Though Chaos Engineering is a popular method to test reliability and performance assurance, available tools can only inject random or manually curated faults into a target system. Given the vast array of faults that can be injected, it is crucial to a.) intelligently pick the faults that can have tangible effects, b.) increase the test coverage, and c.) reduce the overall time needed to assess the reliability of a system under adverse conditions. To the effect, we are proposing to learn from past major outages and use genetic algorithm-based meta-heuristics to evolve complex fault injections.

Security against hardware Trojan that is capable to change the computational output value is accomplished by employing dual modular redundant (DMR) schedule during high level synthesis (HLS). However, building a DMR for Trojan security is nontrivial and incurs extra delay and hardware. This paper proposes a novel HLS methodology for constraint driven low cost hardware Trojan secured DMR schedule design for loop-based control data flow graphs (CDFGs). Proposed approach simultaneously explores an optimal schedule and optimal loop unrolling factor (U) combination for a low cost Trojan security aware DMR schedule. As a specific example, proposed low cost Trojan secured HLS approach relies on particle swarm optimization algorithm to explore optimized Trojan secured schedule with optimal unrolling that provides security against specific Trojan (causing change in computational output) within user provided area and delay constraints. The novel contributions of this paper are, first an exploration of a low cost Trojan security aware HLS solution for loop-based CDFGs; second, proposed encoding scheme for representing design solution comprising candidate schedule resources, candidate loop unrolling factor and candidate vendor allocation information; third, a process for exploring the a low cost vendor assignment that provides Trojan security; finally, experimental results over the standard benchmark that indicates an average reduction in final cost of ~12% compared to recent approach.

Intellectual property (IP) cores have emerged as a promising solution to the challenges of future design as well as mounting time to market pressure. However, due to increasing globalization of design supply chain, possibility of intervention and typical attacks is on the rise, which therefore mandates protection of IP cores from piracy/counterfeiting even at behavioral level. This paper presents a technique for generating low cost watermarking solution during high level synthesis (HLS) based on multi-variable signature encoding for security of reusable IP cores. The watermark generated by the proposed approach satisfies the following properties: (a) low embedding cost (b) robustness (c) low watermark creation time (d) strong proof of authorship (e) lower hardware overhead. Comparison with similar technique revealed that proposed approach obtains watermarked solution with lower embedding cost with less storage overhead and creation time.

An evolutionary algorithm (EA) driven novel design space exploration (DSE) of an optimized hardware Trojan secured datapath based on user power-delay constraint during high level synthesis (HLS) is presented. The focus on hardware Trojan secured datapath generation during HLS has been very little with absolutely zero effort so far in design space exploration of a user multi-objective (MO) constraint optimized hardware Trojan secured datapath. This problem mandates attention as producing a Trojan secured datapath is not inconsequential. Merely the detection process of Trojan is not as straightforward as concurrent error detection (CED) of transient faults as it involves the concept of multiple third party intellectual property (3PIP) vendors to facilitate detection, let aside the exploration process of a user optimized Trojan secured datapath based on MO constraints. The proposed DSE for hardware Trojan detection includes novel problem encoding technique that enables exploration of efficient distinct vendor allocation as well as enables exploration of an optimized Trojan secured datapath structure. The exploration backbone for the proposed approach is bacterial foraging optimization algorithm (BFOA) which is known for its adaptive feature (tumbling/swimming) and simplified model. Results of comparison with recent approach indicated an average improvement in quality of results (QoR) of >14.1%

A novel application of bacterial foraging optimization algorithm (BFOA) in the area of design space exploration (DSE) of datapath in high level synthesis (HLS) is presented in this paper. The BFOA has been transformed into an adaptive automated DSE framework that is capable to handle tradeoffs between area-execution time during HLS. To the authors belief, no such application (or transformation) of BFOA into DSE exist in the literature. The key sub-contributions of the proposed approach can be classified as follows: i) Exploration drift using a novel chemotaxis algorithm ii) Diversity introduction in resource configuration using a novel dispersal algorithm iii) Performance analysis of proposed and related approaches on metrics such as generational distance, maximum pareto-optimal front error, spacing, spreading and weighted metric. Finally, results indicated an average improvement in Quality of Results (QoR) of ∼6% and reduction in exploration runtime of > 18% compared to three recent approaches based on PSO and GA.