作者: 設(shè)施 時(shí)間: 2025-3-21 22:23 作者: 值得贊賞 時(shí)間: 2025-3-22 04:03
Patricia Bachmann,Ignaz Rutter,Peter Stumpfligent cyber deception systems. Such systems can dynamically plan the deception strategy and use several actuators to effectively implement the cyber deception measures. We also present a prototype of a framework designed to simplify the development of cyber deception tools to be integrated with such intelligent agents.作者: 流利圓滑 時(shí)間: 2025-3-22 06:00 作者: 勉強(qiáng) 時(shí)間: 2025-3-22 11:35 作者: 憤慨一下 時(shí)間: 2025-3-22 13:05
Malware Deception with Automatic Analysis and Generation of HoneyResourceeving something. Towards this end, this chapter introduces our preliminary systematic study and a prototype system, ., for automatically extracting the system resource constraints from malware code and generating HoneyResource (e.g., malware vaccines) based on the system resource conditions.作者: glamor 時(shí)間: 2025-3-22 20:42 作者: 不整齊 時(shí)間: 2025-3-22 22:55
Lecture Notes in Computer Scienceeving something. Towards this end, this chapter introduces our preliminary systematic study and a prototype system, ., for automatically extracting the system resource constraints from malware code and generating HoneyResource (e.g., malware vaccines) based on the system resource conditions.作者: 改良 時(shí)間: 2025-3-23 02:36 作者: 討人喜歡 時(shí)間: 2025-3-23 06:24
Ehab Al-Shaer,Jinpeng Wei,Cliff WangProvides comprehensive coverage of adaptive cyber deception in many aspects, including theory and practice, sense-making and decision making, and network and system perspectives.Focuses on how to make作者: 有惡臭 時(shí)間: 2025-3-23 11:30
http://image.papertrans.cn/b/image/166770.jpg作者: faucet 時(shí)間: 2025-3-23 14:14
https://doi.org/10.1007/978-3-030-02110-8cyber deception; deception metrics; deep learning; adversarial cyber deception; differential privacy; dec作者: 表否定 時(shí)間: 2025-3-23 18:34 作者: 氣候 時(shí)間: 2025-3-23 23:33 作者: 彎曲的人 時(shí)間: 2025-3-24 04:52 作者: Incommensurate 時(shí)間: 2025-3-24 10:20
William J. Lenhart,Giuseppe Liottaigence collectors. Honeypot deception can be made more effective when applied with variety. We discuss the range of deception tactics of which honeypots can take advantage. Ideas can come from deception theory, and honeypot deceptions can benefit from planning and experimentation.作者: Ascendancy 時(shí)間: 2025-3-24 12:11
Genus, Treewidth, and Local Crossing Numberr adversaries that try to discover and exploit vulnerabilities. To improve cyber agility of networks, the NetShifter performs multi-dimensional network-level adaptive defense in full scale beyond physical constraints of the networks by adopting the software-defined network (SDN).作者: 縮減了 時(shí)間: 2025-3-24 16:55 作者: CEDE 時(shí)間: 2025-3-24 20:02 作者: 大罵 時(shí)間: 2025-3-25 02:32 作者: microscopic 時(shí)間: 2025-3-25 03:45
Rectilinear Planarity of?Partial 2-Trees game theories have considered incomplete information to consider uncertainty, how players’ different perceptions or misperceptions can affect their decision-making has not been fully addressed. In particular, we discuss . which has been used to resolve conflicts under uncertainty. In this chapter, 作者: critique 時(shí)間: 2025-3-25 09:56
Jacob Miller,Vahan Huroyan,Stephen Kobourovtems vulnerable to targeted attacks that are deceptive, persistent, adaptive, and strategic. Attack instances such as Stuxnet, Dyn, and WannaCry ransomware have shown the insufficiency of off-the-shelf defensive methods including the firewall and intrusion detection systems. Hence, it is essential t作者: FEIGN 時(shí)間: 2025-3-25 13:02
Tarik Crnovrsanin,Jacqueline Chu,Kwan-Liu Masignificant confusion in discovering and targeting cyber assets. One of the key objectives for cyber deception is to hide the true identity of the cyber assets in order to effectively deflect adversaries away from critical targets, and detect their activities early in the kill chain..Although many c作者: Preamble 時(shí)間: 2025-3-25 16:33 作者: NOT 時(shí)間: 2025-3-25 20:41 作者: figure 時(shí)間: 2025-3-26 00:16
Fabian Lipp,Alexander Wolff,Johannes Zinkf these new entrants to the market lack security engineering experience and focus heavily on time-to-market. As a result, many home and office networks contain IoT devices with security flaws and no clear path for security updates, making them attractive targets for attacks, e.g., recent IoT-centric作者: lethal 時(shí)間: 2025-3-26 08:02 作者: Finasteride 時(shí)間: 2025-3-26 09:02
Lecture Notes in Computer Sciencey to infect only targeted computers, etc. If we are able to extract the system resource constraints from malware binary code, and manipulate the environment state as ., we would then be able to deceive malware for defense purpose, e.g., immunize a computer from infections, or trick malware into beli作者: 形容詞 時(shí)間: 2025-3-26 14:46
Using Deep Learning to Generate Relational HoneyDatay little attention. In this book chapter, we discuss our secure deceptive data generation framework that makes it hard for an attacker to distinguish between the real versus deceptive data. Especially, we discuss how to generate such deceptive data using deep learning and differential privacy techni作者: PALMY 時(shí)間: 2025-3-26 17:55 作者: engender 時(shí)間: 2025-3-27 00:28
