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A Network Telescope Approach for Inferring and Characterizing IoT ExploitationsUnknown Date (has links)
While the seamless interconnection of IoT devices with the physical realm
is envisioned to bring a plethora of critical improvements on many aspects and in
diverse domains, it will undoubtedly pave the way for attackers that will target and
exploit such devices, threatening the integrity of their data and the reliability of
critical infrastructure. The aim of this thesis is to generate cyber threat intelligence
related to Internet-scale inference and evaluation of malicious activities generated by
compromised IoT devices to facilitate prompt detection, mitigation and prevention of
IoT exploitation.
In this context, we initially provide a unique taxonomy, which sheds the light
on IoT vulnerabilities from five di↵erent perspectives. Subsequently, we address the
task of inference and characterization of IoT maliciousness by leveraging active and
passive measurements. To support large-scale empirical data analytics in the context
of IoT, we made available corresponding raw data through an authenticated platform. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection
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Preemptive distributed intrusion detection using mobile agents.January 2002 (has links)
by Chan Pui Chung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves [56]-[61]). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Trends --- p.1 / Chapter 1.2 --- What this Thesis Contains --- p.3 / Chapter 2 --- Background --- p.5 / Chapter 2.1 --- Computer Security --- p.5 / Chapter 2.2 --- Anti-intrusion Techniques --- p.6 / Chapter 2.3 --- The Need for Intrusion Detection System --- p.7 / Chapter 2.4 --- Intrusion Detection System Categorization --- p.8 / Chapter 2.4.1 --- Network-based vs. Host-based --- p.8 / Chapter 2.4.2 --- Anomaly Detection vs. Misuse Detection --- p.10 / Chapter 2.4.3 --- Centralized vs. Distributed --- p.11 / Chapter 2.5 --- Agent-based IDS --- p.12 / Chapter 2.6 --- Mobile agent-based IDS --- p.12 / Chapter 3 --- Survey on Intrusion Step --- p.14 / Chapter 3.1 --- Introduction --- p.14 / Chapter 3.2 --- Getting information before break in --- p.14 / Chapter 3.2.1 --- Port scanning --- p.14 / Chapter 3.2.2 --- Sniffing --- p.16 / Chapter 3.2.3 --- Fingerprinting --- p.17 / Chapter 3.3 --- Intrusion method --- p.17 / Chapter 3.3.1 --- DOS and DDOS --- p.17 / Chapter 3.3.2 --- Password cracking --- p.18 / Chapter 3.3.3 --- Buffer overflows --- p.19 / Chapter 3.3.4 --- Race Condition --- p.20 / Chapter 3.3.5 --- Session Hijacking --- p.20 / Chapter 3.3.6 --- Computer Virus --- p.21 / Chapter 3.3.7 --- Worms --- p.21 / Chapter 3.3.8 --- Trojan Horse --- p.22 / Chapter 3.3.9 --- Social Engineering --- p.22 / Chapter 3.3.10 --- Physical Attack --- p.23 / Chapter 3.4 --- After intrusion --- p.23 / Chapter 3.4.1 --- Covering Tracks --- p.23 / Chapter 3.4.2 --- Back-doors --- p.23 / Chapter 3.4.3 --- Rootkits --- p.23 / Chapter 3.5 --- Conclusion --- p.24 / Chapter 4 --- A Survey on Intrusion Detection System --- p.25 / Chapter 4.1 --- Introduction --- p.25 / Chapter 4.2 --- Information Source --- p.25 / Chapter 4.2.1 --- Host-based Source --- p.25 / Chapter 4.2.2 --- Network-based Source --- p.26 / Chapter 4.2.3 --- Out-of-band Source --- p.27 / Chapter 4.2.4 --- Data Fusion from multiple sources --- p.27 / Chapter 4.3 --- Detection Technology --- p.28 / Chapter 4.3.1 --- Intrusion signature --- p.28 / Chapter 4.3.2 --- Threshold Detection --- p.31 / Chapter 4.3.3 --- Statistical Analysis --- p.31 / Chapter 4.3.4 --- Neural Network --- p.32 / Chapter 4.3.5 --- Artificial Immune System --- p.33 / Chapter 4.3.6 --- Data Mining --- p.33 / Chapter 4.3.7 --- Traffic Analysis --- p.34 / Chapter 4.4 --- False Alarm Rate --- p.35 / Chapter 4.5 --- Response --- p.35 / Chapter 4.6 --- Difficulties in IDS --- p.36 / Chapter 4.6.1 --- Base Rate Fallacy --- p.36 / Chapter 4.6.2 --- Denial of Service Attack against IDS --- p.37 / Chapter 4.6.3 --- Insertion and Evasion attack against the Network-Based IDS . --- p.37 / Chapter 4.7 --- Conclusion --- p.38 / Chapter 5 --- Preemptive Distributed Intrusion Detection using Mobile Agents --- p.39 / Chapter 5.1 --- Introduction --- p.39 / Chapter 5.2 --- Architecture Design --- p.40 / Chapter 5.2.1 --- Overview --- p.40 / Chapter 5.2.2 --- Agents involved --- p.40 / Chapter 5.2.3 --- Clustering --- p.42 / Chapter 5.3 --- How it works --- p.44 / Chapter 5.3.1 --- Pseudo codes of operations --- p.48 / Chapter 5.4 --- Advantages --- p.49 / Chapter 5.5 --- Drawbacks & Possible Solutions --- p.49 / Chapter 5.6 --- Other Possible Mode of Operation --- p.50 / Chapter 5.7 --- Conclusion --- p.51 / Chapter 6 --- Conclusion --- p.52 / A Paper Derived from this Thesis --- p.54 / Bibliography --- p.55
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Secure execution of mobile agents on open networks using cooperative agents.January 2002 (has links)
Yu Chiu-Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 93-96). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgements --- p.ii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Advantages of mobile agents --- p.2 / Chapter 1.2 --- Security --- p.3 / Chapter 1.3 --- Contributions --- p.3 / Chapter 1.4 --- Structure --- p.4 / Chapter 2 --- The Problem of Execution Tampering Attack --- p.5 / Chapter 2.1 --- Mobile agent execution model --- p.5 / Chapter 2.2 --- Tampering attack from malicious hosts --- p.5 / Chapter 2.3 --- Open network environment --- p.6 / Chapter 2.4 --- Conclusion --- p.6 / Chapter 3 --- Existing Approaches to Solve the Execution Tampering Prob- lem --- p.8 / Chapter 3.1 --- Introduction --- p.8 / Chapter 3.2 --- Trusted execution environment --- p.9 / Chapter 3.2.1 --- Closed system --- p.9 / Chapter 3.2.2 --- Trusted hardware --- p.9 / Chapter 3.3 --- Tamper-detection --- p.11 / Chapter 3.3.1 --- Execution tracing --- p.11 / Chapter 3.4 --- Tamper-prevention --- p.12 / Chapter 3.4.1 --- Blackbox security --- p.12 / Chapter 3.4.2 --- Time limited blackbox --- p.13 / Chapter 3.4.3 --- Agent mess-up --- p.15 / Chapter 3.4.4 --- Addition of noisy code --- p.15 / Chapter 3.4.5 --- Co-operating agents --- p.16 / Chapter 3.5 --- Conclusion --- p.17 / Chapter 4 --- Tamper-Detection Mechanism of Our Protocol --- p.18 / Chapter 4.1 --- Introduction --- p.18 / Chapter 4.2 --- Execution tracing --- p.18 / Chapter 4.3 --- Code obfuscation --- p.21 / Chapter 4.3.1 --- Resilience of obfuscating transformation --- p.22 / Chapter 4.4 --- Execution tracing with obfuscated program --- p.23 / Chapter 4.5 --- Conclusion --- p.27 / Chapter 5 --- A Flexible Tamper-Detection Protocol by Using Cooperating Agents --- p.28 / Chapter 5.1 --- Introduction --- p.28 / Chapter 5.1.1 --- Agent model --- p.29 / Chapter 5.1.2 --- Execution model --- p.30 / Chapter 5.1.3 --- System model --- p.30 / Chapter 5.1.4 --- Failure model --- p.30 / Chapter 5.2 --- The tamper-detection protocol --- p.30 / Chapter 5.3 --- Fault-tolerance policy --- p.38 / Chapter 5.4 --- Costs of the protocol --- p.38 / Chapter 5.5 --- Discussion --- p.40 / Chapter 5.6 --- Conclusion --- p.42 / Chapter 6 --- Verification of the Protocol by BAN Logic --- p.43 / Chapter 6.1 --- Introduction --- p.43 / Chapter 6.2 --- Modifications to BAN logic --- p.44 / Chapter 6.3 --- Term definitions --- p.45 / Chapter 6.4 --- Modeling of our tamper-detection protocol --- p.46 / Chapter 6.5 --- Goals --- p.47 / Chapter 6.6 --- Sub-goals --- p.48 / Chapter 6.7 --- Assumptions --- p.48 / Chapter 6.8 --- Verification --- p.49 / Chapter 6.9 --- Conclusion --- p.53 / Chapter 7 --- Experimental Results Related to the Protocol --- p.54 / Chapter 7.1 --- Introduction --- p.54 / Chapter 7.2 --- Experiment environment --- p.54 / Chapter 7.3 --- Experiment procedures --- p.55 / Chapter 7.4 --- Experiment implementation --- p.56 / Chapter 7.5 --- Experimental results --- p.61 / Chapter 7.6 --- Conclusion --- p.65 / Chapter 8 --- Extension to Solve the ´حFake Honest Host´ح Problem --- p.68 / Chapter 8.1 --- Introduction --- p.68 / Chapter 8.2 --- "The method to solve the ""fake honest host"" problem" --- p.69 / Chapter 8.2.1 --- Basic idea --- p.69 / Chapter 8.2.2 --- Description of the method --- p.69 / Chapter 8.3 --- Conclusion --- p.71 / Chapter 9 --- Performance Improvement by Program Slicing --- p.73 / Chapter 9.1 --- Introduction --- p.73 / Chapter 9.2 --- Deployment of program slicing --- p.73 / Chapter 9.3 --- Conclusion --- p.75 / Chapter 10 --- Increase Scalability by Supporting Multiple Mobile Agents --- p.76 / Chapter 10.1 --- Introduction --- p.76 / Chapter 10.2 --- Supporting multiple mobile agents --- p.76 / Chapter 10.3 --- Conclusion --- p.78 / Chapter 11 --- Deployment of Trust Relationship in the Protocol --- p.79 / Chapter 11.1 --- Introduction --- p.79 / Chapter 11.2 --- Deployment of trust relationship --- p.79 / Chapter 11.3 --- Conclusion --- p.82 / Chapter 12 --- Conclusions and Future Work --- p.83 / A Data of Experimental Results --- p.86 / Publication --- p.92 / Bibliography --- p.93
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A software cipher system for providing security for computer dataWalker, John Cleve January 2010 (has links)
Typescript, etc. / Digitized by Kansas Correctional Industries
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Levels of protection and associated overhead in the formulary protection systemKleopfer, Lyle January 2010 (has links)
Digitized by Kansas Correctional Industries
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Regions Security Policy (RSP) : applying regions to network security / RSP : applying regions to network securityBaratz, Joshua W. (Joshua William), 1981- January 2004 (has links)
Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004. / Includes bibliographical references (p. 51-54). / The Regions network architecture is a new look at network organization that groups nodes into regions based on common purposes. This shift from strict network topology groupings of nodes requires a change in security systems. This thesis designs and implements the Regions Security Policy (RSP). RSP allows a unified security policy to be set across a region, fully controlling data as it enters into, exits from, and transits within a region. In doing so, it brings together several existing security solutions so as to provide security comparable to existing systems that is more likely to function correctly. / by Joshua W. Baratz. / M.Eng.and S.B.
