object interaction. We observe that CPEM achieves state-of-the-art task success performance in various metrics using a challenging interactive instruction following benchmark both in seen and unseen environments by large margins (up to +10.70% in unseen env.). CPEM with the templated actions, named ECLAIR, also won the 1st generalist language grounding agents challenge at Embodied AI Workshop in CVPR'23.Comment: ICCV 202