Honeypot Deception Tacticsigence collectors. Honeypot deception can be made more effective when applied with variety. We discuss the range of deception tactics of which honeypots can take advantage. Ideas can come from deception theory, and honeypot deceptions can benefit from planning and experimentation.作者: 脫離 時(shí)間: 2025-3-27 02:14
Modeling and Analysis of Deception Games Based on Hypergame Theory game theories have considered incomplete information to consider uncertainty, how players’ different perceptions or misperceptions can affect their decision-making has not been fully addressed. In particular, we discuss . which has been used to resolve conflicts under uncertainty. In this chapter, 作者: machination 時(shí)間: 2025-3-27 08:38 作者: cognizant 時(shí)間: 2025-3-27 11:20
CONCEAL: A Strategy Composition for Resilient Cyber Deception: Framework, Metrics, and Deploymentsignificant confusion in discovering and targeting cyber assets. One of the key objectives for cyber deception is to hide the true identity of the cyber assets in order to effectively deflect adversaries away from critical targets, and detect their activities early in the kill chain..Although many c作者: hypnogram 時(shí)間: 2025-3-27 16:34 作者: Rustproof 時(shí)間: 2025-3-27 17:50
Deception-Enhanced Threat Sensing for Resilient Intrusion Detectionch deceptions are particularly helpful for addressing and overcoming barriers to effective machine learning-based intrusion detection encountered in many practical deployments. For example, they can provide a rich source of training data when training data is scarce, they avoid imposing a labeling b作者: 刺穿 時(shí)間: 2025-3-27 23:06 作者: Irksome 時(shí)間: 2025-3-28 03:11
gExtractor: Automated Extraction of Malware Deception Parameters for Autonomous Cyber Deceptiond undetectable manner. While it is very hard to detect or predict attacks, adversaries can always scan the network, learn about countermeasures, and develop new evasion techniques. Active Cyber Deception (ACD) has emerged as effective means to reverse this asymmetry in cyber warfare by dynamically o作者: 使迷醉 時(shí)間: 2025-3-28 10:06
Malware Deception with Automatic Analysis and Generation of HoneyResourcey to infect only targeted computers, etc. If we are able to extract the system resource constraints from malware binary code, and manipulate the environment state as ., we would then be able to deceive malware for defense purpose, e.g., immunize a computer from infections, or trick malware into beli作者: SEED 時(shí)間: 2025-3-28 12:52 作者: tattle 時(shí)間: 2025-3-28 14:42
Dynamic Bayesian Games for Adversarial and Defensive Cyber Deception.g., a legitimate user or an attacker. The realization of the user’s type is private information due to the cyber deception. Then, we extend the one-shot simultaneous interaction into the one-shot interaction with asymmetric information structure, i.e., the signaling game. Finally, we investigate th作者: probate 時(shí)間: 2025-3-28 20:45
CONCEAL: A Strategy Composition for Resilient Cyber Deception: Framework, Metrics, and Deploymentd attackers. In fact, in this chapter our analytical and experimental work showed that highly resilient cyber deception is unlikely attainable using a single technique, but it requires an optimal composition of various concealment techniques to maximize the deception utility. We, therefore, present 作者: Encumber 時(shí)間: 2025-3-28 23:30
Deception-Enhanced Threat Sensing for Resilient Intrusion Detectionsulting system coordinates multiple levels of the software stack to achieve fast, automatic, and accurate labeling of live web data streams, and thereby detects attacks with higher accuracy and adaptability than comparable non-deceptive defenses.作者: Defense 時(shí)間: 2025-3-29 05:02
HONEYSCOPE: IoT Device Protection with Deceptive Network Views To achieve these goals, HoneyScope uses an SDN-based security gateway to create virtualized views of the network and nodes therein providing fine-grained control over the communications that individual devices may have.作者: 小蟲 時(shí)間: 2025-3-29 09:29
gExtractor: Automated Extraction of Malware Deception Parameters for Autonomous Cyber Deceptionwe present a new analytic framework and an implemented tool, called ., to analyze the malware behavior and automatically extract the deception parameters using symbolic execution in order to enable the automated creation of cyber deception plans. The deception parameters are environmental variables 作者: Ejaculate 時(shí)間: 2025-3-29 12:26 作者: chalice 時(shí)間: 2025-3-29 17:01 作者: 大炮 時(shí)間: 2025-3-29 21:11
Jacob Miller,Vahan Huroyan,Stephen Kobourov.g., a legitimate user or an attacker. The realization of the user’s type is private information due to the cyber deception. Then, we extend the one-shot simultaneous interaction into the one-shot interaction with asymmetric information structure, i.e., the signaling game. Finally, we investigate th作者: 召集 時(shí)間: 2025-3-30 03:57 作者: CIS 時(shí)間: 2025-3-30 06:37
Tarik Crnovrsanin,Jacqueline Chu,Kwan-Liu Masulting system coordinates multiple levels of the software stack to achieve fast, automatic, and accurate labeling of live web data streams, and thereby detects attacks with higher accuracy and adaptability than comparable non-deceptive defenses.作者: PALSY 時(shí)間: 2025-3-30 11:22