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The molecularisation of security : medical countermeasure development and the Biomedical Advanced Research and Development Authority (BARDA), 2006-2015Long, Christopher January 2017 (has links)
No description available.
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Machine learning algorithms for the analysis and detection of network attacksUnknown Date (has links)
The Internet and computer networks have become an important part of our
organizations and everyday life. With the increase in our dependence on computers
and communication networks, malicious activities have become increasingly prevalent.
Network attacks are an important problem in today’s communication environments.
The network traffic must be monitored and analyzed to detect malicious activities
and attacks to ensure reliable functionality of the networks and security of users’
information. Recently, machine learning techniques have been applied toward the
detection of network attacks. Machine learning models are able to extract similarities
and patterns in the network traffic. Unlike signature based methods, there is no need
for manual analyses to extract attack patterns. Applying machine learning algorithms
can automatically build predictive models for the detection of network attacks.
This dissertation reports an empirical analysis of the usage of machine learning
methods for the detection of network attacks. For this purpose, we study the detection
of three common attacks in computer networks: SSH brute force, Man In The Middle
(MITM) and application layer Distributed Denial of Service (DDoS) attacks. Using
outdated and non-representative benchmark data, such as the DARPA dataset, in the intrusion detection domain, has caused a practical gap between building detection
models and their actual deployment in a real computer network. To alleviate this
limitation, we collect representative network data from a real production network for
each attack type. Our analysis of each attack includes a detailed study of the usage
of machine learning methods for its detection. This includes the motivation behind
the proposed machine learning based detection approach, the data collection process,
feature engineering, building predictive models and evaluating their performance.
We also investigate the application of feature selection in building detection models
for network attacks. Overall, this dissertation presents a thorough analysis on how
machine learning techniques can be used to detect network attacks. We not only study
a broad range of network attacks, but also study the application of different machine
learning methods including classification, anomaly detection and feature selection for
their detection at the host level and the network level. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection
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Design of smart card enabled protocols for micro-payment and rapid application development builder for e-commerce.January 2001 (has links)
by Tsang Hin Chung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 118-124). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Authentication and Transaction Protocol --- p.2 / Chapter 1.2 --- E-Commerce Enabler --- p.3 / Chapter 2 --- Literature Review --- p.4 / Chapter 2.1 --- Cryptographic Preliminaries --- p.4 / Chapter 2.1.1 --- One-Way Hash Function --- p.4 / Chapter 2.1.2 --- Triple DES --- p.5 / Chapter 2.1.3 --- RSA --- p.7 / Chapter 2.1.4 --- Elliptic Curve --- p.8 / Chapter 2.2 --- Smart Cards --- p.8 / Chapter 2.2.1 --- Smart Card Operating Systems --- p.11 / Chapter 2.2.2 --- Java Card --- p.12 / Chapter 2.3 --- Authentication Protocol --- p.14 / Chapter 2.3.1 --- Properties --- p.15 / Chapter 2.3.2 --- Survey --- p.16 / Chapter 2.4 --- Transaction