ALGEBRAIC COUNTERMEASURE TO ENHANCE THE IMPROVED SUMMATION GENERATOR WITH 2-BIT MEMORY

Recently proposed algebraic attack has been shown to be very effective on several stream ciphers. In this paper, we have investigated the resistance of PingPong family of stream ciphers against algebraic attacks. This stream cipher was proposed in 2008 to enhance the security of the improved summation generator against the algebraic attack. In particular, we focus on the PingPong-128 stream cipher’s resistance against algebraic attack in this paper. In our analysis, it is found that an algebraic attack on PingPong family of stream ciphers require much more operations compare to the exhaustive key search on the internal state of the LFSRs. It will be shown that due to the irregular and mutual clock controlling in PingPong stream cipher the degree of the generated equation tends to grow up with each successive clock which in turn increases the overall complexity of an algebraic attack. Along with the PingPong 128 stream cipher the other instances of PingPong family stream ciphers are also investigated against the algebraic attack. Our analysis shows that, PingPong family stream ciphers are highly resistant against the algebraic attack due to their mutual and irregular clocking function

Artificial intelligence methods for security and cyber security systems

This research is in threat analysis and countermeasures employing Artificial Intelligence (AI) methods within the civilian domain, where safety and mission-critical aspects are essential. AI has challenges of repeatable determinism and decision explanation. This research proposed methods for dense and convolutional networks that provided repeatable determinism. In dense networks, the proposed alternative method had an equal performance with more structured learnt weights. The proposed method also had earlier learning and higher accuracy in the Convolutional networks. When demonstrated in colour image classification, the accuracy improved in the first epoch to 67%, from 29% in the existing scheme. Examined in transferred learning with the Fast Sign Gradient Method (FSGM) as an analytical method to control distortion of dissimilarity, a finding was that the proposed method had more significant retention of the learnt model, with 31% accuracy instead of 9%. The research also proposed a threat analysis method with set-mappings and first principle analytical steps applied to a Symbolic AI method using an algebraic expert system with virtualized neurons. The neural expert system method demonstrated the infilling of parameters by calculating beamwidths with variations in the uncertainty of the antenna type. When combined with a proposed formula extraction method, it provides the potential for machine learning of new rules as a Neuro-Symbolic AI method. The proposed method uses extra weights allocated to neuron input value ranges as activation strengths. The method simplifies the learnt representation reducing model depth, thus with less significant dropout potential. Finally, an image classification method for emitter identification is proposed with a synthetic dataset generation method and shows the accurate identification between fourteen radar emission modes with high ambiguity between them (and achieved 99.8% accuracy). That method would be a mechanism to recognize non-threat civil radars aimed at threat alert when deviations from those civilian emitters are detected

Stream ciphers for secure display

In any situation where private, proprietary or highly confidential material is being dealt with, the need to consider aspects of data security has grown ever more important. It is usual to secure such data from its source, over networks and on to the intended recipient. However, data security considerations typically stop at the recipient's processor, leaving connections to a display transmitting raw data which is increasingly in a digital format and of value to an adversary. With a progression to wireless display technologies the prominence of this vulnerability is set to rise, making the implementation of 'secure display' increasingly desirable. Secure display takes aspects of data security right to the display panel itself, potentially minimising the cost, component count and thickness of the final product. Recent developments in display technologies should help make this integration possible. However, the processing of large quantities of time-sensitive data presents a significant challenge in such resource constrained environments. Efficient high- throughput decryption is a crucial aspect of the implementation of secure display and one for which the widely used and well understood block cipher may not be best suited. Stream ciphers present a promising alternative and a number of strong candidate algorithms potentially offer the hardware speed and efficiency required. In the past, similar stream ciphers have suffered from algorithmic vulnerabilities. Although these new-generation designs have done much to respond to this concern, the relatively short 80-bit key lengths of some proposed hardware candidates, when combined with ever-advancing computational power, leads to the thesis identifying exhaustive search of key space as a potential attack vector. To determine the value of protection afforded by such short key lengths a unique hardware key search engine for stream ciphers is developed that makes use of an appropriate data element to improve search efficiency. The simulations from this system indicate that the proposed key lengths may be insufficient for applications where data is of long-term or high value. It is suggested that for the concept of secure display to be accepted, a longer key length should be used

Decryption Failure Attacks on Post-Quantum Cryptography

This dissertation discusses mainly new cryptanalytical results related to issues of securely implementing the next generation of asymmetric cryptography, or Public-Key Cryptography (PKC).PKC, as it has been deployed until today, depends heavily on the integer factorization and the discrete logarithm problems.Unfortunately, it has been well-known since the mid-90s, that these mathematical problems can be solved due to Peter Shor's algorithm for quantum computers, which achieves the answers in polynomial time.The recently accelerated pace of R&D towards quantum computers, eventually of sufficient size and power to threaten cryptography, has led the crypto research community towards a major shift of focus.A project towards standardization of Post-quantum Cryptography (PQC) was launched by the US-based standardization organization, NIST. PQC is the name given to algorithms designed for running on classical hardware/software whilst being resistant to attacks from quantum computers.PQC is well suited for replacing the current asymmetric schemes.A primary motivation for the project is to guide publicly available research toward the singular goal of finding weaknesses in the proposed next generation of PKC.For public key encryption (PKE) or digital signature (DS) schemes to be considered secure they must be shown to rely heavily on well-known mathematical problems with theoretical proofs of security under established models, such as indistinguishability under chosen ciphertext attack (IND-CCA).Also, they must withstand serious attack attempts by well-renowned cryptographers both concerning theoretical security and the actual software/hardware instantiations.It is well-known that security models, such as IND-CCA, are not designed to capture the intricacies of inner-state leakages.Such leakages are named side-channels, which is currently a major topic of interest in the NIST PQC project.This dissertation focuses on two things, in general:1) how does the low but non-zero probability of decryption failures affect the cryptanalysis of these new PQC candidates?And 2) how might side-channel vulnerabilities inadvertently be introduced when going from theory to the practice of software/hardware implementations?Of main concern are PQC algorithms based on lattice theory and coding theory.The primary contributions are the discovery of novel decryption failure side-channel attacks, improvements on existing attacks, an alternative implementation to a part of a PQC scheme, and some more theoretical cryptanalytical results

