An ideology is sweeping Europe and the world which threatens democracy and the rule of law. The post-national ideology, which posits that nation-states are no longer capable of running their own affairs in a modern, interdependent economy, confuses the constitution of a state with the power of its government, and ignores the importance of the sense of community essential to any democratic debate. A rigorous synthesis of historical and philosophical arguments, THE TAINTED SOURCE is a powerful appeal in favour of the constitutional foundations of the liberal order. Post-national structures - multinational companies, 'region-states' and supranational organisations such as the European Union - are corrosive of liberal values, to such an extent that John Laughland makes it devastatingly clear that the post-national ideology formed a crucial core of Nazi economic and political thinking. Like the European ideology of today, it was predicted on dissolving the nation-state and the liberal order.
This text provides a broad and deep analysis of the underlying assumptions governing modern European politics, and of the way European union works in reality. It argues that the plans to integrate Western Europe around a single currency are dangerous for democracy and the rule of law. It also contends that Western policy towards Eastern Europe and Russia is similarly misguided, and that the current drift will only encourage the hegemony of Russia over the West. John Laughland shows how the European idea was warmly embraced by Fascists and Nazis during World War II - especially in France, Germany and Belgium. He reiterates the essential link between free trade on the one hand, and democratic politics, nationhood and the rule of law on the other.
All justified beliefs ultimately rest on attitudes that are immediately justified. This book illuminates the nature of immediate justification and the states that provide it. Simply put, immediate justification arises from how things appear to us—from all and only our "seemings." The author defends each aspect of this "seemings foundationalism," including the assumption of foundationalism itself. Most notably, the author draws from common sense philosopher Thomas Reid to present new and improved arguments for phenomenal conservatism and gives the first systematic argument that seemings alone are capable of immediately justifying. The discussion delves deeply into the nature of seemings and how it is that their assertive phenomenal character makes them (and them alone) capable of immediately justifying. Along the way, the author makes novel contributions to perennial debates such as: internalism versus externalism, deontologism and epistemic blame, epistemic circularity, and the common sense response to skepticism. Seemings and the Foundations of Justification will appeal to scholars and advanced students interested in epistemology, Thomas Reid, or the common sense tradition.
In recent years, binary code analysis, i.e., applying program analysis directly at the machine code level, has become an increasingly important topic of study. This is driven to a large extent by the information security community, where security auditing of closed-source software and analysis of malware are important applications. Since most of the high-level semantics of the original source code are lost upon compilation to executable code, static analysis is intractable for, e.g., fine-grained information flow analysis of binary code. Dynamic analysis, however, does not suffer in the same way from reduced accuracy in the absence of high-level semantics, and is therefore also more readily applicable to binary code. Since fine-grained dynamic analysis often requires recording detailed information about every instruction execution, scalability can become a significant challenge. In this thesis, we address the scalability challenges of two powerful dynamic analysis methods whose widespread use has, so far, been impeded by their lack of scalability: dynamic slicing and instruction trace alignment. Dynamic slicing provides fine-grained information about dependencies between individual instructions, and can be used both as a powerful debugging aid and as a foundation for other dynamic analysis techniques. Instruction trace alignment provides a means for comparing executions of two similar programs and has important applications in, e.g., malware analysis, security auditing, and plagiarism detection. We also apply our work on scalable dynamic analysis in two novel approaches to improve fuzzing — a popular random testing technique that is widely used in industry to discover security vulnerabilities. To use dynamic slicing, detailed information about a program execution must first be recorded. Since the amount of information is often too large to fit in main memory, existing dynamic slicing methods apply various time-versus-space trade-offs to reduce memory requirements. However, these trade-offs result in very high time overheads, limiting the usefulness of dynamic slicing in practice. In this thesis, we show that the speed of dynamic slicing can be greatly improved by carefully designing data structures and algorithms to exploit temporal locality of programs. This allows avoidance of the expensive trade-offs used in earlier methods by accessing recorded runtime information directly from secondary storage without significant random-access overhead. In addition to being a standalone contribution, scalable dynamic slicing also forms integral parts of our contributions to fuzzing. Our first contribution uses dynamic slicing and binary code mutation to automatically turn an existing executable into a test generator. In our experiments, this new approach to fuzzing achieved about an order of magnitude better code coverage than traditional mutational fuzzing and found several bugs in popular Linux software. The second work on fuzzing presented in this thesis uses dynamic slicing to accelerate the state-of-the-art fuzzer AFL by focusing the fuzzing effort on previously unexplored parts of the input space. For the second dynamic analysis technique whose scalability we sought to improve — instruction trace alignment — we employed techniques used in speech recognition and information retrieval to design what is, to the best of our knowledge, the first general approach to aligning realistically long program traces. We show in our experiments that this method is capable of producing meaningful alignments even in the presence of significant syntactic differences stemming from, for example, the use of different compilers or optimization levels.