Protocol --- p.19 / Chapter 2.5 --- BAN Logic --- p.20 / Chapter 2.5.1 --- Notation --- p.20 / Chapter 2.5.2 --- Logical Postulates --- p.22 / Chapter 2.5.3 --- Protocol Analysis --- p.25 / Chapter 3 --- Authentication Protocol --- p.26 / Chapter 3.1 --- Formulation of Problem --- p.26 / Chapter 3.2 --- The New Idea --- p.27 / Chapter 3.3 --- Assumptions --- p.29 / Chapter 3.4 --- Trust Model --- p.29 / Chapter 3.5 --- Protocol --- p.30 / Chapter 3.5.1 --- Registration --- p.30 / Chapter 3.5.2 --- Local Authentication --- p.31 / Chapter 3.5.3 --- Remote Authentication --- p.33 / Chapter 3.5.4 --- Silent Key Distribution Scheme --- p.35 / Chapter 3.5.5 --- Advantages --- p.37 / Chapter 3.6 --- BAN Logic Analysis --- p.38 / Chapter 3.7 --- Experimental Evaluation --- p.43 / Chapter 3.7.1 --- Configuration --- p.44 / Chapter 3.7.2 --- Performance Analysis --- p.45 / Chapter 4 --- Transaction Protocol --- p.51 / Chapter 4.1 --- Assumptions --- p.52 / Chapter 4.2 --- Protocol --- p.55 / Chapter 4.3 --- Conflict Resolution Policy --- p.58 / Chapter 4.4 --- Justifications --- p.58 / Chapter 4.5 --- Experimental Evaluation --- p.59 / Chapter 4.5.1 --- Configuration --- p.59 / Chapter 4.5.2 --- Performance Analysis --- p.60 / Chapter 5 --- E-Commerce Builder --- p.65 / Chapter 5.1 --- Overview --- p.66 / Chapter 5.2 --- Design of Smart RAD --- p.68 / Chapter 5.2.1 --- Mechanism --- p.68 / Chapter 5.2.2 --- Java Card Layer --- p.69 / Chapter 5.2.3 --- Host Layer --- p.71 / Chapter 5.2.4 --- Server Layer --- p.72 / Chapter 5.3 --- Implementation --- p.73 / Chapter 5.3.1 --- Implementation Reflection --- p.73 / Chapter 5.3.2 --- Implementation Issues --- p.76 / Chapter 5.4 --- Evaluation --- p.77 / Chapter 5.5 --- An Application Example: Multi-MAX --- p.79 / Chapter 5.5.1 --- System Model --- p.79 / Chapter 5.5.2 --- Design Issues --- p.80 / Chapter 5.5.3 --- Implementation Issues --- p.80 / Chapter 5.5.4 --- Evaluation --- p.84 / Chapter 5.6 --- Future Work --- p.89 / Chapter 6 --- Conclusion --- p.91 / Chapter A --- Detail Experimental Result --- p.93 / Chapter A.1 --- Authentication Time Measurement --- p.94 / Chapter A.2 --- On-Card and Off-Card Computation Time in Authentication --- p.95 / Chapter A.3 --- Authentication Time with Different Servers --- p.96 / Chapter A.4 --- Transaction Time Measurement --- p.97 / Chapter A.5 --- On-card and Off-card Computation Time in Transaction --- p.97 / Chapter B --- UML Diagram --- p.99 / Chapter B.1 --- Package cuhk.cse.demo.applet --- p.99 / Chapter B.2 --- Package cuhk.cse.demo.client --- p.105 / Chapter B.3 --- Package server --- p.110 / Chapter C --- Glossary and Abbreviation --- p.115 / Bibliography --- p.118
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Cyber Power and the International SystemLonergan, Shawn William January 2017 (has links)
This dissertation is comprised of three separate papers that address how cyber power contributes to national power and the implications for international security posed by cyber operations. The first paper, “Cyber Power and International Stability: Assessing Deterrence and Escalation in Cyberspace,” posits that there are unique attributes that define the cyber domain and that have direct implications on deterrence and escalation dynamics between state actors. The second paper, “Arms Control and Confidence Building Measures for the Cyber Domain,” explores at various mechanisms that states have traditionally used to foster stability and prevent inadvertent conflict and assesses their applicability to controlling cyber operations. Finally, “The Logic of Coercion in Cyberspace” delves into the role of cyber operations as both inadvertent and deliberate signals and assesses their utility as a coercive instrument of statecraft.
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