Unified field multiplier for GF(p) and GF(2 n) with novel digit encoding

In recent years, there has been an increase in demand for unified field multipliers for Elliptic Curve Cryptography in the electronics industry because they provide flexibility for customers to choose between Prime (GF(p)) and Binary (GF(2")) Galois Fields. Also, having the ability to carry out arithmetic over both GF(p) and GF(2") in the same hardware provides the possibility of performing any cryptographic operation that requires the use of both fields. The unified field multiplier is relatively future proof compared with multipliers that only perform arithmetic over a single chosen field. The security provided by the architecture is also very important. It is known that the longer the key length, the more susceptible the system is to differential power attacks due to the increased amount of data leakage. Therefore, it is beneficial to design hardware that is scalable, so that more data can be processed per cycle. Another advantage of designing a multiplier that is capable of dealing with long word length is improvement in performance in terms of delay, because less cycles are needed. This is very important because typical elliptic curve cryptography involves key size of 160 bits. A novel unified field radix-4 multiplier using Montgomery Multiplication for the use of G(p) and GF(2") has been proposed. This design makes use of the unexploited state in number representation for operation in GF(2") where all carries are suppressed. The addition is carried out using a modified (4:2) redundant adder to accommodate the extra 1 * state. The proposed adder and the partial product generator design are capable of radix-4 operation, which reduces the number of computation cycles required. Also, the proposed adder is more scalable than existing designs.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

Unified field multiplier for GF(p) and GF(2 n) with novel digit encoding

In recent years, there has been an increase in demand for unified field multipliers for Elliptic Curve Cryptography in the electronics industry because they provide flexibility for customers to choose between Prime (GF(p)) and Binary (GF(2')) Galois Fields. Also, having the ability to carry out arithmetic over both GF(p) and GF(2') in the same hardware provides the possibility of performing any cryptographic operation that requires the use of both fields. The unified field multiplier is relatively future proof compared with multipliers that only perform arithmetic over a single chosen field. The security provided by the architecture is also very important. It is known that the longer the key length, the more susceptible the system is to differential power attacks due to the increased amount of data leakage. Therefore, it is beneficial to design hardware that is scalable, so that more data can be processed per cycle. Another advantage of designing a multiplier that is capable of dealing with long word length is improvement in performance in terms of delay, because less cycles are needed. This is very important because typical elliptic curve cryptography involves key size of 160 bits. A novel unified field radix-4 multiplier using Montgomery Multiplication for the use of G(p) and GF(2') has been proposed. This design makes use of the unexploited state in number representation for operation in GF(2') where all carries are suppressed. The addition is carried out using a modified (4:2) redundant adder to accommodate the extra 1 * state. The proposed adder and the partial product generator design are capable of radix-4 operation, which reduces the number of computation cycles required. Also, the proposed adder is more scalable than existing designs

Principles of Security and Trust: 7th International Conference, POST 2018, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2018, Thessaloniki, Greece, April 14-20, 2018, Proceedings

authentication; computer science; computer software selection and evaluation; cryptography; data privacy; formal logic; formal methods; formal specification; internet; privacy; program compilers; programming languages; security analysis; security systems; semantics; separation logic; software engineering; specifications; verification; world wide we

Profiling side-channel attacks on cryptographic algorithms

Traditionally, attacks on cryptographic algorithms looked for mathematical weaknesses in the underlying structure of a cipher. Side-channel attacks, however, look to extract secret key information based on the leakage from the device on which the cipher is implemented, be it smart-card, microprocessor, dedicated hardware or personal computer. Attacks based on the power consumption, electromagnetic emanations and execution time have all been practically demonstrated on a range of devices to reveal partial secret-key information from which the full key can be reconstructed. The focus of this thesis is power analysis, more specifically a class of attacks known as profiling attacks. These attacks assume a potential attacker has access to, or can control, an identical device to that which is under attack, which allows him to profile the power consumption of operations or data flow during encryption. This assumes a stronger adversary than traditional non-profiling attacks such as differential or correlation power analysis, however the ability to model a device allows templates to be used post-profiling to extract key information from many different target devices using the power consumption of very few encryptions. This allows an adversary to overcome protocols intended to prevent secret key recovery by restricting the number of available traces. In this thesis a detailed investigation of template attacks is conducted, along with how the selection of various attack parameters practically affect the efficiency of the secret key recovery, as well as examining the underlying assumption of profiling attacks in that the power consumption of one device can be used to extract secret keys from another. Trace only attacks, where the corresponding plaintext or ciphertext data is unavailable, are then investigated against both symmetric and asymmetric algorithms with the goal of key recovery from a single trace. This allows an adversary to bypass many of the currently proposed countermeasures, particularly in the asymmetric domain. An investigation into machine-learning methods for side-channel analysis as an alternative to template or stochastic methods is also conducted, with support vector machines, logistic regression and neural networks investigated from a side-channel viewpoint. Both binary and multi-class classification attack scenarios are examined in order to explore the relative strengths of each algorithm. Finally these machine-learning based alternatives are empirically compared with template attacks, with their respective merits examined with regards to attack efficiency