This book constitutes the refereed proceedings of the 36th IFIP TC 11 International Conference on Information Security and Privacy Protection, SEC 2021, held in Oslo, Norway, in June 2021.* The 28 full papers presented were carefully reviewed and selected from 112 submissions. The papers present novel research on theoretical and practical aspects of security and privacy protection in ICT systems. They are organized in topical sections on digital signatures; vulnerability management; covert channels and cryptography; application and system security; privacy; network security; machine learning for security; and security management. *The conference was held virtually.
This book constitutes the thoroughly refereed roceedings of the 13th International Conference on Security and Privacy in Communications Networks, SecureComm 2017, held in Niagara Falls, ON, Canada, in October 2017.The 31 revised regular papers and 15 short papers were carefully reviewed and selected from 105 submissions. The topics range from security and privacy in machine learning to differential privacy, which are currently hot research topics in cyber security research.
Malicious software (i.e., malware) has become a severe threat to interconnected computer systems for decades and has caused billions of dollars damages each year. A large volume of new malware samples are discovered daily. Even worse, malware is rapidly evolving becoming more sophisticated and evasive to strike against current malware analysis and defense systems. Automatic Malware Analysis presents a virtualized malware analysis framework that addresses common challenges in malware analysis. In regards to this new analysis framework, a series of analysis techniques for automatic malware analysis is developed. These techniques capture intrinsic characteristics of malware, and are well suited for dealing with new malware samples and attack mechanisms.
Botnets have become the platform of choice for launching attacks and committing fraud on the Internet. A better understanding of Botnets will help to coordinate and develop new technologies to counter this serious security threat. Botnet Detection: Countering the Largest Security Threat consists of chapters contributed by world-class leaders in this field, from the June 2006 ARO workshop on Botnets. This edited volume represents the state-of-the-art in research on Botnets.
This is an open access book. As a leading role in the global megatrend of scientific innovation, China has been creating a more and more open environment for scientific innovation, increasing the depth and breadth of academic cooperation, and building a community of innovation that benefits all. These endeavors have made new contribution to globalization and creating a community of shared future. With the rapid development of modern economic society, in the process of economic management, informatization has become the mainstream of economic development in the future. At the same time, with the emergence of advanced management technologies such as blockchain technology and big data technology, real market information can be quickly obtained in the process of economic management, which greatly reduces the operating costs of the market economy and effectively enhances the management level of operators, thus contributing to the sustained, rapid and healthy development of the market economy. Under the new situation, the innovative application of economic management research is of great practical significance. 2022 International Conference on Bigdata, Blockchain and Economic Management (ICBBEM 2022) will be held on March 25–27, 2022 in Wuhan, China. ICBBEM 2022 will focus on the latest fields of Bigdata, Blockchain and Economic Management to provide an international platform for experts, professors, scholars and engineers from universities, scientific institutes, enterprises and government-affiliated institutions at home and abroad to share experiences, to expand professional fields, to exchange new ideas face to face, to present research results, and to discuss the key challenging issues and research directions facing the development of this field, with a view to promoting the development and application of theories and technologies in universities and enterprises.
